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Discrete GeometryGraph TheoryTheoretical Computer Science·Captain: wurtle

L1 Embeddings of Graphs of Bounded TreewidthResearch Paper

Motivation: L1L_1L1​ embeddings, sparsest cut and the GNRS conjecture

A finite metric embeds into L1L_1L1​ exactly when it is a nonnegative combination of cut metrics δS(u,v)=∣1S(u)−1S(v)∣\delta_S(u,v)=|\mathbf 1_S(u)-\mathbf 1_S(v)|δS​(u,v)=∣1S​(u)−1S​(v)∣. This makes L1L_1L1​ distortion the right measure for the flow–cut gap: given edge capacities and pairwise demands, the ratio between the sparsest cut value ϕ∗\phi_*ϕ∗​ and the maximum concurrent flow λ∗\lambda_*λ∗​. Linial, London and Rabinovich (1995) and Aumann and Rabani (1998) developed this connection, and Gupta, Newman, Rabinovich and Sinclair (2004) proved that the worst flow–cut gap on a fixed graph equals the worst L1L_1L1​ distortion of its weighted shortest-path metrics. They conjectured that every proper minor-closed family embeds into L1L_1L1​ with uniformly bounded distortion (the GNRS conjecture). Graphs of bounded treewidth form one of its basic cases.

Timeline

  • 1986 — Robertson and Seymour: excluding a fixed planar graph as a minor bounds the treewidth (JCTB 1986).
  • 2004 — Gupta, Newman, Rabinovich and Sinclair prove the treewidth-two (series-parallel) case, show that some series-parallel metrics need expected tree distortion Ω(log⁡n)\Omega(\log n)Ω(logn), and state the GNRS conjecture (Combinatorica 2004).
  • 2006 — Chekuri, Gupta, Newman, Rabinovich and Sinclair: bounded distortion for kkk-outerplanar graphs (SIDMA 2006).
  • 2008–2010 — Chakrabarti, Jaffe, Lee and Vincent obtain the optimal bound 222 for treewidth two (FOCS 2008), matched by Lee and Raghavendra (DCG 2010).
  • 2010 — Chlamtáč, Krauthgamer and Raghavendra: bounded distortion for bounded treewidth under a local-consistency assumption on small vertex sets (APPROX/RANDOM 2010).
  • 2013 — Lee and Sidiropoulos settle bounded pathwidth via stochastic tree embeddings (Combinatorica 2013); Lee and Poore treat 2-sums of a fixed finite family (SoCG 2013).
  • 2022 — Abraham, Filtser, Gupta and Neiman: O(p)O(\sqrt p)O(p​) distortion for pathwidth ppp (SICOMP 2022).
  • 2025 — Filtser et al.: optimal padded decompositions for bounded treewidth and an O(log⁡(2+t)log⁡n)O(\sqrt{\log(2+t)\log n})O(log(2+t)logn​) bound (TheoretiCS 2025).
  • 2026 — An OpenAI preprint, L1L_1L1​ Embeddings of Graphs of Bounded Treewidth (OpenAI Math Release, September 23, 2026), claims a uniform bound for every fixed treewidth. The preprint has not been peer reviewed, and its main theorem is not formally verified.

Setting

Let G=(V,E)G=(V,E)G=(V,E) be a finite connected graph with edge lengths ℓ:E→(0,∞)\ell:E\to(0,\infty)ℓ:E→(0,∞). The shortest-path metric dG,ℓ(u,v)d_{G,\ell}(u,v)dG,ℓ​(u,v) is the least total length of a path from uuu to vvv.

A tree decomposition of GGG is a finite tree TTT with bags Bt⊆VB_t\subseteq VBt​⊆V (t∈V(T)t\in V(T)t∈V(T)) such that the bags cover VVV, each edge has both endpoints in some bag, and for each vertex vvv the nodes whose bag contains vvv induce a connected subtree. In this mission, as in the source, kkk bounds the bag cardinality ∣Bt∣≤k|B_t|\le k∣Bt​∣≤k, so the treewidth bound is k−1k-1k−1.

A map F:V→ℓ1mF:V\to\ell_1^mF:V→ℓ1m​ has distortion at most CCC if dG,ℓ(u,v)≤∥F(u)−F(v)∥1≤C dG,ℓ(u,v)d_{G,\ell}(u,v)\le\|F(u)-F(v)\|_1\le C\,d_{G,\ell}(u,v)dG,ℓ​(u,v)≤∥F(u)−F(v)∥1​≤CdG,ℓ​(u,v).

Formalization targets

Goal: Theorem 1.1 (bounded-treewidth graph metrics in L1L_1L1​)

For every integer k≥2k\ge2k≥2 there is a constant Ck≥1C_k\ge1Ck​≥1 such that for every nonempty finite connected graph GGG with a tree decomposition of bag size at most kkk and every ℓ:E→(0,∞)\ell:E\to(0,\infty)ℓ:E→(0,∞), there are mmm and F:V→ℓ1mF:V\to\ell_1^mF:V→ℓ1m​ with

dG,ℓ(u,v)  ≤  ∥F(u)−F(v)∥1  ≤  Ck dG,ℓ(u,v)(u,v∈V).d_{G,\ell}(u,v)\;\le\;\|F(u)-F(v)\|_1\;\le\;C_k\,d_{G,\ell}(u,v)\qquad(u,v\in V).dG,ℓ​(u,v)≤∥F(u)−F(v)∥1​≤Ck​dG,ℓ​(u,v)(u,v∈V).

CkC_kCk​ is independent of the number of vertices, the decomposition and all ratios of edge lengths; the goal asserts only its existence. The goal statement is published on the platform with status Open: no machine-checked proof exists yet.

Significance

The result itself. The theorem settles the bounded-treewidth case of the GNRS conjecture. Through the GNRS equivalence, it gives λ∗≤ϕ∗≤Ckλ∗\lambda_*\le\phi_*\le C_k\lambda_*λ∗​≤ϕ∗​≤Ck​λ∗​ for every multicommodity instance on graphs of treewidth less than kkk. By the Robertson–Seymour excluded-planar-minor theorem it also covers every family excluding a fixed planar minor. Combined with known approximation algorithms for the minimum L1L_1L1​ distortion (Gupta–Talwar–Witmer 2013; Cohen-Addad–Mömke–Verdugo 2024), it yields fixed-parameter-time embeddings of distortion (2+ε)Ck(2+\varepsilon)C_k(2+ε)Ck​. With the planar companion preprint it covers the almost-embeddable families of Lee and Sidiropoulos.

Formalizing it. The proof constructs cut measures directly on a tree decomposition and combines them with padded random partitions from the literature. A formal proof would certify that the constants depend only on kkk, the point at which earlier approaches lost uniformity.

Difficulty

The successful pathwidth approach embeds the graph stochastically into dominating trees, but that route cannot work here: some series-parallel metrics require expected tree distortion Ω(log⁡n)\Omega(\log n)Ω(logn) (GNRS 2004, Theorem 5.6). Local-consistency approaches assume that small vertex sets admit compatible isometric cut representations, which a general bounded-treewidth metric need not provide. Multiscale constructions from padded partitions give good separation at each scale, but summing their contributions loses a factor growing with the number of scales. The construction must handle arbitrary branching of the decomposition tree and arbitrary edge-length ratios without such accumulation.

Formalization scope

  • The vertex type V is any nonempty Fintype with decidable equality; G : SimpleGraph V is connected.
  • HasTreeDecomposition G k: a tree T on Fin n, bags Fin n → Finset V covering all vertices and all edges, with the bags containing each vertex inducing a connected subgraph of T, and all bags of cardinality at most k.
  • Edge lengths are ℓ : G.edgeSet → ℝ, strictly positive. shortestPathDistance is the sInf of lengths of paths (IsPath) from uuu to vvv; this set is finite and nonempty for a connected finite graph, so the infimum is the true distance.
  • The target is the finite-dimensional space PiLp 1 (Fin m → ℝ) with mmm chosen per graph; this is the source's remark (p. 2) that the target can be taken to be finite-dimensional ℓ1\ell_1ℓ1​, and it is at least as strong as an L1(μ)L_1(\mu)L1​(μ) target.
  • The constant C depends only on k and is quantified before the graph.
  • Infrastructure needed: tree decompositions, cut-measure representations of ℓ1\ell_1ℓ1​ metrics, Markov flows on layered graphs, padded decompositions. Tree-decomposition and cut-metric infrastructure is reusable.

Selected references

  • N. Robertson, P. D. Seymour, Graph minors. V. Excluding a planar graph, J. Combin. Theory Ser. B 41 (1986), 92–114. https://doi.org/10.1016/0095-8956(86)90030-4
  • N. Linial, E. London, Y. Rabinovich, The geometry of graphs and some of its algorithmic applications, Combinatorica 15 (1995), 215–245. https://doi.org/10.1007/BF01200757
  • Y. Aumann, Y. Rabani, An O(log⁡k)O(\log k)O(logk) approximate min-cut max-flow theorem and approximation algorithm, SIAM J. Comput. 27 (1998), 291–301. https://doi.org/10.1137/S0097539794285983
  • A. Gupta, I. Newman, Y. Rabinovich, A. Sinclair, Cuts, trees and ℓ1\ell_1ℓ1​-embeddings of graphs, Combinatorica 24 (2004), 233–269. https://doi.org/10.1007/s00493-004-0015-x
  • A. Chakrabarti, A. Jaffe, J. R. Lee, J. Vincent, Embeddings of topological graphs: lossy invariants, linearization, and 2-sums, FOCS 2008, 761–770. https://doi.org/10.1109/FOCS.2008.79
  • J. R. Lee, P. Raghavendra, Coarse differentiation and multi-flows in planar graphs, Discrete Comput. Geom. 43 (2010), 346–362. https://doi.org/10.1007/s00454-009-9172-4
  • E. Chlamtáč, R. Krauthgamer, P. Raghavendra, Approximating sparsest cut in graphs of bounded treewidth, APPROX/RANDOM 2010, LNCS 6302, 124–137. https://doi.org/10.1007/978-3-642-15369-3_10
  • J. R. Lee, A. Sidiropoulos, Pathwidth, trees, and random embeddings, Combinatorica 33 (2013), 349–374. https://doi.org/10.1007/s00493-013-2685-8
  • I. Abraham, A. Filtser, A. Gupta, O. Neiman, Metric embedding via shortest path decompositions, SIAM J. Comput. 51 (2022), 290–314. https://doi.org/10.1137/19M1296021
  • A. Filtser, T. Friedrich, D. Issac, N. Kumar, H. Le, N. Mallek, Z. Zeif, Optimal padded decomposition for bounded treewidth graphs, TheoretiCS 4 (2025), Article 22. https://doi.org/10.46298/theoretics.25.22
  • OpenAI, L1L_1L1​ Embeddings of Graphs of Bounded Treewidth, OpenAI Math Release preprint, September 23, 2026 (source of the goal; Theorem 1.1, p. 2). https://github.com/openai/math/blob/adc7f1241b42e322a6451854ab7e4b4c146bf78a/preprints/L1-Embeddings-of-Graphs-of-Bounded-Treewidth-September-23-2026/paper.pdf
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Discrete GeometryGraph TheoryTheoretical Computer Science·Captain: wurtle

Planar Graph Metrics Embed into L1 with Constant DistortionResearch Paper

Motivation: cut metrics, flows and the planar embedding conjecture

A finite metric space embeds into L1L_1L1​ exactly when its metric is a nonnegative combination of cut metrics δS(x,y)=∣1S(x)−1S(y)∣\delta_S(x,y)=|\mathbf 1_S(x)-\mathbf 1_S(y)|δS​(x,y)=∣1S​(x)−1S​(y)∣. For this reason the least distortion with which a graph metric embeds into L1L_1L1​ governs the gap between multicommodity flow and sparsest cut: Linial, London and Rabinovich (1995) and Aumann and Rabani (1998) connected metric embeddings to the approximate max-flow/min-cut theorem, and Gupta, Newman, Rabinovich and Sinclair (2004) proved that the worst flow–cut gap on a fixed graph equals the worst L1L_1L1​ distortion of its weighted shortest-path metrics. They conjectured (the GNRS conjecture) that every proper minor-closed graph family embeds into L1L_1L1​ with uniformly bounded distortion. The planar case has been the central open instance.

Timeline

  • 1981 — Okamura and Seymour: multicommodity flows in planar graphs with all terminals on one face (JCTB 1981), giving isometric L1L_1L1​ representations of one-face metrics.
  • 1993 — Klein, Plotkin and Rao: decompositions of graphs excluding a fixed minor (STOC 1993).
  • 1999 — Rao: every nnn-vertex planar metric embeds into L1L_1L1​ (via Euclidean space) with distortion O(log⁡n)O(\sqrt{\log n})O(logn​) (SoCG 1999).
  • 2003 — Newman and Rabinovich: series-parallel metrics may need Ω(log⁡n)\Omega(\sqrt{\log n})Ω(logn​) distortion into Euclidean space, so the Euclidean route cannot give a constant (DCG 2003).
  • 2004 — Gupta, Newman, Rabinovich and Sinclair: constant distortion for series-parallel graphs, and the GNRS conjecture (Combinatorica 2004).
  • 2006 — Chekuri, Gupta, Newman, Rabinovich and Sinclair: kkk-outerplanar graphs, with a bound exponential in kkk (SIDMA 2006).
  • 2008–2010 — Chakrabarti, Jaffe, Lee and Vincent: sharp bound 222 for series-parallel graphs (FOCS 2008); Lee and Raghavendra: matching lower bound (DCG 2010). Lee and Sidiropoulos relate the planar case to the full conjecture (STOC 2009).
  • 2013 — Sidiropoulos: constant distortion for planar metrics realized in nonpositively curved simply connected surfaces (FOCS 2013).
  • 2019–2025 — Face-cover bounds by Krauthgamer, Lee and Rika (SODA 2019) and Filtser (TALG 2025); Abraham, Filtser, Gupta and Neiman recover Rao's bound via shortest-path decompositions (SICOMP 2022).
  • 2026 — An OpenAI preprint, Planar Graph Metrics Embed into L1L_1L1​ with Constant Distortion (OpenAI Math Release, September 23, 2026), claims the planar case of the GNRS conjecture. The preprint has not been peer reviewed, and its main theorem is not formally verified.

Setting

Let GGG be a finite connected simple graph on vertex set V={0,…,n−1}V=\{0,\dots,n-1\}V={0,…,n−1} with symmetric edge lengths ℓ(u,v)=ℓ(v,u)>0\ell(u,v)=\ell(v,u)>0ℓ(u,v)=ℓ(v,u)>0 on edges. The graph metric dG(x,y)d_G(x,y)dG​(x,y) is the infimum of ∑ℓ(e)\sum\ell(e)∑ℓ(e) over walks from xxx to yyy. GGG is planar if it has a drawing in R2\mathbb R^2R2: distinct points for vertices and, for each edge, an injective arc between its endpoints whose interior avoids every vertex and meets the interior of no other edge.

A map f:V→L1(Ω,μ)f:V\to L_1(\Omega,\mu)f:V→L1​(Ω,μ) into the real L1L_1L1​ space of some measure space has distortion at most CCC if dG(x,y)≤∥f(x)−f(y)∥1≤C dG(x,y)d_G(x,y)\le\|f(x)-f(y)\|_1\le C\,d_G(x,y)dG​(x,y)≤∥f(x)−f(y)∥1​≤CdG​(x,y) for all x,yx,yx,y.

Formalization targets

Goal: Theorem 1.1 (planar graph metrics in L1L_1L1​)

There is a constant C≥1C\ge1C≥1 such that for every nnn, every connected planar graph GGG on nnn vertices and every symmetric positive edge-length function ℓ\ellℓ, there are a measure space (Ω,F,μ)(\Omega,\mathcal F,\mu)(Ω,F,μ) and f:V→L1(Ω,F,μ;R)f:V\to L_1(\Omega,\mathcal F,\mu;\mathbb R)f:V→L1​(Ω,F,μ;R) with

dG(x,y)  ≤  ∥f(x)−f(y)∥1  ≤  C dG(x,y)(x,y∈V).d_G(x,y)\;\le\;\|f(x)-f(y)\|_1\;\le\;C\,d_G(x,y)\qquad(x,y\in V).dG​(x,y)≤∥f(x)−f(y)∥1​≤CdG​(x,y)(x,y∈V).

The constant is not fixed: the goal asserts only existence, so any improvement of the constant is compatible with it. The goal statement is published on the platform with status Open: no machine-checked proof exists yet.

Significance

The result itself. The theorem settles the planar case of the GNRS conjecture. By the Gupta–Newman–Rabinovich–Sinclair equivalence it gives a universal constant bound on the fractional flow–cut gap for arbitrary demands in planar graphs. With the bounded-treewidth companion preprint it also yields constant distortion for the fixed-parameter almost-embeddable families of Lee and Sidiropoulos (Corollary 10.1 of the source). The general clique-sum closure needed for the full GNRS conjecture is not established.

Formalizing it. The statement is elementary (finite graphs, arcs in the plane, an L1L^1L1 space), yet the proof combines a geometric column model of planar graphs, random multiscale cut constructions and packing estimates. A formal proof would certify every scale-combination step, where errors in uniformity are easy to make.

Difficulty

Standard random-partition methods for planar graphs separate pairs at each distance scale with good probability, but naive summation over scales costs a factor proportional to the number of scales, which is unbounded when edge lengths vary. Embedding first into Euclidean space cannot work: Newman–Rabinovich show Ω(log⁡n)\Omega(\sqrt{\log n})Ω(logn​) Euclidean distortion is necessary already for series-parallel graphs. The difficulty is to combine separations at different scales while keeping a single uniform upper bound on every edge.

Formalization scope

  • Vertices are Fin n; the graph is a SimpleGraph (Fin n) with G.Connected (so n≥1n\ge1n≥1). Singletons are allowed.
  • IsPlanar G asks for an injective vertex placement in ℝ × ℝ and, for each ordered adjacent pair, an injective continuous arc on the unit interval with the right endpoints, whose interior avoids all vertex points and meets the interior of another arc only if it is the same unoriented edge.
  • Edge lengths are a function Fin n → Fin n → ℝ, symmetric, and positive on adjacent pairs; values on non-adjacent pairs are irrelevant. graphDistance is the sInf of walk lengths; for a connected graph with nonnegative edge lengths the set of walk lengths is nonempty and bounded below, so the infimum is the genuine shortest-path distance.
  • The target space is MeasureTheory.Lp Ω ℝ 1 μ for an existentially chosen measure space, and the inequalities are stated without a rescaling factor (the rescaling is absorbed into fff).
  • Infrastructure needed: plane drawings and their combinatorial consequences (rotation systems, noncrossing column models), cut-metric representations of L1L_1L1​ metrics, and the probabilistic multiscale construction. Plane-drawing and cut-metric infrastructure is reusable.

Selected references

  • N. Linial, E. London, Y. Rabinovich, The geometry of graphs and some of its algorithmic applications, Combinatorica 15 (1995). https://doi.org/10.1007/BF01200757
  • Y. Aumann, Y. Rabani, An O(log⁡k)O(\log k)O(logk) approximate min-cut max-flow theorem and approximation algorithm, SIAM J. Comput. (1998). https://doi.org/10.1137/S0097539794285983
  • A. Gupta, I. Newman, Y. Rabinovich, A. Sinclair, Cuts, trees and ℓ1\ell_1ℓ1​-embeddings of graphs, Combinatorica (2004). https://doi.org/10.1007/s00493-004-0015-x
  • S. Rao, Small distortion and volume preserving embeddings for planar and Euclidean metrics, SoCG 1999. https://doi.org/10.1145/304893.304983
  • I. Newman, Y. Rabinovich, A lower bound on the distortion of embedding planar metrics into Euclidean space, Discrete Comput. Geom. (2003). https://doi.org/10.1007/s00454-002-2813-5
  • C. Chekuri, A. Gupta, I. Newman, Y. Rabinovich, A. Sinclair, Embedding kkk-outerplanar graphs into ℓ1\ell_1ℓ1​, SIAM J. Discrete Math. (2006). https://doi.org/10.1137/S0895480102417379
  • A. Chakrabarti, A. Jaffe, J. R. Lee, J. Vincent, Embeddings of topological graphs: lossy invariants, linearization, and 2-sums, FOCS 2008. https://doi.org/10.1109/FOCS.2008.79
  • J. R. Lee, A. Sidiropoulos, On the geometry of graphs with a forbidden minor, STOC 2009. https://doi.org/10.1145/1536414.1536450
  • A. Sidiropoulos, Non-positive curvature and the planar embedding conjecture, FOCS 2013. https://doi.org/10.1109/FOCS.2013.27
  • I. Abraham, A. Filtser, A. Gupta, O. Neiman, Metric embedding via shortest path decompositions, SIAM J. Comput. (2022). https://doi.org/10.1137/19M1296021
  • A. Filtser, A face cover perspective to ℓ1\ell_1ℓ1​ embeddings of planar graphs, ACM Trans. Algorithms (2025). https://doi.org/10.1145/3686800
  • OpenAI, Planar Graph Metrics Embed into L1L_1L1​ with Constant Distortion, OpenAI Math Release preprint, September 23, 2026 (source of the goal; Theorem 1.1, p. 2). https://github.com/openai/math/blob/adc7f1241b42e322a6451854ab7e4b4c146bf78a/preprints/Planar-Graph-Metrics-Embed-into-L1-with-Constant-Distortion-September-23-2026/paper.pdf
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Discrete Geometry·Captain: wurtle

A product counterexample to the simplex maximum for projection-body volumeResearch Paper

Motivation

The projection body ΠK\Pi KΠK of a convex body K⊂RdK\subset\mathbb R^dK⊂Rd is the convex body whose support function in a unit direction uuu is the (d−1)(d-1)(d−1)-dimensional volume of the shadow of KKK on u⊥u^\perpu⊥. Petty showed that K↦ΠKK\mapsto\Pi KK↦ΠK is affinely covariant, so the normalized volume

Rd(K)=∣ΠK∣∣K∣d−1R_d(K)=\frac{|\Pi K|}{|K|^{d-1}}Rd​(K)=∣K∣d−1∣ΠK∣​

is invariant under invertible affine maps, and its extremal values are natural affine isoperimetric questions. Petty's conjecture concerns the minimum (ellipsoids). For the maximum, Brannen conjectured in 1996 that simplices maximize RdR_dRd​ among all convex bodies (Mathematika 1996); the simplex value is cd=(d+1)dd/d!c_d=(d+1)d^d/d!cd​=(d+1)dd/d!.

This mission asks for a formal proof of an explicit counterexample in dimension 202020, as stated in an OpenAI preprint dated September 24, 2026 (source). The preprint has not been peer reviewed and its claims have not been independently verified; on the platform the Lean goal is open.

Background

  • 1967 — Petty, Projection bodies, establishes the affine covariance of the projection-body operator (Proc. Colloq. Convexity, Copenhagen 1965).
  • 1996 — Brannen conjectures that simplices maximize RdR_dRd​ (Mathematika 1996).
  • 2002 — Ludwig characterizes the projection-body operator by valuations (Adv. Math. 2002).
  • 2025 — Henk gives the lower bound 2d(9/8)⌊d/3⌋2^d(9/8)^{\lfloor d/3\rfloor}2d(9/8)⌊d/3⌋ for the optimal upper constant among centrally symmetric bodies (Acta Math. Sci. 2025).
  • 2026 — Chen, Feng, Li, Xi and Xu prove R3(K)≤18=c3R_3(K)\le18=c_3R3​(K)≤18=c3​, with tetrahedra as maximizers (preprint); Feng, Hu, Liu and Xu give counterexamples to Brannen's bound in every dimension d≥9d\ge9d≥9 using polytopes with at most d+2d+2d+2 facets (preprint).
  • September 2026 — The OpenAI preprint gives a direct product counterexample with exact value in dimension 202020 (Theorem 1, p. 2).

Setting

A convex body in Rd\mathbb R^dRd is compact and convex with nonempty interior, and ∣⋅∣|\cdot|∣⋅∣ is ddd-dimensional volume. For u∈Rdu\in\mathbb R^du∈Rd the brightness is hΠK(u)=∥u∥vol⁡d−1(proj⁡u⊥K)h_{\Pi K}(u)=\|u\|\operatorname{vol}_{d-1}(\operatorname{proj}_{u^\perp}K)hΠK​(u)=∥u∥vold−1​(proju⊥​K), and

ΠK={y: ⟨u,y⟩≤hΠK(u) for all u}.\Pi K=\{y:\ \langle u,y\rangle\le h_{\Pi K}(u)\ \text{for all }u\}.ΠK={y: ⟨u,y⟩≤hΠK​(u) for all u}.

Let T10=conv⁡(0,e1,…,e10)⊂R10T_{10}=\operatorname{conv}(0,e_1,\dots,e_{10})\subset\mathbb R^{10}T10​=conv(0,e1​,…,e10​)⊂R10 be the standard simplex and

K=T10×T10={x∈R20: (x1,…,x10)∈T10, (x11,…,x20)∈T10}.K=T_{10}\times T_{10}=\{x\in\mathbb R^{20}:\ (x_1,\dots,x_{10})\in T_{10},\ (x_{11},\dots,x_{20})\in T_{10}\}.K=T10​×T10​={x∈R20: (x1​,…,x10​)∈T10​, (x11​,…,x20​)∈T10​}.

The benchmark constant is cd=(d+1)dd/d!c_d=(d+1)d^d/d!cd​=(d+1)dd/d!, which equals RdR_dRd​ of every ddd-simplex (Proposition 5, p. 4).

Formalization targets

Milestone: failure of the simplex bound in dimension 20 (Theorem 1, p. 2, last sentence, with Proposition 5)

It is not true that R20(P)≤R20(T20)R_{20}(P)\le R_{20}(T_{20})R20​(P)≤R20​(T20​) for every convex body P⊂R20P\subset\mathbb R^{20}P⊂R20.

Goal: Theorem 1 (p. 2)

K=T10×T10K=T_{10}\times T_{10}K=T10​×T10​ is a convex body and

R20(K)c20=121(2010)21⋅220=22 355 47622 020 096>1,so∣ΠK∣>c20∣K∣19.\frac{R_{20}(K)}{c_{20}}=\frac{121\binom{20}{10}}{21\cdot 2^{20}}=\frac{22\,355\,476}{22\,020\,096}>1,\qquad\text{so}\qquad |\Pi K|>c_{20}|K|^{19}.c20​R20​(K)​=21⋅220121(1020​)​=2202009622355476​>1,so∣ΠK∣>c20​∣K∣19.

Significance

The result itself. Brannen's conjecture fails: in dimension 202020 the simplex is not the maximizer of normalized projection-body volume. The mechanism is the product identity Rr+s(A×B)=Rr(A)Rs(B)R_{r+s}(A\times B)=R_r(A)R_s(B)Rr+s​(A×B)=Rr​(A)Rs​(B) for polytopes (Proposition 3, p. 3), which shows that crcsc_rc_scr​cs​ is a lower bound for any universal upper constant in dimension r+sr+sr+s; iterating it gives an exponential excess Rn(Kn)≥λnRn(Tn)R_n(K_n)\ge\lambda^nR_n(T_n)Rn​(Kn​)≥λnRn​(Tn​) for all large nnn (Corollary 6, p. 6). The counterexample in dimensions d≥9d\ge9d≥9 was obtained independently by Feng, Hu, Liu and Xu; the contribution here is an explicit product witness with an exact rational value. The optimal upper constant and its maximizers remain separate questions.

Formalizing it. Every ingredient is elementary: the facet formula for projection bodies of polytopes (Cauchy's formula, Lemma 2, p. 2), the facet structure of a Cartesian product, affine covariance (Lemma 4, p. 3), and a fiber computation of ∣ΠTd∣|\Pi T_d|∣ΠTd​∣. A formal proof would supply Mathlib with projection bodies of polytopes and Cauchy's projection formula, both reusable. The final comparison is an exact rational identity.

Difficulty

There is no shortcut through general inequalities: the statement is a strict comparison of two explicit volumes in dimension 202020, so both ∣ΠK∣|\Pi K|∣ΠK∣ and ∣ΠT20∣|\Pi T_{20}|∣ΠT20​∣ must be computed exactly. Computing Π\PiΠ of a product directly from shadow volumes is unwieldy; the efficient route goes through facet area-normal vectors, which requires proving that, up to a null set, each point of a shadow lies over exactly two facet interiors, and that the facets of A×BA\times BA×B are exactly F×BF\times BF×B and A×GA\times GA×G. The simplex value needs the volume of a cube plus a segment.

Formalization scope

  • Space is EuclideanSpace ℝ (Fin 20). In the goal, projectionVolume is the induced Lebesgue measure on the submodule (span⁡{u})⊥(\operatorname{span}\{u\})^\perp(span{u})⊥ of the orthogonal projection of KKK; brightness u = ‖u‖ * projectionVolume, so the support-function inequality is imposed for all uuu (the homogeneous extension).
  • productWitness is the set of xxx whose first and last ten coordinates both lie in standardSimplex 10; the goal includes that it is compact, convex, with nonempty interior.
  • simplexConstant 20 is the explicit number c20c_{20}c20​, not R20(T20)R_{20}(T_{20})R20​(T20​); the goal states the exact ratio, its reduced fraction, the strict inequality, and ∣ΠK∣>c20∣K∣19|\Pi K|>c_{20}|K|^{19}∣ΠK∣>c20​∣K∣19.
  • The milestone uses a separate definition file: shadow volumes via euclideanHausdorffMeasure (d-1) of the image under the orthogonal projection, and compares with ratio (simplex 20), so it implicitly needs Proposition 5.
  • Volumes are read with toReal; all bodies involved are bounded, so no infinite value is hidden.

Selected references

  • OpenAI, A product counterexample to the simplex maximum for projection-body volume, OpenAI Math Release preprint, September 24, 2026. https://github.com/openai/math/blob/adc7f1241b42e322a6451854ab7e4b4c146bf78a/preprints/A-product-counterexample-to-the-simplex-maximum-for-projection-body-volume-September-24-2026/paper.pdf
  • N. S. Brannen, Volumes of projection bodies, Mathematika 43 (1996), 255–264. https://doi.org/10.1112/S002557930001175X
  • C. M. Petty, Projection bodies, Proc. Colloq. Convexity (Copenhagen, 1965), 1967, 234–241.
  • M. Ludwig, Projection bodies and valuations, Adv. Math. 172 (2002), 158–168. https://doi.org/10.1016/S0001-8708(02)00021-X
  • M. Henk, Note on projection bodies of zonotopes with n+1 generators, Acta Math. Sci. 45 (2025), 96–103. https://doi.org/10.1007/s10473-025-0107-9
  • S. Chen, Y. Feng, Y. Li, D. Xi, L. Xu, Petty's conjectured projection inequality in dimension three, preprint (2026). https://archive.ymsc.tsinghua.edu.cn/pacm_download/741/12780-pettyinequality.pdf
  • Y. Feng, S. Hu, W. Liu, L. Xu, On the reverse projection inequality, preprint (2026). https://archive.ymsc.tsinghua.edu.cn/pacm_download/743/12781--2026.8.26.pdf
  • C. Saroglou, On the shape of a convex body with respect to its second projection body, Adv. Appl. Math. 67 (2015), 55–74. https://doi.org/10.1016/j.aam.2015.03.004
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AnalysisDiscrete Geometry·Captain: wurtle

Petty’s projection-volume conjecture in dimensions at least fourResearch Paper

Motivation

The projection body ΠK\Pi KΠK of a convex body K⊂RnK\subset\mathbb R^nK⊂Rn packages the areas of all shadows of KKK into a single convex body: its support function in direction uuu is the (n−1)(n-1)(n−1)-dimensional volume of the orthogonal projection of KKK onto u⊥u^\perpu⊥. The normalized volume ∣ΠK∣/∣K∣n−1|\Pi K|/|K|^{n-1}∣ΠK∣/∣K∣n−1 is invariant under translations and invertible linear maps, so asking for its extremizers is an affine isoperimetric problem. Petty's projection-volume conjecture (Petty, 1971) predicts that this ratio is minimized exactly by ellipsoids. It is related to, but distinct from, Petty's projection inequality for the polar body Π∘K\Pi^\circ KΠ∘K, which is a classical theorem; inequalities in this family underlie affine Sobolev inequalities and isoperimetric inequalities in normed spaces.

This mission asks for a formal proof of the conjecture in every dimension n≥4n\ge4n≥4, as stated in an OpenAI preprint dated September 24, 2026 (source). The preprint has not been peer reviewed and its claims have not been independently verified; on the platform the Lean goal is open.

Background

  • 1971 — Petty formulates the conjecture (Isoperimetric problems, Proc. Conf. Convexity and Combinatorial Geometry, Univ. of Oklahoma, 1971).
  • 1990 — Lutwak reformulates it as a lower bound for a two-body integral with kernel ∣u⋅v∣|u\cdot v|∣u⋅v∣ against surface-area measures (Contemp. Math. 113, 1990) and derives lower-degree consequences (Geom. Dedicata 1990).
  • 2015–2018 — Saroglou's class-reduction results for the second projection body (Adv. Appl. Math. 2015); Saroglou–Zvavitch local minimality near the ball in L∞L^\inftyL∞ (JFA 2017); Ivaki's local rigidity for C2C^2C2 solutions of Π2K=cK\Pi^2K=cKΠ2K=cK (Mathematika 2018).
  • 2026 — Mielke-Sulz proves the conjecture for bodies of revolution (arXiv:2609.13517); Chen, Feng, Li, Xi and Xu prove the unrestricted three-dimensional case with ellipsoid equality (preprint, August 2026).
  • September 2026 — The OpenAI preprint claims all dimensions n≥4n\ge4n≥4 (Theorem 1.1, p. 1).

Setting

A convex body K⊂RnK\subset\mathbb R^nK⊂Rn is a compact convex set with nonempty interior, and ∣⋅∣|\cdot|∣⋅∣ denotes nnn-dimensional Lebesgue volume. For a unit vector uuu, let proj⁡u⊥K\operatorname{proj}_{u^\perp}Kproju⊥​K be the orthogonal projection of KKK onto the hyperplane u⊥u^\perpu⊥ and vol⁡n−1\operatorname{vol}_{n-1}voln−1​ the Lebesgue measure on that hyperplane. The projection body is

ΠK={x∈Rn: ⟨u,x⟩≤vol⁡n−1(proj⁡u⊥K) for every unit u},\Pi K=\{x\in\mathbb R^n:\ \langle u,x\rangle\le \operatorname{vol}_{n-1}(\operatorname{proj}_{u^\perp}K)\ \text{for every unit }u\},ΠK={x∈Rn: ⟨u,x⟩≤voln−1​(proju⊥​K) for every unit u},

the convex body with support function hΠK(u)=vol⁡n−1(proj⁡u⊥K)h_{\Pi K}(u)=\operatorname{vol}_{n-1}(\operatorname{proj}_{u^\perp}K)hΠK​(u)=voln−1​(proju⊥​K). Write κm\kappa_mκm​ for the volume of the Euclidean unit ball B2mB_2^mB2m​. An ellipsoid is a set a+TB2na+TB_2^na+TB2n​ with a∈Rna\in\mathbb R^na∈Rn and TTT an invertible linear map. Since ΠB2n=κn−1B2n\Pi B_2^n=\kappa_{n-1}B_2^nΠB2n​=κn−1​B2n​, the ball has ratio κn−1nκn2−n\kappa_{n-1}^n\kappa_n^{2-n}κn−1n​κn2−n​.

Formalization targets

Goal: Theorem 1.1 (p. 1)

For every integer n≥4n\ge4n≥4 and every convex body K⊂RnK\subset\mathbb R^nK⊂Rn,

∣ΠK∣∣K∣n−1 ≥ κn−1 n κn 2−n,\frac{|\Pi K|}{|K|^{n-1}}\ \ge\ \kappa_{n-1}^{\,n}\,\kappa_n^{\,2-n},∣K∣n−1∣ΠK∣​ ≥ κn−1n​κn2−n​,

with equality if and only if KKK is an ellipsoid.

Significance

The result itself. Together with the separately proved three-dimensional case, it settles Petty's conjecture for all n≥3n\ge3n≥3 (in dimension 222 the ratio is constant up to the standard identification). The preprint derives from it the Lutwak–Petty lower-degree inequalities, a mixed determinant-gradient inequality strengthening the Sobolev–Zhang affine L1L^1L1 inequality, and the sharp Holmes–Thompson isoperimetric inequality in normed spaces (Corollaries 7.1–7.3, pp. 27–29). Those corollaries for n=3n=3n=3 rely on the external three-dimensional theorem.

Formalizing it. The proof uses the first variation of volume, spherical harmonics with explicit cosine and Funk transform multipliers, a strict harmonic estimate for arbitrary norms, a variational representation of support functionals, and Brouwer's fixed-point theorem. Mathlib has Brouwer-type results only in limited forms and has no spherical-harmonic decomposition of L2(Sn−1)L^2(S^{n-1})L2(Sn−1); these would be reusable. No machine-checked proof of any case n≥2n\ge2n≥2 of the conjecture is known.

Difficulty

Previous results are local: they require the body, after a linear change of variables, to be close to the ball, because the harmonic analysis of the projection operator only controls perturbations of the ball. A global argument must handle arbitrary bodies without symmetry or regularity. In the preprint (pp. 2–3) the degree-two spherical harmonic component is not a zero mode of the relevant sign-test operator and has to be removed by choosing affine coordinates; this needs a continuous family of variational minimizers extended to singular matrices and a fixed-point argument (Proposition 5.5, p. 23). Harmonics of degree at least four are controlled by a strict norm estimate valid for every norm (Theorem 4.1, p. 12). The equality case must come out of the same estimates.

Formalization scope

  • Space n is EuclideanSpace ℝ (Fin n); IsConvexBody K is compact, convex, nonempty interior; n≥4n\ge4n≥4.
  • shadowVolume K u is the measure, in the induced Euclidean volume on the submodule (span⁡{u})⊥(\operatorname{span}\{u\})^\perp(span{u})⊥, of the image of KKK under orthogonalProjectionOnto. projectionBody K is the intersection of half-spaces over unit vectors, which has support function shadowVolume K because that function is itself a support function.
  • projectionRatio K = volume.real (projectionBody K) / volume.real K ^ (n - 1); for a convex body both volumes are finite and the denominator is positive.
  • pettyConstant n = kappa (n-1) ^ n * kappa n ^ (2 - n) with an integer exponent, κm\kappa_mκm​ the volume of the closed unit ball.
  • IsEllipsoid K: K=a+T(closed unit ball)K = a + T(\text{closed unit ball})K=a+T(closed unit ball) for a linear equivalence TTT.
  • The goal is the conjunction of the inequality and the iff equality characterization; neither part is vacuous for n≥4n\ge4n≥4.

Selected references

  • OpenAI, Petty's projection-volume conjecture in dimensions at least four, OpenAI Math Release preprint, September 24, 2026. https://github.com/openai/math/blob/adc7f1241b42e322a6451854ab7e4b4c146bf78a/preprints/Pettys-projection-volume-conjecture-in-dimensions-at-least-four-September-24-2026/paper.pdf
  • C. M. Petty, Isoperimetric problems, Proc. Conf. Convexity and Combinatorial Geometry, Univ. of Oklahoma, 1971, 26–41.
  • E. Lutwak, On a conjectured projection inequality of Petty, Contemp. Math. 113 (1990), 171–182.
  • E. Lutwak, On quermassintegrals of mixed projection bodies, Geom. Dedicata 33 (1990), 51–58. https://doi.org/10.1007/BF00147600
  • C. Saroglou, A. Zvavitch, Iterations of the projection body operator and a remark on Petty's conjectured projection inequality, J. Funct. Anal. 272 (2017), 613–630. https://doi.org/10.1016/j.jfa.2016.08.015
  • M. N. Ivaki, A local uniqueness theorem for minimizers of Petty's conjectured projection inequality, Mathematika 64 (2018), 1–19. https://doi.org/10.1112/S0025579317000444
  • S. Chen, Y. Feng, Y. Li, D. Xi, L. Xu, Petty's conjectured projection inequality in dimension three, preprint (2026). https://archive.ymsc.tsinghua.edu.cn/pacm_download/741/12780-pettyinequality.pdf
  • F. Mielke-Sulz, The Petty conjecture for convex bodies of revolution, arXiv:2609.13517 (2026). https://arxiv.org/abs/2609.13517v1
  • G. Zhang, The affine Sobolev inequality, J. Differential Geom. 53 (1999), 183–202.
  • R. J. Gardner, The Brunn–Minkowski inequality, Bull. AMS 39 (2002), 355–405. https://doi.org/10.1090/S0273-0979-02-00941-2
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Discrete GeometrySymplectic Geometry·Captain: wurtle

Symplectic Balls in Symmetric Polar ProductsResearch Paper

Motivation

Place a convex body K⊂RnK\subset\mathbb R^nK⊂Rn in the position coordinates and its polar K∘K^\circK∘ in the momentum coordinates of the standard symplectic space (Rqn×Rpn,ω0)(\mathbb R^n_q\times\mathbb R^n_p,\omega_0)(Rqn​×Rpn​,ω0​). The resulting Lagrangian product K×K∘K\times K^\circK×K∘ links two problems. Its volume is the Mahler volume product ∣K∣∣K∘∣|K||K^\circ|∣K∣∣K∘∣, and its symplectic capacities measure how large a round ball can be squeezed into it by a symplectic map. Since symplectic maps preserve volume, a ball of capacity ccc inside int⁡K×int⁡K∘\operatorname{int}K\times\operatorname{int}K^\circintK×intK∘ forces ∣K∣∣K∘∣≥cn/n!|K||K^\circ|\ge c^n/n!∣K∣∣K∘∣≥cn/n!. Artstein-Avidan, Karasev and Ostrover showed that the Hofer–Zehnder capacity of K×K∘K\times K^\circK×K∘ equals 444 for every origin-symmetric KKK and connected Viterbo's volume–capacity conjecture to Mahler's conjecture (Duke 2014). Whether actual balls of capacity close to 444 fit, i.e. whether the Gromov width also equals 444, was open.

This mission asks for a formal proof that it does, as claimed in an OpenAI preprint dated September 22, 2026 (source). The preprint has not been peer reviewed and its claims have not been independently verified; on the platform the Lean goal is open.

Timeline

  • 1939 — Mahler formulates the symmetric volume-product problem (Časopis 1939).
  • 1985 — Gromov's nonsqueezing theorem shows that ball embeddings detect symplectic rigidity beyond volume (Invent. Math. 1985).
  • 1987 — Bourgain–Milman reverse Santaló inequality (Invent. Math. 1987); Reisner's sharp inequality for unconditional bodies (J. LMS 1987).
  • 1994 — Hofer and Zehnder introduce their capacity (book, 1994).
  • 2000 — Viterbo proposes the volume–capacity inequality for convex domains (JAMS 2000).
  • 2013 — Latschev, McDuff and Schlenk compute Gromov widths of four-dimensional tori with area-preserving constructions (G&T 2013).
  • 2014 — Artstein-Avidan, Karasev and Ostrover prove cHZ(K×K∘)=4c_{HZ}(K\times K^\circ)=4cHZ​(K×K∘)=4 for symmetric KKK (Duke 2014).
  • 2019–2021 — Ramos and Sepe identify the cube–cross-polytope product with a ball of capacity 444 (J. Symplectic Geom. 2019); Karasev treats ℓp\ell_pℓp​ balls (Israel J. Math. 2021).
  • 2020 — Iriyeh and Shibata prove the three-dimensional symmetric Mahler conjecture (Duke 2020).
  • 2024–2026 — Haim-Kislev and Ostrover disprove the general Viterbo conjecture with a non-symmetric four-dimensional example (Annals 2026); Vicente studies functional-dual products and records the width question (arXiv:2505.07572).
  • September 2026 — The OpenAI preprint claims Gromov width 444 for every symmetric polar product, n≥2n\ge2n≥2 (Theorem 1.1, p. 1).

Setting

An origin-symmetric convex body K⊂RnK\subset\mathbb R^nK⊂Rn is compact, convex, has nonempty interior, and satisfies x∈K  ⟺  −x∈Kx\in K\iff -x\in Kx∈K⟺−x∈K. Its polar is K∘={p:⟨q,p⟩≤1 ∀q∈K}K^\circ=\{p:\langle q,p\rangle\le1\ \forall q\in K\}K∘={p:⟨q,p⟩≤1 ∀q∈K}. On Rn×Rn\mathbb R^n\times\mathbb R^nRn×Rn put ω0((q,p),(q′,p′))=⟨q,p′⟩−⟨q′,p⟩\omega_0((q,p),(q',p'))=\langle q,p'\rangle-\langle q',p\rangleω0​((q,p),(q′,p′))=⟨q,p′⟩−⟨q′,p⟩, and let

UK=int⁡K×int⁡K∘,B2n(c)={(q,p):π(∣q∣2+∣p∣2)<c}.U_K=\operatorname{int}K\times\operatorname{int}K^\circ,\qquad B^{2n}(c)=\{(q,p):\pi(|q|^2+|p|^2)<c\}.UK​=intK×intK∘,B2n(c)={(q,p):π(∣q∣2+∣p∣2)<c}.

A symplectic embedding of an open set UUU into VVV is a C∞C^\inftyC∞ map on UUU that is a topological embedding, maps UUU into VVV, and whose derivative preserves ω0\omega_0ω0​ at every point. The Gromov width cG(V)c_G(V)cG​(V) is the supremum of capacities c>0c>0c>0 for which B2n(c)B^{2n}(c)B2n(c) embeds symplectically into VVV.

Formalization targets

Milestone: the symmetric Mahler inequality (Corollary 5.3, p. 16)

For every n≥1n\ge1n≥1 and origin-symmetric convex body K⊂RnK\subset\mathbb R^nK⊂Rn,  ∣K∣ ∣K∘∣≥4n/n!\ |K|\,|K^\circ|\ge 4^n/n! ∣K∣∣K∘∣≥4n/n!.

Goal: Theorem 1.1 (p. 1)

For every n≥2n\ge2n≥2 and every origin-symmetric convex body K⊂RnK\subset\mathbb R^nK⊂Rn,

cG(UK)=4,c_G(U_K)=4,cG​(UK​)=4,

and for every 0<c<40<c<40<c<4 there is a symplectic embedding B2n(c)↪UKB^{2n}(c)\hookrightarrow U_KB2n(c)↪UK​. No embedding at capacity exactly 444 is asserted.

Significance

The result itself. It answers the symmetric-polar-product width question with no smoothness, strict convexity or unconditionality assumptions, and through volume preservation it implies the symmetric Mahler inequality in every dimension (Corollary 5.3). For n≥3n\ge3n≥3 it also transports finite ball packings satisfying strict volume and pairwise-capacity conditions into UKU_KUK​ (Corollary 5.5, p. 17). It is specific to symmetric polar products: the general Viterbo conjecture is false.

Formalizing it. Mathlib has smooth manifolds and differential forms but no symplectic capacities, nonsqueezing, or Moser's deformation method. A formal proof would need these, together with a conformal map of the disk with explicit boundary estimates. These components are reusable across symplectic geometry. No machine-checked computation of a Gromov width of a non-trivial domain is known.

Difficulty

The upper bound cG≤4c_G\le4cG​≤4 follows from Gromov nonsqueezing and a supporting-cylinder argument (or from the Hofer–Zehnder computation). The lower bound is the hard direction: knowing cHZ=4c_{HZ}=4cHZ​=4 does not produce any ball, and explicit embeddings were previously known only for special families (ℓp\ell_pℓp​ balls, the cube). The preprint's route (Sections 2–4) needs balls of capacity close to πk\pi kπk from holomorphic maps vanishing to order kkk, and a momentum scale Sk=(1+o(1))πk/4S_k=(1+o(1))\pi k/4Sk​=(1+o(1))πk/4 that is uniform up to the tips of a conformal lens, where slice heights approach ±1\pm1±1 as kkk grows; a non-uniform estimate does not suffice.

Formalization scope

  • Position and momentum spaces are EuclideanSpace ℝ (Fin n); phase space is their product. polar uses the real inner product; polarProduct K is interior K ×ˢ interior (polar K).
  • capacityBall n c is the open ball π(∣q∣2+∣p∣2)<c\pi(|q|^2+|p|^2)<cπ(∣q∣2+∣p∣2)<c, so a ball of radius rrr has capacity πr2\pi r^2πr2.
  • HasSymplecticEmbedding U V: some e with ContDiffOn ℝ ∞ e U, IsEmbedding on the subtype U, MapsTo e U V, and ω0(De v,De w)=ω0(v,w)\omega_0(De\,v,De\,w)=\omega_0(v,w)ω0​(Dev,Dew)=ω0​(v,w) for all z∈Uz\in Uz∈U.
  • gromovWidth is an sSup in ℝ≥0∞ of the admissible capacities, so an unbounded set would give ⊤; the goal asserts the value 4 and separately every capacity below 444.
  • The hypothesis is n≥2n\ge2n≥2, as in the source; the milestone allows n≥1n\ge1n≥1.

Welcome contributions: a Lean notion of symplectic embedding between open subsets of R2n\mathbb R^{2n}R2n, Gromov nonsqueezing (as an axiom-free target in its own right), and volume preservation for symplectic maps.

Selected references

  • OpenAI, Symplectic Balls in Symmetric Polar Products, OpenAI Math Release preprint, September 22, 2026. https://github.com/openai/math/blob/adc7f1241b42e322a6451854ab7e4b4c146bf78a/preprints/Symplectic-Balls-in-Symmetric-Polar-Products-September-22-2026/paper.pdf
  • OpenAI, The symmetric Mahler conjecture and its equality cases, OpenAI Math Release preprint, September 22, 2026. https://github.com/openai/math/blob/adc7f1241b42e322a6451854ab7e4b4c146bf78a/preprints/The-symmetric-Mahler-conjecture-and-its-equality-cases-September-22-2026/paper.pdf
  • S. Artstein-Avidan, R. Karasev, Y. Ostrover, From symplectic measurements to the Mahler conjecture, Duke Math. J. (2014). https://doi.org/10.1215/00127094-2794999
  • M. Gromov, Pseudo holomorphic curves in symplectic manifolds, Invent. Math. (1985). https://doi.org/10.1007/BF01388806
  • C. Viterbo, Metric and isoperimetric problems in symplectic geometry, J. Amer. Math. Soc. (2000). https://doi.org/10.1090/S0894-0347-00-00328-3
  • H. Hofer, E. Zehnder, Symplectic Invariants and Hamiltonian Dynamics, Birkhäuser (1994). https://doi.org/10.1007/978-3-0348-8540-9
  • P. Haim-Kislev, Y. Ostrover, A counterexample to Viterbo's conjecture, Ann. of Math. (2026). https://doi.org/10.4007/annals.2026.203.2.5
  • R. Karasev, Mahler's conjecture for some hyperplane sections, Israel J. Math. (2021). https://doi.org/10.1007/s11856-021-2114-4
  • V. G. B. Ramos, D. Sepe, On the rigidity of Lagrangian products, J. Symplectic Geom. (2019). https://doi.org/10.4310/JSG.2019.v17.n5.a7
  • J. Latschev, D. McDuff, F. Schlenk, The Gromov width of 4-dimensional tori, Geom. Topol. (2013). https://doi.org/10.2140/gt.2013.17.2813
  • J. Moser, On the volume elements on a manifold, Trans. Amer. Math. Soc. (1965). https://doi.org/10.1090/S0002-9947-1965-0182927-5
  • K. Mahler, Ein Übertragungsprinzip für konvexe Körper, Časopis Pěst. Mat. Fys. (1939). https://doi.org/10.21136/CPMF.1939.109441
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Discrete GeometryFunctional Analysis·Captain: wurtle

The Mahler Conjecture for General Convex BodiesResearch Paper

Motivation

The volume product of a convex body measures how large a body and its polar can simultaneously be. For a body without a distinguished centre, the polar is taken about the point that makes it smallest, the Santaló point, so the product is invariant under all invertible affine maps. The Blaschke–Santaló inequality identifies ellipsoids as the maximizers. Mahler's conjecture for general convex bodies asks for the minimizers and predicts simplices, with minimum value (n+1)n+1/(n!)2(n+1)^{n+1}/(n!)^2(n+1)n+1/(n!)2. The question arose from Mahler's work on polarity and the geometry of numbers, and it is the sharp form of the Bourgain–Milman reverse Santaló inequality.

This mission asks for a formal proof of the general Mahler conjecture with its equality case, as stated in an OpenAI preprint dated September 22, 2026 (source). The preprint has not been peer reviewed and its claims have not been independently verified; on the platform the Lean goal is open.

Timeline

  • 1938–1939 — Mahler proves the planar inequality among polygons with triangles as equality cases (Ein Minimalproblem für konvexe Polygone, Mathematica (Zutphen) B, 1938) and formulates the higher-dimensional problem (Časopis 1939).
  • 1949 — Santaló's affine invariant and the centre now named after him (Portugaliae Math., 1949).
  • 1987 — Bourgain and Milman prove an inverse Santaló inequality with an exponential constant (Invent. Math. 1987).
  • 1991 — Meyer completes the planar case for arbitrary convex bodies: triangles are exactly the minimizers (Monatsh. Math. 1991).
  • 2006 — Meyer and Reisner use shadow systems to prove the sharp inequality for polytopes with at most n+3n+3n+3 vertices (Mathematika 2006).
  • 2008–2012 — Kuperberg's explicit lower bounds via Gauss linking integrals (GAFA 2008); Nazarov's complex-analytic proof of Bourgain–Milman (GAFA seminar 2012).
  • 2011 — Kim and Reisner prove strict local minimality at every simplex (Mathematika 2011).
  • 2018 — Klartag's cone/Laplace-transform formulation of Mahler volumes (Adv. Math. 2018).
  • 2024 — Mastrantonis and Rubinstein extend Nazarov's method to nonsymmetric bodies (arXiv:2206.06188).
  • 2026 — Chen, Li, Xi and Xu prove the three-dimensional general case with tetrahedra as minimizers (arXiv:2605.09334).
  • September 2026 — The OpenAI preprint claims the general conjecture in every dimension (Theorem 1.1, p. 1).

Setting

A convex body K⊂RnK\subset\mathbb R^nK⊂Rn is a compact convex set with nonempty interior; ∣⋅∣|\cdot|∣⋅∣ is Lebesgue measure and ⟨⋅,⋅⟩\langle\cdot,\cdot\rangle⟨⋅,⋅⟩ the Euclidean inner product. For an interior point zzz, the polar of KKK about zzz is

(K−z)∘={y∈Rn: ⟨y,x−z⟩≤1 for all x∈K},(K-z)^\circ=\{y\in\mathbb R^n:\ \langle y,x-z\rangle\le1\ \text{for all }x\in K\},(K−z)∘={y∈Rn: ⟨y,x−z⟩≤1 for all x∈K},

and the volume product is

P(K)=inf⁡z∈int⁡K∣K∣ ∣(K−z)∘∣.P(K)=\inf_{z\in\operatorname{int}K}|K|\,|(K-z)^\circ|.P(K)=z∈intKinf​∣K∣∣(K−z)∘∣.

The infimum is attained at the unique Santaló point s(K)s(K)s(K). A simplex is the convex hull of n+1n+1n+1 affinely independent points.

Formalization targets

Goal: the general Mahler conjecture (Theorem 1.1, p. 1)

For every n≥1n\ge1n≥1 and every convex body K⊂RnK\subset\mathbb R^nK⊂Rn,

P(K) ≥ (n+1)n+1(n!)2,P(K)\ \ge\ \frac{(n+1)^{n+1}}{(n!)^2},P(K) ≥ (n!)2(n+1)n+1​,

with equality if and only if KKK is a simplex.

Significance

The result itself. It is the exact form of a problem open since the 1930s and previously settled only in dimensions 222 and 333 and for polytopes with few vertices. Because the infimum over centres is taken, it gives the same lower bound for ∣K∣∣(K−z)∘∣|K||(K-z)^\circ|∣K∣∣(K−z)∘∣ at every interior point zzz. Via the known geometric-to-functional implication, the preprint derives the sharp functional Mahler inequality for log-concave functions and an entropy–transport inequality (Corollary 1.2, p. 4; Corollary 8.1, p. 41). The symmetric conjecture, with the larger constant 4n/n!4^n/n!4n/n!, is a different statement treated in a companion preprint.

Formalizing it. The proof combines convex cones and their Laplace transforms, Gaussian Sobolev calculus, Moreau's decomposition, matrix divided differences, and certified one-variable inequalities. A formal proof would provide checked versions of these tools and of the Santaló point's existence and uniqueness. No machine-checked proof of the conjecture in any dimension n≥2n\ge2n≥2 is known.

Difficulty

Symmetrization does not apply, the volume product is not convex along natural deformations except in restricted families (shadow systems), and local minimality at simplices says nothing about distant bodies. In the preprint's route the main obstacle (Introduction, pp. 2–3) is that the Jacobian matrices Pz=DΠC(Z+ξz)P_z=D\Pi_C(Z+\xi_z)Pz​=DΠC​(Z+ξz​) of the Gaussian-averaged cone projections neither commute nor increase in zzz: bounding them separately loses both the sharp constant and the equality case. Controlling them jointly requires comparing the whole family with spectral thresholds of a linear Gaussian matrix (Sections 5–7), and equality must then force the cone to split into half-lines.

Formalization scope

  • Bodies are subsets of EuclideanSpace ℝ (Fin n) with IsCompact, Convex ℝ and nonempty interior, and n≥1n\ge1n≥1.
  • polarAt K z is the polar about zzz; volumeProduct K is the sInf over interior K of (volume K).toReal * (volume (polarAt K z)).toReal. For an interior zzz the polar is bounded, so toReal reads the true volume; the index set is nonempty because the interior is.
  • The goal is a conjunction: the inequality, and volumeProduct K = (n+1)^(n+1)/(n!)^2 iff K = convexHull ℝ (range v) for some affinely independent v : Fin (n+1) → _.
  • The Santaló point is not named in Lean; using the infimum over interior points is equivalent to evaluating at s(K)s(K)s(K) because the infimum is attained there (Section 2 of the preprint).

Welcome contributions: polar bodies and their volumes in Mathlib, the Santaló point, Laplace transforms of convex cones, and Gaussian integration by parts.

Selected references

  • OpenAI, The Mahler Conjecture for General Convex Bodies, OpenAI Math Release preprint, September 22, 2026. https://github.com/openai/math/blob/adc7f1241b42e322a6451854ab7e4b4c146bf78a/preprints/The-Mahler-Conjecture-for-General-Convex-Bodies-September-22-2026/paper.pdf
  • OpenAI, The symmetric Mahler conjecture and its equality cases, OpenAI Math Release preprint, September 22, 2026. https://github.com/openai/math/blob/adc7f1241b42e322a6451854ab7e4b4c146bf78a/preprints/The-symmetric-Mahler-conjecture-and-its-equality-cases-September-22-2026/paper.pdf
  • K. Mahler, Ein Übertragungsprinzip für konvexe Körper, Časopis Pěst. Mat. Fys. 68 (1939). https://doi.org/10.21136/CPMF.1939.109441
  • M. Meyer, Convex bodies with minimal volume product in R2\mathbb R^2R2, Monatsh. Math. (1991). https://doi.org/10.1007/BF01351770
  • J. Bourgain, V. Milman, New volume ratio properties for convex symmetric bodies in Rn\mathbb R^nRn, Invent. Math. (1987). https://doi.org/10.1007/BF01388911
  • G. Kuperberg, From the Mahler conjecture to Gauss linking integrals, GAFA (2008). https://doi.org/10.1007/s00039-008-0669-4
  • M. Meyer, S. Reisner, Shadow systems and volumes of polar convex bodies, Mathematika (2006). https://doi.org/10.1112/S0025579300000061
  • J. Kim, S. Reisner, Local minimality of the volume-product at the simplex, Mathematika (2011). https://doi.org/10.1112/S0025579310001555
  • B. Klartag, Isotropic constants and Mahler volumes, Adv. Math. (2018). https://doi.org/10.1016/j.aim.2018.03.009
  • V. Mastrantonis, Y. A. Rubinstein, The Nazarov proof of the non-symmetric Bourgain–Milman inequality, Indiana Univ. Math. J. (2024). https://arxiv.org/abs/2206.06188
  • S. Chen, Y. Li, D. Xi, Z. Xu, The Mahler Conjecture in Three Dimensions, preprint (2026). https://arxiv.org/abs/2605.09334v3
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AnalysisHarmonic Analysis·Captain: wurtle

An Endpoint Gradient Bound for the Centered Disk Maximal OperatorResearch Paper

Motivation

The Hardy–Littlewood maximal function replaces a function by the largest of its averages around each point. It is the basic tool for differentiation theorems and singular integrals, and it is bounded on LpL^pLp for p>1p>1p>1 but not on L1L^1L1. Kinnunen showed that it also preserves first-order Sobolev regularity: it is bounded on W1,p(Rn)W^{1,p}(\mathbb R^n)W1,p(Rn) for 1<p<∞1<p<\infty1<p<∞, because ∣∇Mf∣≤M∣∇f∣|\nabla Mf|\le M|\nabla f|∣∇Mf∣≤M∣∇f∣ pointwise (Kinnunen 1997). At p=1p=1p=1 this argument breaks, since MMM is unbounded on L1L^1L1. Hajłasz and Onninen asked whether the gradient estimate ∥∇Mf∥1≤C∥∇f∥1\|\nabla Mf\|_1\le C\|\nabla f\|_1∥∇Mf∥1​≤C∥∇f∥1​ nevertheless holds (Question 1 in Ann. Acad. Sci. Fenn. Math. 2004). The question is a test of whether maximal operators improve or destroy regularity at the endpoint, where the usual LpL^pLp machinery is unavailable.

This mission asks for a formal proof of the planar centered-disk case, as stated in an OpenAI preprint dated September 26, 2026 (source). The preprint has not been peer reviewed and its claims have not been independently verified; on the platform the Lean goal is open.

Background

  • 1997 — Kinnunen: MMM is bounded on W1,pW^{1,p}W1,p, 1<p<∞1<p<\infty1<p<∞ (Israel J. Math. 1997).
  • 2002–2007 — In one dimension, Tanaka proves an L1L^1L1 derivative bound for the uncentered operator (Bull. Austral. Math. Soc. 2002); Aldaz and Pérez Lázaro obtain the sharp variation constant and absolute continuity (Trans. AMS 2007).
  • 2004 — Hajłasz and Onninen pose the endpoint question.
  • 2009 — Aldaz and Pérez Lázaro treat block-decreasing inputs in higher dimensions (Studia Math. 2009).
  • 2015 — Kurka proves a variation bound for the one-dimensional centered operator (Ann. Acad. Sci. Fenn. Math. 2015).
  • 2018 — Luiro proves the L1L^1L1 gradient estimate for radial inputs and the uncentered ball operator (Ark. Mat. 2018).
  • 2020–2025 — Beltran–Madrid and Weigt treat fractional centered operators (JFA 2020; Math. Z. 2022); Weigt proves variation bounds for dyadic and uncentered-cube maximal operators (IMRN 2023; JEMS 2025); Lahti and Weigt show that a variation bound for the centered operator upgrades to Sobolev regularity (arXiv:2510.01936).
  • September 2026 — The OpenAI preprint claims the planar centered-disk endpoint bound (Theorem 1.1, p. 1).

Setting

Identify R2\mathbb R^2R2 with the Euclidean plane and write B(x,r)B(x,r)B(x,r) for the open disk of radius rrr centered at xxx. For a locally integrable real function fff, the centered disk maximal function is

Mf(x)=sup⁡r>01πr2∫B(x,r)∣f(y)∣ dy∈[0,∞].Mf(x)=\sup_{r>0}\frac1{\pi r^2}\int_{B(x,r)}|f(y)|\,dy\in[0,\infty].Mf(x)=r>0sup​πr21​∫B(x,r)​∣f(y)∣dy∈[0,∞].

The space W1,1(R2)W^{1,1}(\mathbb R^2)W1,1(R2) consists of integrable fff whose distributional gradient is represented by an integrable vector field ∇f\nabla f∇f, i.e. ∫f ∂iφ=−∫(∇f)iφ\int f\,\partial_i\varphi=-\int(\nabla f)_i\varphi∫f∂i​φ=−∫(∇f)i​φ for all φ∈Cc∞\varphi\in C_c^\inftyφ∈Cc∞​. Norms of gradients are Euclidean: ∥∇f∥1=∫∣∇f∣\|\nabla f\|_1=\int|\nabla f|∥∇f∥1​=∫∣∇f∣. For the signed estimate, put Atg(x)=1πt2∫B(x,t)gA_tg(x)=\frac1{\pi t^2}\int_{B(x,t)}gAt​g(x)=πt21​∫B(x,t)​g and Sa,bg(x)=sup⁡a≤t≤bAtg(x)S_{a,b}g(x)=\sup_{a\le t\le b}A_tg(x)Sa,b​g(x)=supa≤t≤b​At​g(x).

Formalization targets

Milestone: Proposition 1.2 (signed finite-band estimate, p. 2)

There is an absolute constant CCC such that for every real g∈Cc∞(R2)g\in C_c^\infty(\mathbb R^2)g∈Cc∞​(R2) and 0<a≤b0<a\le b0<a≤b with b/ab/ab/a a power of two (including 111),

∫R2∣∇Sa,bg∣ dx≤C∫R2∣∇g∣ dx,\int_{\mathbb R^2}|\nabla S_{a,b}g|\,dx\le C\int_{\mathbb R^2}|\nabla g|\,dx,∫R2​∣∇Sa,b​g∣dx≤C∫R2​∣∇g∣dx,

with CCC independent of aaa, bbb and the number of dyadic scales.

Goal: Theorem 1.1 (p. 1)

There is an absolute constant C<∞C<\inftyC<∞ such that for every real f∈W1,1(R2)f\in W^{1,1}(\mathbb R^2)f∈W1,1(R2), MfMfMf is finite almost everywhere, locally integrable, belongs to Wloc1,1(R2)W^{1,1}_{\mathrm{loc}}(\mathbb R^2)Wloc1,1​(R2), and has a globally integrable weak gradient with

∫R2∣∇Mf∣ dx≤C∫R2∣∇f∣ dx.\int_{\mathbb R^2}|\nabla Mf|\,dx\le C\int_{\mathbb R^2}|\nabla f|\,dx.∫R2​∣∇Mf∣dx≤C∫R2​∣∇f∣dx.

Significance

The result itself. It resolves the planar centered-disk case of the Hajłasz–Onninen question with no radiality or support assumption. As a consequence (Corollary 6.3, p. 39) the bound extends to BV(R2)BV(\mathbb R^2)BV(R2) inputs and yields a co-area type perimeter bound for level sets of M1EM\mathbf 1_EM1E​. The constant is absolute but not optimized. Higher dimensions, other centered maximal operators, and continuity of f↦∇Mff\mapsto\nabla Mff↦∇Mf in W1,1W^{1,1}W1,1 remain separate questions.

Formalizing it. Mathlib has Lebesgue integration, weak derivatives only in limited form, and no maximal-function regularity theory. A formal proof would need distributional gradients, Poincaré inequalities on squares, dyadic multiscale decompositions and a vector-measure representation of bounded distributional derivatives (the preprint's Appendix A). These pieces are reusable across harmonic analysis.

Difficulty

For p>1p>1p>1 one bounds ∣∇Mf∣≤M∣∇f∣|\nabla Mf|\le M|\nabla f|∣∇Mf∣≤M∣∇f∣ and uses the strong maximal inequality, which fails for p=1p=1p=1. One-dimensional proofs order the optimizing intervals, and that ordering has no analogue for families of centered disks. Fractional-order proofs use that optimizing balls overlap little, a mechanism that degenerates at order zero. The preprint (Sections 2–5) instead proves the signed finite-band estimate uniformly in the number of scales: it uses a vanishing first moment at interior maximizing radii, a concentration-in-a-thin-shell lemma (Lemma 2.4, p. 8), and two multiscale constructions that pay for direction changes in scale and space. A variation bound alone would leave a possibly singular derivative measure; removing the singular part needs the signed form of Proposition 1.2 applied to locally mean-subtracted inputs (Section 6).

Formalization scope

  • The plane is EuclideanSpace ℝ (Fin 2). maximal f x is an ℝ≥0∞-valued supremum over all real r>0r>0r>0 of lower Lebesgue integrals of ∣f∣|f|∣f∣ over Metric.ball x r divided by πr2\pi r^2πr2; the goal asserts it is finite a.e. before passing to maximalReal = toReal.
  • HasWeakGradient f g is the integration-by-parts identity against every C∞C^\inftyC∞ compactly supported test function, coordinatewise; the input is Integrable f, Integrable g, HasWeakGradient f g, which is exactly W1,1W^{1,1}W1,1 with weak gradient g. The bound is stated against this g, so it does not depend on a choice of representative.
  • InW11Loc asks for local integrability and a locally integrable weak gradient; the goal also asks for one integrable weak gradient G with ∫ ‖G‖ ≤ C * ∫ ‖g‖, C ≥ 0 chosen before f.
  • The milestone uses signed averages (Bochner integrals) and sSup over the closed radius band [a,2ma][a,2^ma][a,2ma]; the band envelope is continuous in rrr, so the supremum is finite. Inputs are ContDiff ℝ ∞ with compact support.
  • The BV extension (Corollary 6.3) is not part of either target.

Selected references

  • OpenAI, An Endpoint Gradient Bound for the Centered Disk Maximal Operator, OpenAI Math Release preprint, September 26, 2026. https://github.com/openai/math/blob/adc7f1241b42e322a6451854ab7e4b4c146bf78a/preprints/An-Endpoint-Gradient-Bound-for-the-Centered-Disk-Maximal-Operator-September-26-2026/article.pdf
  • J. Kinnunen, The Hardy–Littlewood maximal function of a Sobolev function, Israel J. Math. (1997). https://doi.org/10.1007/BF02773636
  • P. Hajłasz, J. Onninen, On boundedness of maximal functions in Sobolev spaces, Ann. Acad. Sci. Fenn. Math. (2004). https://afm.journal.fi/article/view/135096
  • H. Tanaka, A remark on the derivative of the one-dimensional Hardy–Littlewood maximal function, Bull. Austral. Math. Soc. (2002). https://doi.org/10.1017/S0004972700020293
  • J. M. Aldaz, J. Pérez Lázaro, Functions of bounded variation, the derivative of the one dimensional maximal function, and applications to inequalities, Trans. AMS (2007). https://doi.org/10.1090/S0002-9947-06-04347-9
  • O. Kurka, On the variation of the Hardy–Littlewood maximal function, Ann. Acad. Sci. Fenn. Math. (2015). https://doi.org/10.5186/aasfm.2015.4003
  • H. Luiro, The variation of the maximal function of a radial function, Ark. Mat. (2018). https://doi.org/10.4310/ARKIV.2018.v56.n1.a9
  • J. Weigt, The variation of the uncentered maximal operator with respect to cubes, J. Eur. Math. Soc. (2025). https://doi.org/10.4171/JEMS/1575
  • P. Lahti, J. Weigt, The centered maximal operator removes the non-concave Cantor part from the gradient, arXiv:2510.01936 (2025). https://arxiv.org/abs/2510.01936v1
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AnalysisHarmonic Analysis·Captain: wurtle

A uniform Hilbert transform estimate for Lipschitz directionsResearch Paper

Motivation

The Hilbert transform Hf(x)=p.v.∫f(x−t) dttHf(x)=\mathrm{p.v.}\int f(x-t)\,\frac{dt}{t}Hf(x)=p.v.∫f(x−t)tdt​ is the basic singular integral of harmonic analysis. In the plane one can take it along a line through each point, with the direction of the line allowed to depend on the point: given a unit vector field v:R2→S1v:\mathbb R^2\to S^1v:R2→S1, integrate fff along the segment through xxx in direction v(x)v(x)v(x). Whether such directional Hilbert transforms are bounded on L2L^2L2 is one of the central problems connecting singular integrals, Kakeya-type geometry and time–frequency analysis. If vvv depends on only one coordinate, the L2L^2L2 problem already contains Carleson's theorem on almost-everywhere convergence of Fourier series. For general fields some regularity of vvv is necessary, and some truncation of the integration length is necessary because a field can turn.

Stein asked whether a Lipschitz field suffices when the integration length is at most a small multiple of 1/Lip(v)1/\mathrm{Lip}(v)1/Lip(v). In the formulation of Lacey and Li, this is a uniform weak-(2,2)(2,2)(2,2) conjecture. A parallel conjecture of Zygmund concerns the corresponding maximal averages.

Timeline

  • 1966. Carleson proves almost-everywhere convergence of Fourier series of L2L^2L2 functions (doi:10.1007/BF02392815); the one-variable-field L2L^2L2 case of the directional problem reduces to this.
  • 1987. Stein lists the Lipschitz directional Hilbert transform among problems in harmonic analysis in his ICM address (Problems in harmonic analysis related to curvature and oscillatory integrals).
  • 1989. Bourgain proves an L2L^2L2 bound for the maximal averaging operator along analytic vector fields (doi:10.1017/CBO9780511662294.006).
  • 2006. Lacey and Li prove annular weak-(2,2)(2,2)(2,2) and strong LpL^pLp, p>2p>2p>2, bounds for directional Hilbert transforms with measurable directions (doi:10.1090/S0002-9947-06-03869-4), and a Lipschitz Kakeya maximal theorem.
  • 2010. Lacey and Li's memoir develops the relation between maximal operators and the Hilbert-transform problem, with conditional results requiring stronger maximal estimates or C1+ηC^{1+\eta}C1+η fields (doi:10.1090/S0065-9266-10-00572-7).
  • 2012. Stein and Street prove local LpL^pLp bounds for singular Radon transforms associated with real-analytic maps (doi:10.1016/j.aim.2011.11.016).
  • 2013. Bateman proves single-annulus LpL^pLp estimates for fields depending on one coordinate (doi:10.4171/RMI/748); Bateman and Thiele prove strong LpL^pLp bounds, 3/2<p<∞3/2<p<\infty3/2<p<∞, for the full transform along one-variable fields (doi:10.2140/apde.2013.6.1577).
  • 2015–2017. Guo extends the one-variable setting to fields constant along Lipschitz curves (doi:10.2140/apde.2015.8.1263, doi:10.1090/tran/6750) and proves single-annulus variation-norm bounds for Lipschitz fields; Guo and Thiele treat a lacunary model of Lipschitz fields (doi:10.1112/S0025579316000280).
  • 2018. Di Plinio and Parissis extend the lacunary framework (doi:10.1007/s11856-018-1724-y); Di Plinio, Guo, Thiele and Zorin-Kranich show that uniform L2L^2L2 bounds on vertical frequency bands imply the full short principal-value bound under a small Lipschitz condition (doi:10.1016/j.jfa.2018.07.005).

The source of this mission, an OpenAI preprint dated September 25, 2026, claims the uniform strong L2L^2L2 bound at short scale for every Lipschitz field.

Setting

Let v:R2→S1v:\mathbb R^2\to S^1v:R2→S1 be Lipschitz with Lip(v)≤1\mathrm{Lip}(v)\le1Lip(v)≤1. For 0<ε<a0<\varepsilon<a0<ε<a the short directional Hilbert transform is

Hv,aεf(x)=∫ε<∣t∣<af(x−t v(x)) dtt.H^{\varepsilon}_{v,a}f(x)=\int_{\varepsilon<|t|<a} f\bigl(x-t\,v(x)\bigr)\,\frac{dt}{t}.Hv,aε​f(x)=∫ε<∣t∣<a​f(x−tv(x))tdt​.

The direction is frozen at the output point xxx. For a Schwartz function fff the principal value Hv,af=lim⁡ε↓0Hv,aεfH_{v,a}f=\lim_{\varepsilon\downarrow0}H^\varepsilon_{v,a}fHv,a​f=limε↓0​Hv,aε​f exists at every point, since f(x−tv(x))−f(x+tv(x))=Ox(∣t∣)f(x-tv(x))-f(x+tv(x))=O_x(|t|)f(x−tv(x))−f(x+tv(x))=Ox​(∣t∣).

Formalization targets

Goal: Theorem 1.1

There are absolute constants a∗∈(0,1/2)a_*\in(0,1/2)a∗​∈(0,1/2) and C∗<∞C_*<\inftyC∗​<∞ such that every unit field vvv with Lip(v)≤1\mathrm{Lip}(v)\le1Lip(v)≤1 satisfies, for all f∈S(R2)f\in\mathcal S(\mathbb R^2)f∈S(R2),

sup⁡0<ε<a∗∥Hv,a∗εf∥L2≤C∗∥f∥L2,∥Hv,a∗f∥2≤C∗∥f∥2,\sup_{0<\varepsilon<a_*}\|H^{\varepsilon}_{v,a_*}f\|_{L^2}\le C_*\|f\|_{L^2},\qquad \|H_{v,a_*}f\|_2\le C_*\|f\|_2,0<ε<a∗​sup​∥Hv,a∗​ε​f∥L2​≤C∗​∥f∥L2​,∥Hv,a∗​​f∥2​≤C∗​∥f∥2​, ∣{x:∣Hv,a∗f(x)∣>λ}∣≤C∗2λ−2∥f∥22(λ>0),\bigl|\{x:|H_{v,a_*}f(x)|>\lambda\}\bigr|\le C_*^2\lambda^{-2}\|f\|_2^2\qquad(\lambda>0),​{x:∣Hv,a∗​​f(x)∣>λ}​≤C∗2​λ−2∥f∥22​(λ>0),

and the truncations and the principal value extend to bounded operators on L2L^2L2 with norm at most C∗C_*C∗​. The constants a∗a_*a∗​ and C∗C_*C∗​ are existential; no numerical value is fixed. The Lean statement OAI.LipschitzHilbert.main is open on the platform.

The proposal also contains OAI.LipschitzHilbert.uniform_truncation, the rescaled form for KKK-Lipschitz fields at every outer length R≤1/(106K)R\le 1/(10^6K)R≤1/(106K). By the dilation x↦Kxx\mapsto Kxx↦Kx it is the same estimate at the reciprocal-Lipschitz scale; its explicit constant 10−610^{-6}10−6 is a convention of the formalization, not of the paper.

Significance

The theorem answers the short-scale form of Stein's question affirmatively and with a strong (not only weak-type) L2L^2L2 bound, for fields depending on both coordinates and with no regularity beyond Lipschitz. Earlier unconditional results required the field to depend on one variable, to be constant along a foliation, to be analytic, to take lacunary directions, or restricted the frequency to one annulus. The uniformity in the inner truncation is an operator bound for each truncation, which is what the principal value and the weak-type bound are derived from.

The result is claimed in an OpenAI preprint of 87 pages; it has not been peer reviewed and no machine-checked proof exists. The Lean goal records the complete short-scale conclusion; a formal proof would certify a long chain of time–frequency arguments (wave-packet decompositions, size and density selection, a Lipschitz Kakeya input, and a phase-gain iteration).

Difficulty

Restricting to short scales limits how far the field turns but does not make the operator a Fourier multiplier: the line of integration still varies with the output point. Positive (maximal) operator bounds lose all oscillation, while the one-variable reduction to Carleson's theorem is unavailable when vvv depends on both coordinates. The known band-to-full reassembly reduces matters to one vertical frequency band, but on a band one needs a restricted estimate with a logarithmic gain in the ratio of the measures of the input and test sets; the Lacey–Li Kakeya estimate only provides a polynomial loss in that ratio, so an additional oscillatory saving is required.

Formalization scope

  • The plane is EuclideanSpace ℝ (Fin 2); inputs are SchwartzMap Plane ℂ, norms are eLpNorm _ 2 volume in ℝ≥0∞.
  • The field is v : Plane → Plane with LipschitzWith 1 v and ‖v x‖ = 1 for all x.
  • twoSidedTruncation v ε a f x is the sum of interval integrals over [−a,−ε][-a,-\varepsilon][−a,−ε] and [ε,a][\varepsilon,a][ε,a] of t−1f(x−tv(x))t^{-1}f(x-tv(x))t−1f(x−tv(x)); smoothPrincipalValue integrates the symmetric quotient over (0,a)(0,a)(0,a), with the removable value at t=0t=0t=0 filled by the derivative.
  • ShortHilbertConclusion a C bundles the five clauses (truncation bound for 0<ε<a0<\varepsilon<a0<ε<a, principal-value bound, weak-(2,2) bound at every finite nonzero level, and bounded Lp extensions agreeing a.e. on Schwartz inputs). The goal asks for a∈(0,1/2)a\in(0,1/2)a∈(0,1/2) and C>0C>0C>0.

A complete development needs singular-integral and Littlewood–Paley machinery on R2\mathbb R^2R2, wave-packet analysis and a Lipschitz Kakeya maximal estimate; much of this is reusable for other time–frequency problems. Contributions formalizing the band-restricted estimate, the band-to-full reassembly, or the one-dimensional inputs (the maximal truncated Hilbert transform) are welcome.

Selected references

  • OpenAI, A uniform Hilbert transform estimate for Lipschitz directions, preprint, September 25, 2026. https://github.com/openai/math/blob/adc7f1241b42e322a6451854ab7e4b4c146bf78a/preprints/A-uniform-Hilbert-transform-estimate-for-Lipschitz-directions-September-25-2026/main.pdf
  • M. Lacey, X. Li, On a conjecture of E. M. Stein on the Hilbert transform on vector fields, Mem. Amer. Math. Soc., 2010. https://doi.org/10.1090/S0065-9266-10-00572-7
  • M. T. Lacey, X. Li, Maximal theorems for the directional Hilbert transform on the plane, Trans. Amer. Math. Soc., 2006. https://doi.org/10.1090/S0002-9947-06-03869-4
  • M. Bateman, C. Thiele, LpL^pLp estimates for the Hilbert transforms along a one-variable vector field, Anal. PDE, 2013. https://doi.org/10.2140/apde.2013.6.1577
  • F. Di Plinio, S. Guo, C. Thiele, P. Zorin-Kranich, Square functions for bi-Lipschitz maps and directional operators, J. Funct. Anal., 2018. https://doi.org/10.1016/j.jfa.2018.07.005
  • S. Guo, C. Thiele, Hilbert transforms along Lipschitz direction fields: a lacunary model, Mathematika, 2017. https://doi.org/10.1112/S0025579316000280
  • E. M. Stein, B. Street, Multi-parameter singular Radon transforms III: real analytic surfaces, Adv. Math., 2012. https://doi.org/10.1016/j.aim.2011.11.016
  • L. Carleson, On convergence and growth of partial sums of Fourier series, Acta Math., 1966. https://doi.org/10.1007/BF02392815
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Koebe's Circle-Domain ConjectureResearch Paper

Motivation

The Riemann mapping theorem says that every simply connected proper domain in the plane is conformally equivalent to the unit disk. For domains with more complicated complements one needs a model with many "holes". Koebe's Kreisnormierungsproblem (1908) asks whether every domain in the Riemann sphere is conformally equivalent to a circle domain, one whose complementary components are all round disks or points. Such a model would give a canonical geometric picture of an arbitrary planar domain, and it is closely tied to circle packings, Kleinian groups and the geometry of hyperbolic surfaces of genus zero.

Timeline

  • 1908. Koebe poses the problem (Nachr. Ges. Wiss. Göttingen, 1908).
  • 1920. Koebe's treatment of the finitely connected case (doi:10.1007/BF01199400).
  • 1993. He and Schramm prove the conjecture for countably connected domains (doi:10.2307/2946541).
  • 1995. Schramm introduces transboundary extremal length and treats domains bounded by points and KKK-quasicircles (doi:10.1007/BF02788827).
  • 2025. Rajala shows that arbitrary interior exhaustions can fail to have circle-domain limits and proves an exhaustion refinement theorem for countably connected domains (doi:10.1353/ajm.2025.a966291); Ntalampekos and Rajala study exhaustions of circle domains (arXiv:2312.06840).
  • 2026. Esmayli and Rajala prove uniformization for cospread domains and under a quasitripod condition (arXiv:2401.08485); Karafyllia and Ntalampekos treat spherical Gromov-hyperbolic domains (arXiv:2405.13782). Ntalampekos surveys the area (arXiv:2603.15098).

The source of this mission, an OpenAI preprint dated September 23, 2026, claims the conjecture in its unrestricted form.

Setting

The Riemann sphere is C^=C∪{∞}\widehat{\mathbb C}=\mathbb C\cup\{\infty\}C=C∪{∞}, with local coordinate zzz near finite points and 1/z1/z1/z near ∞\infty∞. A domain is a nonempty connected open subset. A map fff is conformal at ppp if it is continuous at ppp and, in these coordinates, complex differentiable at ppp with nonzero derivative. A conformal equivalence f:U→Vf:U\to Vf:U→V is a bijection that is conformal at every point of UUU and whose inverse is conformal at every point of VVV.

A closed round disk in C^\widehat{\mathbb C}C is the image of the closed unit disk under a Möbius transformation z↦(az+b)/(cz+d)z\mapsto (az+b)/(cz+d)z↦(az+b)/(cz+d), ad−bc≠0ad-bc\ne0ad−bc=0; these are closed Euclidean disks, closed half-planes together with ∞\infty∞, and complements of open disks. A circle domain is a domain each of whose complementary connected components is a closed round disk or a single point. The complement may be empty, finite, countable or uncountable.

Formalization targets

Goal: Theorem 1.1 (circle-domain uniformization)

∀ G⊂C^ domain∃ Ω circle domain, ∃ f:G→ conformal Ω bijective.\forall\,G\subset\widehat{\mathbb C}\ \text{domain}\quad\exists\,\Omega\ \text{circle domain},\ \exists\,f:G\xrightarrow{\ \text{conformal}\ }\Omega\ \text{bijective}.∀G⊂C domain∃Ω circle domain, ∃f:G conformal ​Ω bijective.

Lean: OAI.Problem047.koebe_circle_domain, open on the platform.

Significance

The theorem would complete the existence half of Koebe's problem with no restriction on the number, size or geometry of the complementary components. The paper derives a consequence for hyperbolic geometry (Corollary 8.1): every complete hyperbolic surface of genus zero is isometric to the boundary of the convex hull of a closed set in ∂∞H3\partial_\infty\mathbb H^3∂∞​H3 whose components are round disks or points. Combined with the exhaustion theorem of Ntalampekos and Rajala, it also gives convergent finitely connected approximations for every proper domain. Uniqueness up to Möbius maps is a different question (the He–Schramm rigidity conjecture), addressed in the companion mission on removable boundaries.

The result is claimed in an OpenAI preprint that has not been peer reviewed; no machine-checked proof exists. Mathlib has neither the Riemann mapping theorem in full generality nor finitely connected circle-domain uniformization, so a formal proof would build substantial reusable complex-analytic infrastructure.

Difficulty

The standard approach uniformizes finitely connected approximations, whose complements are finitely many round disks, and passes to a limit. The difficulty is control at the limit: with possibly uncountably many complementary components, a limiting component can be strictly larger than the round disk obtained by following one approximating disk, or can be a non-round continuum for which no disk was followed at all. Rajala showed that arbitrary exhaustions can indeed fail to produce circle-domain limits, so the approximations must be chosen with care, and all components must be controlled simultaneously, not one at a time.

Formalization scope

  • Sphere := OnePoint ℂ; Möbius maps are Matrix.GeneralLinearGroup (Fin 2) ℂ acting on it.
  • IsConformalAt f p: ContinuousAt f p and a nonzero HasDerivAt of fff in the charts chart p, chart (f p) (identity coordinate at finite points, z↦1/zz\mapsto1/zz↦1/z at ∞\infty∞).
  • IsConformalEquivalence f U V: fff conformal on UUU, MapsTo f U V, and a conformal g on VVV with MapsTo g V U that is a two-sided inverse.
  • IsCircleDomain V: open, IsConnected (hence nonempty), and every connectedComponentIn Vᶜ p is a singleton or IsRoundClosedDisk (a Möbius image of the closed unit disk).
  • The goal quantifies over all open connected U; there is no countability or regularity assumption on the complement.

A complete development needs finitely connected uniformization, normal families on the sphere, Dirichlet energy and extremal length, and component correspondence for limits. Contributions formalizing the named intermediate results (Theorem 3.1 finite transfer, Theorem 4.3 compatible barrier lemma, Theorem 5.1 positive-law alternative, Theorem 7.5 retained-test transfer) or the classical He–Schramm countable case are welcome.

Selected references

  • OpenAI, Koebe's Circle-Domain Conjecture, preprint, September 23, 2026. https://github.com/openai/math/blob/adc7f1241b42e322a6451854ab7e4b4c146bf78a/preprints/Koebes-Circle-Domain-Conjecture-September-23-2026/paper.pdf
  • P. Koebe, Über die Uniformisierung beliebiger analytischer Kurven (Dritte Mitteilung), Nachr. Ges. Wiss. Göttingen, 1908.
  • P. Koebe, Abhandlungen zur Theorie der konformen Abbildung VI, Math. Z., 1920. https://doi.org/10.1007/BF01199400
  • Z.-X. He, O. Schramm, Fixed points, Koebe uniformization and circle packings, Ann. of Math., 1993. https://doi.org/10.2307/2946541
  • O. Schramm, Transboundary extremal length, J. Analyse Math., 1995. https://doi.org/10.1007/BF02788827
  • K. Rajala, Uniformization of planar domains by exhaustion, Amer. J. Math., 2025. https://doi.org/10.1353/ajm.2025.a966291
  • D. Ntalampekos, K. Rajala, Exhaustions of circle domains, IMRN, 2025. https://doi.org/10.1093/imrn/rnaf296
  • B. Esmayli, K. Rajala, Conformal uniformization of domains bounded by quasitripods, Duke Math. J., 2026. https://doi.org/10.1215/00127094-2025-0035
  • C. Karafyllia, D. Ntalampekos, Uniformization of Gromov hyperbolic domains by circle domains, Duke Math. J., 2026. https://doi.org/10.1215/00127094-2025-0076
  • D. Ntalampekos, Uniformization problems in the plane: A survey, preprint, 2026. https://arxiv.org/abs/2603.15098
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Removable Boundaries and Rigidity of Circle DomainsResearch Paper

Motivation

A circle domain is a domain in the Riemann sphere whose complementary components are round disks or points. Koebe asked in 1908 whether every domain is conformally equivalent to a circle domain (existence). A second question is rigidity: when is that circle-domain model unique up to Möbius transformations? For finitely and countably connected domains the model is unique, but for domains with uncountably many boundary components uniqueness can fail, and the boundary geometry decides. He and Schramm conjectured that a circle domain is rigid exactly when its boundary is conformally removable. Rigidity is what makes the circle-domain model canonical, and it connects conformal geometry with removability questions for quasiconformal and Sobolev maps.

Timeline

  • 1993. He and Schramm prove uniformization and rigidity for countably connected circle domains (doi:10.2307/2946541).
  • 1994. He and Schramm prove rigidity when the boundary has σ\sigmaσ-finite linear measure, and conjecture that rigidity is equivalent to conformal removability of the boundary (doi:10.1007/BF01231761).
  • 2000. Jones and Smirnov relate removability for continuous Sobolev functions to quasiconformal removability (doi:10.1007/BF02384320).
  • 2016. Younsi proves that conformal rigidity is equivalent to quasiconformal rigidity and studies the removability formulations (doi:10.1016/j.aim.2016.08.039).
  • 2020. Ntalampekos and Younsi prove rigidity under square integrability of the quasihyperbolic distance, covering Hölder and John circle domains (doi:10.1007/s00222-019-00921-1).
  • 2023–2024. Ntalampekos proves rigidity when point components are countably negligible for extremal distance (CNED) and continuous Sobolev extension across closed CNED sets (doi:10.1090/tran/8923, doi:10.1007/s00029-024-00951-5).
  • 2025. Rajala constructs a rigid circle domain with non-removable boundary, so rigidity does not imply removability (doi:10.1112/plms.70081).

The source of this mission, an OpenAI preprint dated September 23, 2026, claims the remaining implication: removability implies rigidity.

Setting

The Riemann sphere C^=C∪{∞}\widehat{\mathbb C}=\mathbb C\cup\{\infty\}C=C∪{∞} has local coordinates zzz and 1/z1/z1/z. A map is conformal at ppp if it is continuous there and complex differentiable with nonzero derivative in these coordinates; a conformal equivalence f:Ω→Ω′f:\Omega\to\Omega'f:Ω→Ω′ is a bijection, conformal on Ω\OmegaΩ, with conformal inverse. A Möbius transformation is z↦(az+b)/(cz+d)z\mapsto(az+b)/(cz+d)z↦(az+b)/(cz+d) with ad−bc≠0ad-bc\neq0ad−bc=0. A closed round disk is the Möbius image of the closed unit disk. A circle domain is a nonempty connected open set whose complementary components are closed round disks or points.

A compact E⊂C^E\subset\widehat{\mathbb C}E⊂C is conformally removable if every orientation-preserving homeomorphism of C^\widehat{\mathbb C}C that is conformal on C^∖E\widehat{\mathbb C}\setminus EC∖E is Möbius. A circle domain Ω\OmegaΩ is conformally rigid if every conformal equivalence from Ω\OmegaΩ onto another circle domain is the restriction of a Möbius transformation.

Formalization targets

Goal: Theorem 1.1

Ω,Ω′ circle domains,  ∂Ω conformally removable,  f:Ω→Ω′ conformal equivalence ⟹ ∃M Mo¨bius: f=M∣Ω.\Omega,\Omega'\ \text{circle domains},\ \ \partial\Omega\ \text{conformally removable},\ \ f:\Omega\to\Omega'\ \text{conformal equivalence}\ \Longrightarrow\ \exists M\ \text{Möbius}:\ f=M|_\Omega.Ω,Ω′ circle domains,  ∂Ω conformally removable,  f:Ω→Ω′ conformal equivalence ⟹ ∃M Mo¨bius: f=M∣Ω​.

Lean: OAI.Problem047.removability_implies_rigidity, open on the platform. The complement may have any cardinality, and no boundary extension of fff is assumed.

Significance

Together with Rajala's counterexample to the converse, the theorem would settle the He–Schramm rigidity conjecture: removability is sufficient but not necessary. It subsumes the earlier sufficient conditions (σ\sigmaσ-finite length, Hölder/John domains, CNED point sets) whenever those boundaries are removable. The intermediate Theorem 5.1, a continuous Sobolev extension theorem across compact totally disconnected conformally removable sets, is of independent interest. The result is claimed in an OpenAI preprint that has not been peer reviewed, and no machine-checked proof exists.

Difficulty

Removability is a statement about homeomorphisms of the whole sphere, while rigidity starts from a map defined only on the domain. The obvious route, extending fff to a homeomorphism of the sphere and then invoking removability, fails: a point component of the complement of Ω\OmegaΩ may correspond to a disk component of Ω′\Omega'Ω′ and vice versa, so the coordinates of fff need not extend continuously, and nothing a priori controls boundary behaviour at uncountably many point components whose union can have positive area.

Formalization scope

  • Sphere := OnePoint ℂ, Möbius maps are Matrix.GeneralLinearGroup (Fin 2) ℂ acting on it; conformality uses the charts zzz and 1/z1/z1/z with HasDerivAt and a nonzero derivative.
  • IsCircleDomain: open, IsConnected, and every connectedComponentIn of the complement is a singleton or a Möbius image of the closed unit disk.
  • IsConformallyRemovable E: IsCompact E and every homeomorphism h : Sphere ≃ₜ Sphere that is homotopic to the identity (orientation preserving) and conformal on Eᶜ equals some Möbius map everywhere.
  • The boundary is frontier U; the conclusion is ∃ M, ∀ p ∈ U, f p = M • p.
  • The shared definitions are those of the Koebe circle-domain mission of the same family.

A complete development needs the theory of conformal maps on the sphere, Sobolev functions and Dirichlet energy in the plane, the measurable Riemann mapping theorem (used for the conductivity deformation), and component correspondence. Contributions formalizing Theorem 5.1 (continuous Sobolev extension), Proposition 6.2 (common point traces), or the He–Schramm countable case are welcome.

Selected references

  • OpenAI, Removable Boundaries and Rigidity of Circle Domains, preprint, September 23, 2026. https://github.com/openai/math/blob/adc7f1241b42e322a6451854ab7e4b4c146bf78a/preprints/Removable-Boundaries-and-Rigidity-of-Circle-Domains-September-23-2026/paper.pdf
  • Z.-X. He, O. Schramm, Fixed points, Koebe uniformization and circle packings, Ann. of Math., 1993. https://doi.org/10.2307/2946541
  • Z.-X. He, O. Schramm, Rigidity of circle domains whose boundary has σ-finite linear measure, Invent. Math., 1994. https://doi.org/10.1007/BF01231761
  • M. Younsi, Removability, rigidity of circle domains and Koebe's conjecture, Adv. Math., 2016. https://doi.org/10.1016/j.aim.2016.08.039
  • D. Ntalampekos, M. Younsi, Rigidity theorems for circle domains, Invent. Math., 2020. https://doi.org/10.1007/s00222-019-00921-1
  • D. Ntalampekos, Rigidity and continuous extension for conformal maps of circle domains, Trans. Amer. Math. Soc., 2023. https://doi.org/10.1090/tran/8923
  • D. Ntalampekos, CNED sets: countably negligible for extremal distances, Selecta Math., 2024. https://doi.org/10.1007/s00029-024-00951-5
  • P. W. Jones, S. K. Smirnov, Removability theorems for Sobolev functions and quasiconformal maps, Ark. Mat., 2000. https://doi.org/10.1007/BF02384320
  • K. Rajala, Rigid circle domains with non-removable boundaries, Proc. Lond. Math. Soc., 2025. https://doi.org/10.1112/plms.70081
  • OpenAI, Koebe's Circle-Domain Conjecture, preprint, September 23, 2026.
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Symmetry of semialgebraic bounded domains with compact quotientResearch Paper

Motivation: which bounded domains cover compact spaces?

A bounded symmetric domain is a bounded connected open set in Cm\mathbb C^mCm with, at every point, a holomorphic involution having that point as an isolated fixed point. Examples are the ball, the polydisc and the Siegel upper half-spaces in their bounded realizations. They are the universal covers of compact locally symmetric varieties, such as compact quotients of the ball, and play a central role in algebraic geometry and number theory. A classical theme in several complex variables is that a bounded domain with a large automorphism group must be very special: Wong and Rosay showed that an automorphism orbit accumulating at a strongly pseudoconvex boundary point forces the ball, and Frankel showed that convex domains with compact quotients are symmetric.

Kollár and Pardon, studying algebraic varieties whose universal cover is semialgebraic, asked the following bounded-domain question: if a bounded semialgebraic open subset of a complex affine variety admits a properly discontinuous cocompact group of biholomorphisms, must it be a bounded symmetric domain? Semialgebraicity is a finiteness condition on the shape of the domain. It does not make the boundary smooth or convex, and it imposes nothing on the group.

Timeline

  • 1970 — Vey proves that a divisible generalized Siegel domain is symmetric (Ann. Sci. ÉNS 3).
  • 1977 — Wong characterizes the ball by its automorphism group among strongly pseudoconvex domains (Invent. Math. 41).
  • 1979 — Rosay localizes Wong's theorem to a single C2C^2C2 strongly pseudoconvex boundary point (Ann. Inst. Fourier 29).
  • 1989 — Frankel proves that a convex hyperbolic domain with compact quotient is a bounded symmetric domain, including non-free actions (Acta Math. 163).
  • 2012 — Kollár and Pardon pose the bounded semialgebraic domain question (arXiv v2, Question 25) in Algebraic varieties with semialgebraic universal cover (J. Topol. 5; arXiv:1104.2309v2).
  • 2021 — Zimmer shows that a C1,1C^{1,1}C1,1-bounded domain covering a compact manifold is a ball (Indiana Univ. Math. J. 70).
  • 2026 — An OpenAI preprint, Symmetry of semialgebraic bounded domains with compact quotient (OpenAI Math Release, September 24, 2026), claims an affirmative answer to the Kollár–Pardon question. It has not been peer reviewed, and its proof is not formally verified.

Setting

An affine variety is a reduced complex algebraic set V⊂CnV\subset\mathbb C^nV⊂Cn, the common zero locus of a set of polynomials. A subset of Cn\mathbb C^nCn is semialgebraic if it is a finite Boolean combination of sets {p=0}\{p=0\}{p=0} and {p>0}\{p>0\}{p>0}, with ppp a real polynomial in the real and imaginary parts of the coordinates. Let U⊆VU\subseteq VU⊆V be open in VVV, connected, semialgebraic and bounded. A map on UUU is holomorphic if near each point it is the restriction of a holomorphic map on an open subset of Cn\mathbb C^nCn; a biholomorphism is a homeomorphism that is holomorphic in both directions. A group Γ\GammaΓ acts properly discontinuously if the action is proper for the discrete topology on Γ\GammaΓ (finite stabilizers are allowed), and the action is cocompact if U/ΓU/\GammaU/Γ is compact. UUU is smooth if each point has a neighbourhood in UUU biholomorphic to an open subset of some Cm\mathbb C^mCm.

Formalization targets

Goal: semialgebraic bounded domains with compact quotient are symmetric (Theorem 1.1)

Let UUU be a nonempty connected semialgebraic bounded open subset of a complex affine variety V⊂CnV\subset\mathbb C^nV⊂Cn, and let a group Γ\GammaΓ act on UUU by biholomorphisms, properly discontinuously and with U/ΓU/\GammaU/Γ compact. Then

U is smooth, andU≅D biholomorphically for some bounded symmetric domain D⊂Cm.U\ \text{is smooth, and}\quad U\cong D\ \text{biholomorphically for some bounded symmetric domain } D\subset\mathbb C^m .U is smooth, andU≅D biholomorphically for some bounded symmetric domain D⊂Cm.

The goal statement is published on the platform with status Open.

Significance

The result itself. The theorem answers the Kollár–Pardon question affirmatively. The ambient variety may be singular and nonnormal, the quotient may have finite quotient singularities, and no convexity, boundary regularity or homogeneity is assumed. It shows that semialgebraicity of a single affine realization forces the classical picture: a compact quotient of a semialgebraic bounded domain is a compact quotient of a bounded symmetric domain. This complements the universal-cover classification of the companion preprint on semialgebraic universal covers of normal projective varieties.

Formalizing it. The statement only uses polynomials, real-analytic Boolean combinations, holomorphic maps on subsets of Cn\mathbb C^nCn and group actions, all available in Mathlib. The proof, however, draws on Nash cell decompositions, analytic discs, scaling limits of automorphisms and Vey's theorem on divisible Siegel domains, none of which is formalized. A formal development would provide reusable semialgebraic geometry and several-complex-variables infrastructure.

Difficulty

The classical rigidity arguments (Wong–Rosay, Frankel, Zimmer) need a smooth strongly pseudoconvex or convex boundary point at which rescaled automorphisms converge to a model domain. A semialgebraic boundary can have corners with several complex-normal directions, and the normal fibres can shrink at rates that depend on tangential parameters, so the naive rescaling limit can collapse to a degenerate set. Moreover UUU is not known to be a manifold at the start, so smoothness must be proved from the group action before any differential geometry is available. The heart of the proof is a noncollapse estimate that yields a Siegel-type quadratic model {Im⁡w−H(z,z)∈C}\{\operatorname{Im}w-H(z,z)\in C\}{Imw−H(z,z)∈C} to which Vey's theorem applies.

Formalization scope

  • VVV is IsAffineAlgebraic, the zero set of a set of complex polynomials in Fin n → ℂ; U⊆VU\subseteq VU⊆V is open in the subspace topology of VVV, IsConnected (hence nonempty), bounded, and semialgebraic through an inductive predicate on real polynomials in (Re⁡z,Im⁡z)(\operatorname{Re}z,\operatorname{Im}z)(Rez,Imz), closed under complement and union.
  • Γ\GammaΓ is an arbitrary group with the discrete topology acting on the subtype UUU, with ProperSMul and a compact orbit space. Each γ\gammaγ acts holomorphically in the sense of local ambient analytic extension; since γ−1\gamma^{-1}γ−1 also acts, the elements act by biholomorphisms. A non-faithful action is allowed and is harmless, since properness forces finite stabilizers.
  • IsSmooth U asks for local biholomorphisms of neighbourhoods in UUU onto open subsets of some Cm\mathbb C^mCm. IsBoundedSymmetricDomain D asks that DDD be open, connected and bounded, and have at each point an involutive biholomorphism fixing it with that point isolated among its fixed points.
  • The zero-dimensional case (a point) is included and is trivial, matching the source convention.
  • Needed infrastructure: semialgebraic cell decomposition and selection, Montel-type compactness on singular analytic sets, analytic discs, Kobayashi/Carathéodory-type distance estimates and the structure theory of Siegel domains. Each would be reusable.

Selected references

  • J. Vey, Sur la division des domaines de Siegel, Ann. Sci. École Norm. Sup. (4) 3 (1970), 479–506. https://www.numdam.org/article/ASENS_1970_4_3_4_479_0.pdf
  • B. Wong, Characterization of the unit ball in Cn\mathbb C^nCn by its automorphism group, Invent. Math. 41 (1977), 253–257. https://doi.org/10.1007/BF01403050
  • J.-P. Rosay, Sur une caractérisation de la boule parmi les domaines de Cn\mathbb C^nCn par son groupe d'automorphismes, Ann. Inst. Fourier 29 (1979), 91–97. https://doi.org/10.5802/aif.768
  • S. Frankel, Complex geometry of convex domains that cover varieties, Acta Math. 163 (1989), 109–149. https://doi.org/10.1007/BF02392734
  • J. Kollár and J. Pardon, Algebraic varieties with semialgebraic universal cover, J. Topol. 5 (2012), 199–212. https://doi.org/10.1112/jtopol/jts001
  • A. Zimmer, Smoothly bounded domains covering compact manifolds, Indiana Univ. Math. J. 70 (2021), 2653–2676. https://arxiv.org/abs/1910.05288v2
  • M. Coste, Real algebraic sets, lecture notes, 2005. https://indico.ictp.it/event/a04204/session/10/contribution/7/material/0/0.pdf
  • OpenAI, Symmetry of semialgebraic bounded domains with compact quotient, OpenAI Math Release preprint, September 24, 2026 (Theorem 1.1, p. 1). https://github.com/openai/math/blob/adc7f1241b42e322a6451854ab7e4b4c146bf78a/preprints/Symmetry-of-semialgebraic-bounded-domains-with-compact-quotient-September-24-2026/paper.pdf
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Integrability of split tangent bundles on rationally connected manifoldsResearch Paper

Motivation: when is a split tangent bundle integrable?

If a complex manifold is a product X1×X2X_1\times X_2X1​×X2​, its tangent bundle splits as the sum of the pulled-back tangent bundles of the factors, and each summand is integrable: the bracket of two local holomorphic vector fields tangent to a summand stays in that summand. Conversely, given a holomorphic decomposition TX=E1⊕E2T_X=E_1\oplus E_2TX​=E1​⊕E2​, one wants to know whether it comes from a product. Integrability of the summands is the necessary local condition, and it can fail: Höring exhibited a non-integrable summand on the product of an abelian surface with P1\mathbb P^1P1 (Höring 2007, Example 2.14). For rationally connected projective manifolds — those in which two general points lie on a rational curve, a class including all Fano manifolds — Höring showed that integrability of one summand already yields a compatible product decomposition, which made automatic integrability the remaining question.

Timeline

  • 2000 — Beauville studies how a tangent splitting of a compact Kähler manifold leads to a product decomposition of its universal cover (Beauville 2000).
  • 2002 — Campana and Peternell treat Fano manifolds with a two-summand splitting when one summand has rank one or two, hence every two-summand splitting of a Fano manifold of dimension at most five (Campana–Peternell 2002, Theorems 3.5–3.6, Corollary 3.7).
  • 2007 — Höring proves that on a rationally connected projective manifold integrability of one summand gives a compatible product (Höring 2007, Theorem 1.4).
  • 2008 — Höring conjectures that at least one summand is integrable and proves it when all summands of a uniruled manifold have rank at most two (Höring 2008, Conjecture 1.2, Lemma 4.21).
  • 2026 — Höring proves integrability with algebraic leaves on Q\mathbb QQ-factorial klt varieties of Fano type, giving actual products in the smooth Fano case, and formulates the smooth rationally connected statement as Conjecture 1.5; a singular rationally connected counterexample shows smoothness matters (Höring 2026).
  • 2026 — An OpenAI preprint, Integrability of split tangent bundles on rationally connected manifolds (OpenAI Math Release, September 23, 2026), claims this conjecture in full: both summands are always integrable. The preprint has not been peer reviewed, and its main theorem is not formally verified.

Setting

A complex manifold XXX of dimension nnn is a Hausdorff, second-countable space with a holomorphic atlas to Cn\mathbb C^nCn. XXX is projective if it admits an injective holomorphic immersion into a complex projective space PN\mathbb P^NPN; for compact XXX this is a closed embedding.

A rational curve in XXX is a holomorphic map P1→X\mathbb P^1\to XP1→X. A compact connected projective manifold is rationally connected if there is a nonempty Zariski-open set U⊆X×XU\subseteq X\times XU⊆X×X such that every pair (x,y)∈U(x,y)\in U(x,y)∈U lies on the image of a rational curve. Here Zariski-open is measured through the projective embedding: UUU is the complement of the common zero set of a family of bihomogeneous polynomials in the two sets of homogeneous coordinates.

A holomorphic splitting TX=E1⊕E2T_X=E_1\oplus E_2TX​=E1​⊕E2​ is given by a holomorphic field of idempotent linear maps PxP_xPx​ on the tangent spaces, with E1=im⁡PE_1=\operatorname{im}PE1​=imP and E2=ker⁡PE_2=\ker PE2​=kerP, both of positive rank at every point. A family of subspaces DDD is integrable if for every open UUU and every pair of holomorphic vector fields V,WV,WV,W on UUU with values in DDD, the Lie bracket [V,W][V,W][V,W] takes values in DDD.

Formalization targets

Goal: Theorem 1.1 (automatic integrability)

Let XXX be a smooth connected projective complex manifold of dimension at least two which is rationally connected. For every holomorphic decomposition TX=E1⊕E2T_X=E_1\oplus E_2TX​=E1​⊕E2​ into subbundles of positive rank,

[Γ(U,E1),Γ(U,E1)]⊆Γ(U,E1)and[Γ(U,E2),Γ(U,E2)]⊆Γ(U,E2)[\Gamma(U,E_1),\Gamma(U,E_1)]\subseteq\Gamma(U,E_1)\quad\text{and}\quad[\Gamma(U,E_2),\Gamma(U,E_2)]\subseteq\Gamma(U,E_2)[Γ(U,E1​),Γ(U,E1​)]⊆Γ(U,E1​)and[Γ(U,E2​),Γ(U,E2​)]⊆Γ(U,E2​)

for every open U⊆XU\subseteq XU⊆X, where Γ(U,Ei)\Gamma(U,E_i)Γ(U,Ei​) denotes holomorphic sections over UUU. The goal statement is published on the platform with status Open: no machine-checked proof exists yet.

Significance

The result itself. The theorem has no rank or positivity hypothesis, and it settles the smooth rationally connected case of Höring's conjecture. Combined with Höring's product theorem it gives Corollary 1.2: every holomorphic splitting of the tangent bundle of a smooth rationally connected projective manifold comes from an isomorphism X≃X1×X2X\simeq X_1\times X_2X≃X1​×X2​ identifying EiE_iEi​ with the factor tangent bundles. It also applies to general fibers of the rationally connected quotient of a uniruled compact Kähler manifold, supplying the integrability premise in Höring's structure theorems (Corollary 5.1). Together with the companion preprint on universal-cover splitting for compact Kähler manifolds, it covers both the integrability question and the global product question.

Formalizing it. The statement involves projective embeddings, Zariski-open sets of pairs, rational curves and holomorphic distributions, all expressed from first principles over Mathlib's manifold library. A machine-checked proof would certify a classical-looking but new geometric argument; the compatible product (Corollary 1.2) is not part of this goal.

Difficulty

The bracket of two sections of E1E_1E1​, projected to E2E_2E2​, is a tensor ⋀2E1→E2\bigwedge^2E_1\to E_2⋀2E1​→E2​, and the task is to show it vanishes. The natural approach is to restrict to rational curves and use positivity, as in the Fano and low-rank cases, but without positivity or rank assumptions the restricted bundles can have summands of either sign and no vanishing follows directly. Smoothness cannot be dropped: a singular rationally connected example with a non-integrable summand exists (Höring 2026, Example 4.3), so the argument must use the manifold structure in an essential way. Rational connectedness is also needed: Höring's example on an abelian surface times P1\mathbb P^1P1 is a smooth projective manifold with a non-integrable summand.

Formalization scope

  • ComplexManifold carries its dimension, a Hausdorff second-countable topology, and an analytic (ω) atlas modeled on Fin dim → ℂ. The theorem assumes ConnectedSpace, CompactSpace and 2 ≤ X.dim.
  • ProjectiveEmbedding X is an injective map to ℙ ℂ (Fin (N+1) → ℂ) that is holomorphic and immersive in every affine patch.
  • RationalCurve X is a holomorphic map from P1\mathbb P^1P1 given by two holomorphic maps C→X\mathbb C\to XC→X agreeing via z↦z−1z\mapsto z^{-1}z↦z−1; RationallyConnected e asks for a nonempty, dense, Zariski-open set of pairs (bihomogeneous polynomial complement) all joined by rational curves. Density is automatic for a nonempty Zariski-open subset of the irreducible variety X×XX\times XX×X, so stating it does not narrow the class.
  • TangentSplitting X is a holomorphic idempotent field on the tangent bundle with range and kernel of positive rank at every point. Integrable uses VectorField.mlieBracketWithin for sections that are holomorphic on an open set.
  • The conclusion asserts integrability of both the range and the kernel; the compatible product of Corollary 1.2 is not asserted.
  • Infrastructure needed: holomorphic maps from P1×P1\mathbb P^1\times\mathbb P^1P1×P1, resolution of indeterminacy for rational maps of surfaces, holomorphic bundles on P1\mathbb P^1P1, families of rational curves. The splitting and integrability definitions are reusable for the companion universal-cover mission.

Selected references

  • A. Beauville, Complex manifolds with split tangent bundle, in Complex Analysis and Algebraic Geometry (de Gruyter, 2000), 61–70. https://arxiv.org/abs/math/9809033v2
  • F. Campana, T. Peternell, Projective manifolds with splitting tangent bundle, I, Math. Z. 241 (2002), 613–637. https://doi.org/10.1007/s00209-002-0435-5
  • A. Höring, Uniruled varieties with split tangent bundle, Math. Z. 256 (2007), 465–479. https://arxiv.org/abs/math/0505327v3
  • A. Höring, The structure of uniruled manifolds with split tangent bundle, Osaka J. Math. 45 (2008), 1067–1084. https://www.i-repository.net/contents/osakacu/sugaku/111F0000002-04504-14.pdf
  • A. Höring, Fano varieties with split tangent sheaf, preprint (2026). https://arxiv.org/abs/2602.15427v1
  • J. Kollár, Y. Miyaoka, S. Mori, Rationally connected varieties, J. Algebraic Geom. 1 (1992), 429–448.
  • OpenAI, Integrability of split tangent bundles on rationally connected manifolds, OpenAI Math Release preprint, September 23, 2026 (source of the goal; Theorem 1.1, p. 1). https://github.com/openai/math/blob/adc7f1241b42e322a6451854ab7e4b4c146bf78a/preprints/Integrability-of-split-tangent-bundles-on-rationally-connected-manifolds-September-23-2026/main.pdf
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Algebraic GeometryDifferential Geometry·Captain: wurtle

Universal-cover splitting for compact Kähler manifoldsResearch Paper

Motivation: when does a split tangent bundle come from a product?

If a complex manifold is a product Y1×Y2Y_1\times Y_2Y1​×Y2​, its holomorphic tangent bundle is the direct sum of the tangent bundles of the factors. The converse question asks when a given holomorphic decomposition TX=E1⊕E2T_X=E_1\oplus E_2TX​=E1​⊕E2​ of the tangent bundle of a compact manifold XXX comes from a product decomposition of its universal cover, with the product realizing the specified summands rather than some other splitting. This is the complex-analytic counterpart of the de Rham decomposition theorem for Riemannian manifolds with parallel complementary distributions (de Rham 1952), but a holomorphic splitting supplies no complete metric making the distributions parallel, so de Rham's argument does not apply. The question sits between foliation theory, Kähler geometry and the classification of projective manifolds with split tangent bundle.

Timeline

  • 1952 — de Rham: a complete Riemannian manifold with parallel complementary orthogonal distributions has universal cover isometric to a product (de Rham 1952).
  • 1993 — Yau proves a splitting theorem for Kähler–Einstein manifolds (Yau, Comm. Anal. Geom. 1 (1993)).
  • 2000 — Beauville formulates the compatible universal-cover conjecture for compact Kähler manifolds whose tangent summands have integrable partial sums, and proves it for Kähler–Einstein manifolds and compact Kähler surfaces (Beauville 2000, Section 2.3, Theorems A and C). Druel treats projective manifolds whose tangent bundle is a sum of line bundles (Druel 2000).
  • 2006 — Brunella, Pereira and Touzet settle the case of a line summand with integrable complement on compact Kähler manifolds (BPT 2006).
  • 2007 — Höring proves automatic integrability for split tangent bundles on non-uniruled projective manifolds (Höring 2007).
  • 2013–2024 — Pereira–Touzet obtain a compatible Euclidean factor when one involutive summand is Hermitian flat (PT 2013); Druel, Pereira, Pym and Touzet handle a foliation with a compact leaf with finite holonomy (DPPT 2022) and numerically flat regular foliations (DPPT 2024).
  • 2026 — Höring proves algebraic integrability for tangent summands on klt Fano-type varieties (Höring 2026). An OpenAI preprint, Universal-cover splitting for compact Kähler manifolds (OpenAI Math Release, September 23, 2026), claims the two-summand case of Beauville's conjecture in arbitrary positive ranks. The preprint has not been peer reviewed, and its main theorem is not formally verified.

Setting

A complex manifold XXX of dimension nnn is a Hausdorff, second-countable space with holomorphic charts to Cn\mathbb C^nCn. A Kähler metric is a smooth Riemannian metric ggg on the real tangent bundle that is Hermitian (g(Ju,Jv)=g(u,v)g(Ju,Jv)=g(u,v)g(Ju,Jv)=g(u,v) for multiplication JJJ by iii) and whose fundamental form ω(u,v)=g(Ju,v)\omega(u,v)=g(Ju,v)ω(u,v)=g(Ju,v) is closed.

A holomorphic splitting of TXT_XTX​ with ranks r1,r2r_1,r_2r1​,r2​ is given by a field PPP of C\mathbb CC-linear idempotents Px:TxX→TxXP_x:T_xX\to T_xXPx​:Tx​X→Tx​X, holomorphic in charts, with rank⁡Px=r1\operatorname{rank}P_x=r_1rankPx​=r1​ and dim⁡ker⁡Px=r2\dim\ker P_x=r_2dimkerPx​=r2​; then E1=im⁡PE_1=\operatorname{im}PE1​=imP, E2=ker⁡PE_2=\ker PE2​=kerP and TX=E1⊕E2T_X=E_1\oplus E_2TX​=E1​⊕E2​. A subbundle is integrable if its local holomorphic sections are closed under the Lie bracket. The ordinary universal cover π:X~→X\pi:\widetilde X\to Xπ:X→X is a connected, simply connected covering space carrying the lifted complex structure.

Formalization targets

Goal: Theorem 1.1 (compatible universal-cover splitting)

Let XXX be a compact connected Kähler manifold of complex dimension n≥2n\ge2n≥2 and TX=E1⊕E2T_X=E_1\oplus E_2TX​=E1​⊕E2​ a holomorphic splitting into integrable subbundles of positive ranks r1,r2r_1,r_2r1​,r2​. Then there are connected, simply connected complex manifolds Y1,Y2Y_1,Y_2Y1​,Y2​ with dim⁡CYi=ri\dim_{\mathbb C}Y_i=r_idimC​Yi​=ri​ and a biholomorphism Φ:X~→Y1×Y2\Phi:\widetilde X\to Y_1\times Y_2Φ:X→Y1​×Y2​ with

dΦ(π∗E1)=pr1∗TY1,dΦ(π∗E2)=pr2∗TY2.d\Phi\big(\pi^*E_1\big)=\mathrm{pr}_1^*T_{Y_1},\qquad d\Phi\big(\pi^*E_2\big)=\mathrm{pr}_2^*T_{Y_2}.dΦ(π∗E1​)=pr1∗​TY1​​,dΦ(π∗E2​)=pr2∗​TY2​​.

The goal statement is published on the platform with status Open: no machine-checked proof exists yet.

Significance

The result itself. The theorem proves the two-summand form of Beauville's conjecture with no flatness, compact-leaf or line-bundle assumption: integrability of both summands and a Kähler metric on a compact manifold suffice. Combined with Höring's integrability theorem it gives compatible product decompositions for every split tangent bundle on a non-uniruled projective manifold (Corollary 1.2), and for projective manifolds with nef and big canonical bundle (Corollary 1.3). With the companion preprint on rationally connected manifolds it also covers split tangent bundles there. The factors may be noncompact, and the conclusion concerns the universal cover, not a finite cover.

Formalizing it. The statement involves universal covers, Kähler forms, holomorphic distributions and biholomorphisms of products, all of which must be expressed with Mathlib's manifold library. A machine-checked proof would certify a global continuation argument (Hartogs-type extension, boundary crossing, path rectangles and monodromy) for which no prior formal treatment exists.

Difficulty

Integrability alone gives, by holomorphic Frobenius, local product coordinates. The obvious strategy is to continue these local products along paths and use simple connectivity of X~\widetilde XX. This fails because a path in one foliation need not be transportable along a path in the other: local product charts can break down, and leaves can be noncompact and dense. Compactness makes every metric complete, but does not make the foliations parallel, so the de Rham argument is unavailable. Beauville's example on A×P1A\times\mathbb P^1A×P1 (AAA an abelian surface) shows that even when XXX is a product, a non-integrable complementary summand need not be realized by any product structure, so both integrability hypotheses are needed.

Formalization scope

  • ComplexManifold n bundles a Hausdorff, second-countable type with an atlas modeled on Fin n → ℂ that is smooth for 𝓘(ℂ, Fin n → ℂ), i.e. holomorphic transition maps.
  • KahlerMetric X is a real bilinear form on each tangent space that is symmetric, positive definite, invariant under multiplication by Complex.I, smooth in every chart, and whose fundamental form is closed (the cyclic sum of its chart derivatives vanishes).
  • HolomorphicSplitting X r₁ r₂ is a field of idempotent continuous ℂ-linear maps, holomorphic in charts, with range of rank r1r_1r1​ and kernel of rank r2r_2r2​. Integrable P says that chart-local holomorphic vector fields with values in the range of PPP have bracket in the range of PPP; both S.projection and the complementary projection are assumed integrable.
  • OrdinaryUniversalCover X Z is a covering map from a connected, simply connected complex manifold ZZZ that is a local biholomorphism.
  • CompatibleProduct asks for a homeomorphism Φ:Z→Y1×Y2\Phi:Z\to Y_1\times Y_2Φ:Z→Y1​×Y2​, holomorphic with holomorphic inverse, whose differential sends the pullback of E1E_1E1​ onto ker⁡(snd)\ker(\mathrm{snd})ker(snd) and the pullback of E2E_2E2​ onto ker⁡(fst)\ker(\mathrm{fst})ker(fst).
  • Hypotheses: XXX compact and connected, n≥2n\ge2n≥2, r1,r2>0r_1,r_2>0r1​,r2​>0. A rank-zero summand would make the statement trivial and is excluded, as in the source.
  • Infrastructure needed: holomorphic Frobenius, foliation leaves, meromorphic Hartogs extension, Stokes' theorem for Kähler forms, monodromy for covering spaces. The Kähler-metric and splitting definitions are reusable for the companion integrability mission.

Selected references

  • G. de Rham, Sur la réductibilité d'un espace de Riemann, Comment. Math. Helv. 26 (1952), 328–344. https://doi.org/10.1007/BF02564308
  • S.-T. Yau, A splitting theorem and an algebraic geometric characterization of locally Hermitian symmetric spaces, Comm. Anal. Geom. 1 (1993), 473–486.
  • A. Beauville, Complex manifolds with split tangent bundle, in Complex Analysis and Algebraic Geometry (de Gruyter, 2000), 61–70. https://doi.org/10.1515/9783110806090-004
  • S. Druel, Variétés algébriques dont le fibré tangent est totalement décomposé, J. Reine Angew. Math. 522 (2000), 161–171. https://arxiv.org/abs/math/9901138v2
  • M. Brunella, J. V. Pereira, F. Touzet, Kähler manifolds with split tangent bundle, Bull. Soc. Math. France 134 (2006), 241–252. https://doi.org/10.24033/bsmf.2507
  • A. Höring, Uniruled varieties with split tangent bundle, Math. Z. 256 (2007), 465–479. https://doi.org/10.1007/s00209-006-0072-5
  • J. V. Pereira, F. Touzet, Foliations with vanishing Chern classes, Bull. Braz. Math. Soc. 44 (2013), 731–754. https://arxiv.org/abs/1210.5916v1
  • S. Druel, J. V. Pereira, B. Pym, F. Touzet, A global Weinstein splitting theorem for holomorphic Poisson manifolds, Geom. Topol. 26 (2022), 2831–2853. https://doi.org/10.2140/gt.2022.26.2831
  • S. Druel, J. V. Pereira, B. Pym, F. Touzet, Numerically flat foliations and holomorphic Poisson geometry, preprint (2024). https://arxiv.org/abs/2411.08806v1
  • A. Höring, Fano varieties with split tangent sheaf, preprint (2026). https://arxiv.org/abs/2602.15427v1
  • OpenAI, Universal-cover splitting for compact Kähler manifolds, OpenAI Math Release preprint, September 23, 2026 (source of the goal; Theorem 1.1, p. 3). https://github.com/openai/math/blob/adc7f1241b42e322a6451854ab7e4b4c146bf78a/preprints/Universal-cover-splitting-for-compact-Kahler-manifolds-September-23-2026/paper.pdf
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AlgebraAlgebraic Geometry·Captain: wurtle

An explicit failure of complex affine-space cancellationResearch Paper

Motivation

Zariski's cancellation problem asks whether affine space can be recognized from its cylinder: if a variety XXX satisfies X×A1≅An+1X\times\mathbb A^1\cong\mathbb A^{n+1}X×A1≅An+1, must X≅AnX\cong\mathbb A^nX≅An? Algebraically, for a finitely generated commutative C\mathbb CC-algebra AAA and an independent variable www,

A[w]≅C[n+1] ⟹? A≅C[n],A[w]\cong\mathbb C^{[n+1]}\ \overset{?}{\Longrightarrow}\ A\cong\mathbb C^{[n]},A[w]≅C[n+1] ⟹?​ A≅C[n],

where C[r]\mathbb C^{[r]}C[r] is a polynomial ring in rrr variables and all isomorphisms are C\mathbb CC-algebra isomorphisms. The problem is one of the central questions of affine algebraic geometry, closely tied to the recognition of affine space, coordinates of polynomial rings, and polynomial fibrations.

Background

  • 1972. Abhyankar, Heinzer and Eakin prove cancellation for the affine line (doi:10.1016/0021-8693(72)90134-2).
  • 1974. Dolgachev and Weisfeiler formulate the affine-fibration conjecture (doi:10.1070/IM1974v008n04ABEH002127).
  • 1979–1980. Fujita, and Miyanishi and Sugie, prove cancellation for the complex affine plane (doi:10.3792/pjaa.55.106, doi:10.1215/kjm/1250522319).
  • 1987. Asanuma constructs, in positive characteristic, threefolds whose cylinders are affine four-space (doi:10.1007/BF01389155).
  • 1996. Makar-Limanov uses additive group actions to show that the Russell cubic is not C3\mathbb C^3C3 (doi:10.1007/BF02937314).
  • 2014. Gupta proves failure of cancellation in every dimension ≥3\ge3≥3 over every field of positive characteristic (doi:10.1007/s00222-013-0455-2, doi:10.1016/j.aim.2014.07.012).
  • 2018–2021. El Kahoui–Ouali and Dutta–Lahiri prove that residual coordinates are one-stably coordinates (doi:10.1216/JCA-2018-10-3-317, doi:10.1016/j.jpaa.2021.106707).
  • 2026. Gaifullin and Petrov still list the characteristic-zero problem in dimension ≥3\ge3≥3 as unresolved (arXiv:2607.13593).

The source of this mission is an OpenAI preprint dated September 23, 2026.

Setting

Let p,s,u,F,Jp,s,u,F,Jp,s,u,F,J be independent variables over C\mathbb CC and P=C[p,s,u,F,J]P=\mathbb C[p,s,u,F,J]P=C[p,s,u,F,J]. Put

x=s2+u3+p2F,H=x2F−(1+2sx)J−p2J2−pu,A=P/(H).x=s^2+u^3+p^2F,\qquad H=x^2F-(1+2sx)J-p^2J^2-pu,\qquad A=P/(H).x=s2+u3+p2F,H=x2F−(1+2sx)J−p2J2−pu,A=P/(H).

So AAA is the coordinate ring of the hypersurface {H=0}⊂A5\{H=0\}\subset\mathbb A^5{H=0}⊂A5. For a C\mathbb CC-algebra AAA, A[w]A[w]A[w] denotes the polynomial ring in one further variable, and C[r]\mathbb C^{[r]}C[r] the polynomial ring in rrr variables.

Formalization targets

Goal: Theorem 1.1

A is a finitely generated integral domain of Krull dimension 4,A[w]≅CC[5],A̸≅CC[4].A\ \text{is a finitely generated integral domain of Krull dimension }4,\qquad A[w]\cong_{\mathbb C}\mathbb C^{[5]},\qquad A\not\cong_{\mathbb C}\mathbb C^{[4]}.A is a finitely generated integral domain of Krull dimension 4,A[w]≅C​C[5],A≅C​C[4].

The Lean statement OAI.ComplexCancellation.main is open on the platform.

Significance

Theorem 1.1 gives a negative answer to Zariski's cancellation problem over C\mathbb CC in dimension four, with an explicit counterexample of degree small enough to write in one line. The same polynomial yields two further consequences proved in the paper: HHH is a coordinate of P[w]P[w]P[w] but not of PPP, so the Stable Coordinate Conjecture fails in ambient dimension five (Corollary 1.2); and the maps p:Spec⁡A→A1p:\operatorname{Spec}A\to\mathbb A^1p:SpecA→A1 and (p,H):A5→A2(p,H):\mathbb A^5\to\mathbb A^2(p,H):A5→A2 are smooth A3\mathbb A^3A3-fibrations that are not Zariski-locally trivial, disproving the Dolgachev–Weisfeiler conjecture over these bases (Corollary 7.1). Cancellation in dimension three over C\mathbb CC is not addressed.

The result is proved in an OpenAI preprint, which has not been peer reviewed. No machine-checked proof exists.

Difficulty

The cylinder isomorphism A[w]≅C[5]A[w]\cong\mathbb C^{[5]}A[w]≅C[5] is comparatively explicit: a locally nilpotent derivation sends HHH to p3p^3p3, and exponentiating converts HHH into H+p3wH+p^3wH+p3w. The hard part is proving A≇C[4]A\not\cong\mathbb C^{[4]}A≅C[4]. Standard invariants do not help: AAA is smooth, factorial-type obstructions vanish, and topologically Spec⁡A\operatorname{Spec}ASpecA is contractible like C4\mathbb C^4C4 since its cylinder is C5\mathbb C^5C5. The paper uses additive group actions (locally nilpotent derivations), passing to an associated graded algebra along p=0p=0p=0, lifting actions through a line bundle over a smooth affine quadric, and a rigidity argument based on the Mason–Stothers polynomial abc inequality.

Formalization scope

  • P := MvPolynomial (Fin 5) ℂ with p, s, u, F, J := X 0, …, X 4; x and H are transcribed literally; A := P ⧸ Ideal.span {H}.
  • Dimension is ringKrullDim A = 4; integrality is IsDomain A; finite generation is Algebra.FiniteType ℂ A.
  • The cylinder statement is Nonempty (Polynomial A ≃ₐ[ℂ] MvPolynomial (Fin 5) ℂ); the non-polynomiality is ¬ Nonempty (A ≃ₐ[ℂ] MvPolynomial (Fin 4) ℂ). All isomorphisms are C\mathbb CC-algebra isomorphisms.

A complete development needs: explicit polynomial automorphisms (for the cylinder), Krull dimension of hypersurface quotients, locally nilpotent derivations and their kernels, filtrations and associated graded rings, and the Mason–Stothers theorem for polynomials. Contributions formalizing Proposition 2.2, Proposition 3.4 (the graded identification), Propositions 4.1–4.3, Lemma 5.1 (order of a locally nilpotent derivation), Lemma 6.1 (Mason–Stothers) and Proposition 6.3 are welcome.

Selected references

  • OpenAI, An explicit failure of complex affine-space cancellation, preprint, September 23, 2026. https://github.com/openai/math/blob/adc7f1241b42e322a6451854ab7e4b4c146bf78a/preprints/An-explicit-failure-of-complex-affine-space-cancellation-September-23-2026/paper.pdf
  • N. Gupta, On Zariski's cancellation problem in positive characteristic, Adv. Math., 2014. https://doi.org/10.1016/j.aim.2014.07.012
  • N. Gupta, On the cancellation problem for the affine space A3\mathbb A^3A3 in characteristic ppp, Invent. Math., 2014. https://doi.org/10.1007/s00222-013-0455-2
  • S. S. Abhyankar, W. Heinzer, P. Eakin, On the uniqueness of the coefficient ring in a polynomial ring, J. Algebra, 1972. https://doi.org/10.1016/0021-8693(72)90134-2
  • T. Fujita, On Zariski problem, Proc. Japan Acad. Ser. A, 1979. https://doi.org/10.3792/pjaa.55.106
  • L. Makar-Limanov, On the hypersurface x+x2y+z2+t3=0x+x^2y+z^2+t^3=0x+x2y+z2+t3=0 in C4\mathbb C^4C4 or a C3\mathbb C^3C3-like threefold which is not C3\mathbb C^3C3, Israel J. Math., 1996. https://doi.org/10.1007/BF02937314
  • A. K. Dutta, A. Lahiri, On residual and stable coordinates, J. Pure Appl. Algebra, 2021. https://doi.org/10.1016/j.jpaa.2021.106707
  • M. El Kahoui, M. Ouali, A note on residual coordinates of polynomial rings, J. Commut. Algebra, 2018. https://doi.org/10.1216/JCA-2018-10-3-317
  • B. Yu. Weisfeiler, I. V. Dolgachev, Unipotent group schemes over integral rings, Math. USSR-Izv., 1974. https://doi.org/10.1070/IM1974v008n04ABEH002127
  • S. Gaifullin, M. Petrov, Non-cancellative varieties, maximal tori, and the Makar-Limanov invariant, preprint, 2026. https://arxiv.org/abs/2607.13593
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Number Theory·Captain: wurtle

Positive lower density of large prime gapsResearch Paper

Motivation

Let pnp_npn​ be the nnn-th prime and dn=pn+1−pnd_n=p_{n+1}-p_ndn​=pn+1​−pn​ the nnn-th gap. By the prime number theorem the average gap near ppp is about log⁡p\log plogp. A great deal is known about how large individual gaps can be, but much less about how often large gaps occur. A natural question is whether, for each fixed CCC, a positive proportion of all gaps exceed Clog⁡pnC\log p_nClogpn​. Erdős and Prachar (1962) asked a closely related question about the sequence pn/np_n/npn​/n: do the indices where it increases have positive lower density?

Background

  • 1931. Westzynthius proves that dn/log⁡pnd_n/\log p_ndn​/logpn​ is unbounded.
  • 1935, 1938. Erdős and Rankin construct quantitatively larger gaps (doi:10.1093/qmath/os-6.1.124, doi:10.1112/jlms/s1-13.4.242).
  • 1962. Erdős and Prachar ask whether the indices with pn/n<pn+1/(n+1)p_n/n<p_{n+1}/(n+1)pn​/n<pn+1​/(n+1) have positive lower density (doi:10.1007/BF02992930).
  • 1965. Bombieri and A. I. Vinogradov prove the distribution theorem for primes in progressions on average (doi:10.1112/S0025579300005313).
  • 1976. Gallagher derives Poisson statistics for primes in short intervals from a uniform Hardy–Littlewood hypothesis (doi:10.1112/S0025579300016442).
  • 2005, 2015. Goldston–Yıldırım's divisor-sum correlations and Maynard's multidimensional sieve give the weight technology later used for gaps (arXiv:math/0504336, doi:10.4007/annals.2015.181.1.7).
  • 2010. Bazzanella, Languasco and Zaccagnini obtain positive proportions of prime-start intervals for thresholds below 0.5790.5790.579, and distinguish counting gaps from counting interval starts (doi:10.1090/S0002-9947-09-05009-0).
  • 2016, 2018. Ford, Green, Konyagin and Tao, and Maynard, independently improve the Erdős–Rankin bound; their joint work follows (doi:10.4007/annals.2016.183.3.4, doi:10.4007/annals.2016.183.3.3, doi:10.1090/jams/876).

The source of this mission is an OpenAI preprint dated September 25, 2026.

Setting

  • p1=2<p2=3<⋯p_1=2<p_2=3<\cdotsp1​=2<p2​=3<⋯ are the primes in order, and dn=pn+1−pnd_n=p_{n+1}-p_ndn​=pn+1​−pn​.
  • For A⊆{1,2,… }A\subseteq\{1,2,\dots\}A⊆{1,2,…}, the lower asymptotic density is d‾(A)=lim inf⁡N→∞∣A∩[1,N]∣/N\underline d(A)=\liminf_{N\to\infty}|A\cap[1,N]|/Nd​(A)=liminfN→∞​∣A∩[1,N]∣/N.
  • All logarithms are natural.

Formalization targets

Goal: Theorem 1.1 and Corollary 1.2

For every fixed real C>0C>0C>0 there are c(C)>0c(C)>0c(C)>0 and N0(C)N_0(C)N0​(C) with

#{1≤n≤N: pn+1−pn>Clog⁡pn} ≥ c(C) N(N≥N0(C)),\#\{1\le n\le N:\ p_{n+1}-p_n>C\log p_n\}\ \ge\ c(C)\,N\qquad(N\ge N_0(C)),#{1≤n≤N: pn+1​−pn​>Clogpn​} ≥ c(C)N(N≥N0​(C)),

and

d‾({n≥1: pnn<pn+1n+1})>0.\underline d\Bigl(\Bigl\{n\ge1:\ \frac{p_n}{n}<\frac{p_{n+1}}{n+1}\Bigr\}\Bigr)>0.d​({n≥1: npn​​<n+1pn+1​​})>0.

The Lean statement OAI.Problem344.large_gaps_and_ratio_density is the conjunction of these two claims and is open on the platform.

Significance

Theorem 1.1 says that gaps of size Clog⁡pC\log pClogp are not rare for any fixed CCC: they occupy a positive proportion of the indices up to every large NNN. This is a statement about the frequency of large gaps, not about the size of the largest one, and it does not follow from the Erdős–Rankin or Ford–Green–Konyagin–Maynard–Tao constructions. Corollary 1.2 answers the Erdős–Prachar question: since pn/n<pn+1/(n+1)p_n/n<p_{n+1}/(n+1)pn​/n<pn+1​/(n+1) is equivalent to dn>pn/n∼log⁡pnd_n>p_n/n\sim\log p_ndn​>pn​/n∼logpn​, it follows from Theorem 1.1 with C=2C=2C=2. The constants are not made explicit.

The result is proved in an OpenAI preprint, which has not been peer reviewed. No machine-checked proof exists.

Difficulty

Counting gaps differs from counting empty intervals: a single very long gap contains many starting points of prime-free intervals, so a positive proportion of empty intervals can come from a sparse set of gaps. Results of the latter kind (Bazzanella–Languasco–Zaccagnini, Tao's empty-interval argument) therefore do not give gap counts. The proof needs a sieve weight that makes a prime in (m,m+h](m,m+h](m,m+h] likely while making (m+h,m+2h](m+h,m+2h](m+h,m+2h] almost surely prime-free, and then a multiplicity argument (the last prime before the empty interval is selected by at most hhh values of mmm) to convert weighted interval mass into a count of distinct gaps. Making the second interval nearly empty requires an alternating family of divisor-sum squares whose adjacent dimensions nearly cancel.

Formalization scope

  • prime n = Nat.nth Nat.Prime (n - 1), so prime 1 = 2; largeGapIndices C N filters Finset.Icc 1 N by C * log (prime n) < prime (n+1) - prime n in ℝ.
  • lowerAsymptoticDensity A = sSup {d | ∃ N0, ∀ N ≥ N0, d ≤ initialCount A N / N}, which equals the liminf because the ratios lie in [0,1][0,1][0,1].
  • ratioIncreaseIndices = {n | 1 ≤ n ∧ prime n / n < prime (n+1) / (n+1)} in ℝ.
  • The first clause quantifies over all real C>0C>0C>0, with ccc and N0N_0N0​ depending on CCC.

A complete development needs the prime number theorem, the Bombieri–Vinogradov theorem, smooth Goldston–Yıldırım/Maynard divisor-sum correlations, and averages of the Hardy–Littlewood singular series. These are widely reusable. Contributions formalizing Proposition 2.1 (weights for adjacent intervals), Proposition 3.1 (moment identities and a detector bound), Proposition 4.2 (cancellation between high dimensions), Proposition 5.1 (uniform mixed moments) and Lemma 5.4 (singular series in boxes) are welcome.

Selected references

  • OpenAI, Positive lower density of large prime gaps, preprint, September 25, 2026. https://github.com/openai/math/blob/adc7f1241b42e322a6451854ab7e4b4c146bf78a/preprints/Positive-lower-density-of-large-prime-gaps-September-25-2026/main.pdf
  • P. Erdős, K. Prachar, Sätze und Probleme über pk/kp_k/kpk​/k, Abh. Math. Sem. Univ. Hamburg, 1962. https://doi.org/10.1007/BF02992930
  • D. Bazzanella, A. Languasco, A. Zaccagnini, Prime numbers in logarithmic intervals, Trans. Amer. Math. Soc., 2010. https://doi.org/10.1090/S0002-9947-09-05009-0
  • J. Maynard, Small gaps between primes, Ann. of Math., 2015. https://doi.org/10.4007/annals.2015.181.1.7
  • D. A. Goldston, C. Y. Yıldırım, Small gaps between primes I, preprint, 2005. https://arxiv.org/abs/math/0504336
  • K. Ford, B. Green, S. Konyagin, J. Maynard, T. Tao, Long gaps between primes, J. Amer. Math. Soc., 2018. https://doi.org/10.1090/jams/876
  • P. X. Gallagher, On the distribution of primes in short intervals, Mathematika, 1976. https://doi.org/10.1112/S0025579300016442
  • E. Bombieri, On the large sieve, Mathematika, 1965. https://doi.org/10.1112/S0025579300005313
  • R. A. Rankin, The difference between consecutive prime numbers, J. London Math. Soc., 1938. https://doi.org/10.1112/jlms/s1-13.4.242
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Number Theory·Captain: wurtle

Squarefree values of quartics and power-free values of polynomialsResearch Paper

Motivation: when is a polynomial value free of high powers?

An integer aaa is kkk-power-free if no prime power pkp^kpk divides it (zero is never kkk-power-free). For a fixed integer polynomial fff one expects f(n)f(n)f(n) to be kkk-power-free for a positive proportion of integers nnn, given by an Euler product of local densities, as soon as no prime kkkth power divides every value of fff. The heuristic is a sieve: discard the nnn with pk∣f(n)p^k\mid f(n)pk∣f(n) for each prime ppp. Small primes are handled by the Chinese remainder theorem; the problem lies with primes ppp larger than the range of nnn, where f(n)f(n)f(n) can be divisible by pkp^kpk only if it has an unusually large square-full part. The case k=d−2k=d-2k=d−2, where d=deg⁡fd=\deg fd=degf, is the first exponent left open by classical methods. Its best-known instance is the squarefreeness of n4+2n^4+2n4+2, singled out by Erdős in 1953 and again in his 1965 survey.

Timeline

  • 1933 — Ricci proves the density asymptotic when k≥dk\ge dk≥d (Rend. Circ. Mat. Palermo 57).
  • 1953 — Erdős proves infinitely many (d−1)(d-1)(d−1)-power-free values for d≥3d\ge3d≥3 and singles out the unresolved squarefreeness of n4+2n^4+2n4+2 (J. London Math. Soc.).
  • 1967 — Hooley obtains the asymptotic at exponent k=d−1k=d-1k=d−1 (Mathematika 14).
  • 1976 — Nair proves the asymptotic for k≥(2−12)dk\ge(\sqrt2-\tfrac12)dk≥(2​−21​)d, which reaches k=d−2k=d-2k=d−2 for d≥24d\ge24d≥24 (Mathematika 23).
  • 1998 — Granville shows that the abcabcabc conjecture implies the predicted squarefree density for every separable polynomial without a fixed square divisor (IMRN 1998).
  • 2006 — Heath-Brown's affine determinant method gives k≥(3d+2)/4k\ge(3d+2)/4k≥(3d+2)/4, reaching k=d−2k=d-2k=d−2 for d≥10d\ge10d≥10.
  • 2011 — Browning, combining this with Salberger's global determinant method, reaches k≥(3d+1)/4k\ge(3d+1)/4k≥(3d+1)/4, hence k=d−2k=d-2k=d−2 for d≥9d\ge9d≥9 (Arch. Math. 96); Xiao gives a published reproof (IMRN 2017).
  • 2013–2015 — Heath-Brown treats binomials xd+cx^d+cxd+c for k≥(5d+3)/9k\ge(5d+3)/9k≥(5d+3)/9 (Q. J. Math. 64); Reuss obtains a power-saving error at k=d−1k=d-1k=d−1 (Bull. LMS 47).
  • 2026 — An OpenAI preprint, Squarefree values of quartics and power-free values of polynomials (OpenAI Math Release, September 24, 2026), claims the case k=d−2k=d-2k=d−2 for all degrees 4≤d≤84\le d\le 84≤d≤8, including squarefree values of every admissible irreducible quartic. It has not been peer reviewed, and its proof is not formally verified.

Setting

Let f∈Z[x]f\in\mathbb Z[x]f∈Z[x] be irreducible over Q\mathbb QQ, of degree ddd, and let k≥2k\ge2k≥2. Define

ρf(q)=#{a∈Z/qZ: f(a)≡0(modq)},Sf,k(X)=#{1≤n≤X: f(n) is k-power-free}.\rho_f(q)=\#\{a\in\mathbb Z/q\mathbb Z:\ f(a)\equiv0\pmod q\},\qquad S_{f,k}(X)=\#\{1\le n\le X:\ f(n)\text{ is $k$-power-free}\}.ρf​(q)=#{a∈Z/qZ: f(a)≡0(modq)},Sf,k​(X)=#{1≤n≤X: f(n) is k-power-free}.

The local admissibility condition is ρf(pk)<pk\rho_f(p^k)<p^kρf​(pk)<pk for every prime ppp: no prime kkkth power divides all values of fff. The predicted density is

cf,k=∏p(1−ρf(pk)pk).c_{f,k}=\prod_p\Bigl(1-\frac{\rho_f(p^k)}{p^k}\Bigr).cf,k​=p∏​(1−pkρf​(pk)​).

Formalization targets

Goal: power-free values at exponent d−2d-2d−2 in every degree d≥4d\ge4d≥4 (Corollary 1.2)

Let f∈Z[x]f\in\mathbb Z[x]f∈Z[x] be irreducible over Q\mathbb QQ with d=deg⁡f≥4d=\deg f\ge4d=degf≥4, put k=d−2k=d-2k=d−2, and assume ρf(pk)<pk\rho_f(p^k)<p^kρf​(pk)<pk for every prime ppp. Then the Euler product converges,

cf,k>0,Sf,k(X)=cf,kX+of(X)(X→∞).c_{f,k}>0,\qquad S_{f,k}(X)=c_{f,k}X+o_f(X)\quad(X\to\infty).cf,k​>0,Sf,k​(X)=cf,k​X+of​(X)(X→∞).

For 4≤d≤84\le d\le 84≤d≤8 this is the paper's new Theorem 1.1; for d≥9d\ge9d≥9 it follows from Browning's theorem. Already the case d=4d=4d=4 (squarefree values of quartics such as n4+2n^4+2n4+2 and n4+1n^4+1n4+1) is new. The goal statement is published on the platform with status Open.

Significance

The result itself. The theorem closes the exponent k=d−2k=d-2k=d−2 for every degree, answering Erdős's question about n4+2n^4+2n4+2 and giving the first unconditional squarefree-density theorem for an arbitrary admissible irreducible quartic. No primitivity or sign condition on fff is required. The same large-prime estimate also gives densities for separable products and simultaneous power-freeness of several polynomials (Corollary 1.3).

Formalizing it. The statement is elementary, but its proof uses number-field factorization, the unit theorem, determinant methods for counting points on surfaces and curves, and explicit Hilbert-function computations. None of these components is machine-checked. A formal proof would certify a result that the literature had only reached conditionally (on abcabcabc) or in higher degrees. The finite-prime sieve and the deduction of the density from a large-prime tail bound are reusable for other power-free-value problems.

Difficulty

The sieve over primes p≤Xp\le Xp≤X is routine. The obstacle is the primes p>Xp>Xp>X: one must show that very few n∈(X,2X]n\in(X,2X]n∈(X,2X] have pk∣f(n)p^k\mid f(n)pk∣f(n) for some such ppp (Proposition 1.4, with a power saving X1−δX^{1-\delta}X1−δ). Counting solutions of f(n)=ypkf(n)=yp^kf(n)=ypk as integer points on the surface f(x)=yzkf(x)=yz^kf(x)=yzk with determinant methods succeeds only when ppp is large; in the intermediate range the point counts are too weak, and the existing determinant bounds stop exactly at k≥(3d+1)/4k\ge(3d+1)/4k≥(3d+1)/4.

Formalization scope

  • fff is a Polynomial ℤ whose image in Polynomial ℚ is irreducible, with natDegree ≥ 4; the exponent is f.natDegree - 2 (at least 222, so the natural-number subtraction is harmless).
  • PowerFree k a says no prime ppp has pk∣ap^k\mid apk∣a, so a=0a=0a=0 is not power-free, matching the source convention; negative values are allowed.
  • ρf(q)\rho_f(q)ρf​(q) counts a∈{0,…,q−1}a\in\{0,\dots,q-1\}a∈{0,…,q−1} with q∣f(a)q\mid f(a)q∣f(a); Sf,k(X)S_{f,k}(X)Sf,k​(X) counts 1≤n≤⌊X⌋1\le n\le\lfloor X\rfloor1≤n≤⌊X⌋ over real XXX.
  • The density constant is a tprod over Nat.Primes; the goal asserts Multipliable explicitly, so the constant is not a junk value, together with cf,k>0c_{f,k}>0cf,k​>0 and Sf,k(X)−cf,kX=o(X)S_{f,k}(X)-c_{f,k}X=o(X)Sf,k​(X)−cf,k​X=o(X).
  • No height or uniformity in fff is asserted, matching the source.
  • Needed infrastructure: algebraic number fields and ideal factorization, the unit theorem, Hensel lifting, determinant-method point counting, and an Euler-product sieve. The d≥9d\ge9d≥9 case also needs Browning's theorem (in Xiao's formulation), itself unformalized.

Selected references

  • G. Ricci, Ricerche aritmetiche sui polinomi, Rend. Circ. Mat. Palermo 57 (1933). https://doi.org/10.1007/BF03017586
  • P. Erdős, Arithmetical properties of polynomials, J. London Math. Soc. 28 (1953). https://doi.org/10.1112/jlms/s1-28.4.416
  • C. Hooley, On the power free values of polynomials, Mathematika 14 (1967). https://doi.org/10.1112/S002557930000797X
  • M. Nair, Power free values of polynomials, Mathematika 23 (1976). https://doi.org/10.1112/S0025579300008779
  • A. Granville, ABC allows us to count squarefrees, IMRN 1998. https://doi.org/10.1155/S1073792898000592
  • T. D. Browning, Power-free values of polynomials, Arch. Math. 96 (2011). https://doi.org/10.1007/s00013-011-0224-7
  • S. Y. Xiao, Power-free values of binary forms and the global determinant method, IMRN 2017. https://doi.org/10.1093/imrn/rnw165
  • D. R. Heath-Brown, Power-free values of polynomials, Q. J. Math. 64 (2013). https://doi.org/10.1093/qmath/har030
  • T. Reuss, Power-free values of polynomials, Bull. London Math. Soc. 47 (2015). https://doi.org/10.1112/blms/bdu116
  • OpenAI, Squarefree values of quartics and power-free values of polynomials, OpenAI Math Release preprint, September 24, 2026 (Theorem 1.1, p. 2; Corollary 1.2, p. 4). https://github.com/openai/math/blob/adc7f1241b42e322a6451854ab7e4b4c146bf78a/preprints/Squarefree-values-of-quartics-and-power-free-values-of-polynomials-September-24-2026/manuscript.pdf
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CombinatoricsNumber Theory·Captain: wurtle

The additive indecomposability of the primesResearch Paper

Motivation

Goldbach-type problems ask which sets are sumsets of primes. The inverse Goldbach problem, due to Ostmann (1956), reverses the question: can the set of primes itself, up to finitely many changes, be written as a sumset A+B={a+b:a∈A, b∈B}A+B=\{a+b:a\in A,\ b\in B\}A+B={a+b:a∈A, b∈B} with both AAA and BBB having at least two elements? Ostmann conjectured that it cannot: the primes are asymptotically additively indecomposable. The problem is a clean test of how much additive structure the primes can carry, and it connects sieve theory (the primes avoid one residue class modulo each prime) with inverse questions for the large sieve.

Background

  • 1954–1955. Hornfeck proves early restrictions on additive decompositions of the primes (doi:10.1007/BF01187376).
  • 1956. Ostmann formulates the conjecture in his treatise on additive number theory (doi:10.1007/978-3-662-11030-0).
  • 1964. Laffer and Mann show that a hypothetical decomposition must have two infinite summands (doi:10.2140/pjm.1964.14.547).
  • 1988–1996. Pomerance, Sárközy and Stewart, and Hofmann and Wolke, obtain sieve restrictions on the summands (doi:10.2140/pjm.1988.133.363, doi:10.1007/BF01189097).
  • 2001. Elsholtz combines the large and larger sieves to put both counting functions near the square-root scale and rules out decompositions into three nontrivial summands (doi:10.1112/S0025579300014406).
  • 2014–2016. Green and Harper show that an inverse large-sieve conjecture would imply Ostmann's conjecture (arXiv:1311.6176); Elsholtz and Harper sharpen the binary counting bounds (doi:10.1090/S0002-9947-2014-06384-8); Shao proves a finite ternary obstruction (doi:10.1353/ajm.2016.0038).
  • 2020–2026. Hanson, then Croot, Mao and Yip, and Croot, Mao, Pohoata and Yip prove partial inverse theorems for the large sieve and derive further necessary conditions on a hypothetical decomposition (doi:10.1017/S0305004118000518, arXiv:2510.08862, arXiv:2607.15311).

The source of this mission is an OpenAI preprint dated September 24, 2026.

Setting

Let N0={0,1,2,… }\mathbb N_0=\{0,1,2,\dots\}N0​={0,1,2,…} and let PPP be the set of positive primes. For A,B⊆N0A,B\subseteq\mathbb N_0A,B⊆N0​ the sumset is A+B={a+b:a∈A, b∈B}A+B=\{a+b:a\in A,\ b\in B\}A+B={a+b:a∈A, b∈B}. Two sets are asymptotically equal if their symmetric difference X△Y=(X∖Y)∪(Y∖X)X\triangle Y=(X\setminus Y)\cup(Y\setminus X)X△Y=(X∖Y)∪(Y∖X) is finite. A decomposition is nontrivial if ∣A∣≥2|A|\ge2∣A∣≥2 and ∣B∣≥2|B|\ge2∣B∣≥2; the trivial decompositions {0}+P\{0\}+P{0}+P are excluded.

Formalization targets

Goal: Theorem 1.1 (Ostmann's conjecture)

A,B⊆N0, ∣A∣≥2, ∣B∣≥2 ⟹ (A+B)△P is infinite.A,B\subseteq\mathbb N_0,\ |A|\ge2,\ |B|\ge2\ \Longrightarrow\ (A+B)\triangle P\ \text{is infinite}.A,B⊆N0​, ∣A∣≥2, ∣B∣≥2 ⟹ (A+B)△P is infinite.

Milestone: Theorem 2.3 (two infinite summands)

There are no infinite A,B⊆N0 with (A+B)△P finite.\text{There are no infinite }A,B\subseteq\mathbb N_0\text{ with }(A+B)\triangle P\text{ finite}.There are no infinite A,B⊆N0​ with (A+B)△P finite.

Theorem 2.3 is the core of the proof; Lemma 2.2 reduces Theorem 1.1 to it by a short sieve argument.

The goal OAI.Ostmann.inverseGoldbach is open on the platform.

Significance

Theorem 1.1 resolves Ostmann's conjecture. The conclusion controls both requirements of an eventual decomposition: if ∣A∣,∣B∣≥2|A|,|B|\ge2∣A∣,∣B∣≥2 and A+BA+BA+B contains every sufficiently large prime, then A+BA+BA+B contains infinitely many composite numbers. The proof does not go through the general inverse large-sieve conjecture of Green and Harper; it uses the simultaneous residue restrictions together with coverage of every large prime directly.

The result is proved in an OpenAI preprint, which has not been peer reviewed. No machine-checked proof exists. The statement is elementary, so the formal target is short; the difficulty is entirely in the proof.

Difficulty

Counting alone cannot work: sieve bounds put A(x)A(x)A(x) and B(x)B(x)B(x) near x\sqrt xx​, which is compatible with the lower bound A(x)B(x)≫x/log⁡xA(x)B(x)\gg x/\log xA(x)B(x)≫x/logx forced by covering the primes. The known necessary conditions (large intersections with quadratic images) fall short of the near-containment that Green and Harper's conditional route requires. The proof must turn the local information (modulo each prime ppp, the images of AAA and −B-B−B are disjoint) into a global contradiction: it rules out correlations with translated multiplicative characters of every order, compares a positive sumset statistic with its average over the primes, and handles residue indicators with no prescribed algebraic form via a finite-field comparison of binary trees. The paper runs to about 80 pages.

Formalization scope

  • primes = {n : ℕ | Nat.Prime n}; sumset A B is Mathlib's pointwise A + B on Set ℕ.
  • A.Nontrivial means AAA has two distinct elements.
  • InverseGoldbach asserts Set.Infinite (sumset A B ∆ primes); TwoInfiniteSummandsImpossible uses EventuallyPrimeSumset A B := ∃ N, ∀ n ≥ N, n ∈ A + B ↔ n.Prime, which is equivalent to a finite symmetric difference.
  • OAI.Ostmann.main is the same statement as the goal without the definition file and is included as a reference item.

A complete development needs the additive large sieve (Montgomery–Vaughan), Gallagher's larger sieve, Mertens-type estimates, character sums over finite fields including the quadratic large sieve, prime number theorems in progressions with the exceptional character, and Fourier analysis on Fp\mathbb F_pFp​. Contributions formalizing Lemma 2.1 (fixed shifts), Lemma 2.2 (finite summands), Lemma 2.4 (square-root bounds), Proposition 3.1, Corollary 4.2 (mixed-character decorrelation), Proposition 5.1 and Lemma 6.1 (tree comparison) are welcome.

Selected references

  • OpenAI, The additive indecomposability of the primes, preprint, September 24, 2026. https://github.com/openai/math/blob/adc7f1241b42e322a6451854ab7e4b4c146bf78a/preprints/the-additive-indecomposability-of-the-primes-September-24-2026/paper.pdf
  • H.-H. Ostmann, Additive Zahlentheorie. Erster Teil, Springer, 1956. https://doi.org/10.1007/978-3-662-11030-0
  • W. B. Laffer, H. B. Mann, Decomposition of sets of group elements, Pacific J. Math., 1964. https://doi.org/10.2140/pjm.1964.14.547
  • C. Elsholtz, The inverse Goldbach problem, Mathematika, 2001. https://doi.org/10.1112/S0025579300014406
  • B. Green, A. J. Harper, Inverse questions for the large sieve, Geom. Funct. Anal., 2014. https://doi.org/10.1007/s00039-014-0288-1
  • C. Elsholtz, A. J. Harper, Additive decompositions of sets with restricted prime factors, Trans. Amer. Math. Soc., 2015. https://doi.org/10.1090/S0002-9947-2014-06384-8
  • X. Shao, On an inverse ternary Goldbach problem, Amer. J. Math., 2016. https://doi.org/10.1353/ajm.2016.0038
  • B. Hanson, Additive correlation and the inverse problem for the large sieve, Math. Proc. Cambridge Philos. Soc., 2020. https://doi.org/10.1017/S0305004118000518
  • E. Croot, J. Mao, C. Pohoata, C. H. Yip, A sharp inverse theorem for the quadratic large sieve, preprint, 2026. https://arxiv.org/abs/2607.15311
  • H. L. Montgomery, R. C. Vaughan, The large sieve, Mathematika, 1973. https://doi.org/10.1112/S0025579300004708
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Number Theory·Captain: wurtle

Ordinary two-point correlations of multiplicative functionsResearch Paper

Motivation

Let Ω(n)\Omega(n)Ω(n) count the prime factors of nnn with multiplicity and let λ(n)=(−1)Ω(n)\lambda(n)=(-1)^{\Omega(n)}λ(n)=(−1)Ω(n) be the Liouville function. Chowla's conjecture (1965) predicts that λ\lambdaλ behaves like a random sign sequence: its correlations along any fixed collection of distinct shifts have average tending to zero. The two-point case asks whether nnn and n+hn+hn+h have the same parity of prime-factor count as often as different parity. It is the multiplicative analogue of the twin prime problem and a central test case for the parity barrier in sieve theory. Elliott's conjecture extends the question to bounded multiplicative functions; Matomäki, Radziwiłł and Tao showed that for complex functions it needs a correction, uniform nonpretentiousness against all twists χ(n)nit\chi(n)n^{it}χ(n)nit.

There are two natural averages: the ordinary average 1X∑n≤Xa(n)\frac1X\sum_{n\le X}a(n)X1​∑n≤X​a(n) and the logarithmic average 1log⁡X∑n≤Xa(n)/n\frac1{\log X}\sum_{n\le X}a(n)/nlogX1​∑n≤X​a(n)/n. Logarithmic averaging blends many scales; an ordinary estimate must control the terminal scale itself.

Background

  • 1965. Chowla formulates his conjecture. 1971. Halász's mean-value theorem isolates the twists nitn^{it}nit as the obstruction for one-point means.
  • 1992. Elliott extends the correlation problem to bounded multiplicative functions.
  • 2007. Granville and Soundararajan develop the pretentious distance D\mathbb DD (doi:10.1090/S0894-0347-06-00536-4).
  • 2015–2016. Matomäki and Radziwiłł prove short-interval mean-value theorems and a nontrivial bound 1−δ(h)1-\delta(h)1−δ(h) for each two-point Liouville correlation (doi:10.4007/annals.2016.183.3.6); Matomäki, Radziwiłł and Tao prove an averaged form of Chowla and formulate the corrected Elliott condition (doi:10.2140/ant.2015.9.2167).
  • 2016. Tao proves the logarithmically averaged two-point Chowla and corrected Elliott conjectures, including affine forms (doi:10.1017/fmp.2016.6).
  • 2019. Tao and Teräväinen obtain ordinary binary cancellation outside a set of scales of logarithmic density zero (doi:10.2140/ant.2019.13.2103).
  • 2021, 2026. Helfgott and Radziwiłł obtain a quantitative logarithmic bound via divisibility-graph expansion (arXiv:2103.06853); Pilatte improves it to (log⁡x)1−c0(\log x)^{1-c_0}(logx)1−c0​ (doi:10.1090/jams/1084).
  • 2023, 2026. Klurman, Mangerel and Teräväinen relax the nonpretentiousness hypothesis along a full-density set of scales (arXiv:2304.05344); Tao and Teräväinen obtain logarithmic savings for affine Liouville correlations outside a controlled exceptional set of scales (arXiv:2512.01739).

The source of this mission is an OpenAI preprint dated September 24, 2026, which treats ordinary averages at every cutoff.

Setting

  • λ(n)=(−1)Ω(n)\lambda(n)=(-1)^{\Omega(n)}λ(n)=(−1)Ω(n) for n≥1n\ge1n≥1.
  • A function f:N→Cf:\mathbb N\to\mathbb Cf:N→C is multiplicative if f(mn)=f(m)f(n)f(mn)=f(m)f(n)f(mn)=f(m)f(n) for coprime positive m,nm,nm,n, and one-bounded if ∣f(n)∣≤1|f(n)|\le1∣f(n)∣≤1.
  • For a Dirichlet character χ\chiχ, t∈Rt\in\mathbb Rt∈R and X≥2X\ge2X≥2, the pretentious distance is
D(f,χnit;X)2=∑p≤X1−Re⁡(f(p)χ(p)‾p−it)p.\mathbb D(f,\chi n^{it};X)^2=\sum_{p\le X}\frac{1-\operatorname{Re}\bigl(f(p)\overline{\chi(p)}p^{-it}\bigr)}{p}.D(f,χnit;X)2=p≤X∑​p1−Re(f(p)χ(p)​p−it)​.
  • fff is uniformly nonpretentious if inf⁡∣t∣≤ND(f,χnit;N)→∞\inf_{|t|\le N}\mathbb D(f,\chi n^{it};N)\to\inftyinf∣t∣≤N​D(f,χnit;N)→∞ as N→∞N\to\inftyN→∞, for every fixed χ\chiχ.
  • Two affine forms a1n+b1a_1n+b_1a1​n+b1​, a2n+b2a_2n+b_2a2​n+b2​ with ai≥1a_i\ge1ai​≥1, bi≥0b_i\ge0bi​≥0 are nonproportional if a1b2≠a2b1a_1b_2\ne a_2b_1a1​b2​=a2​b1​.

Formalization targets

Goal: Theorem 1.1 (logarithmic saving for affine Liouville correlations)

There is an absolute c>0c>0c>0 such that for all nonproportional affine forms there is C=Ca1,a2,b1,b2C=C_{a_1,a_2,b_1,b_2}C=Ca1​,a2​,b1​,b2​​ with

∣∑1≤n≤Xλ(a1n+b1)λ(a2n+b2)∣≤C X(log⁡X)c(X≥3).\Bigl|\sum_{1\le n\le X}\lambda(a_1n+b_1)\lambda(a_2n+b_2)\Bigr|\le C\,\frac{X}{(\log X)^c}\qquad(X\ge3).​1≤n≤X∑​λ(a1​n+b1​)λ(a2​n+b2​)​≤C(logX)cX​(X≥3).

With a1=a2=1a_1=a_2=1a1​=a2​=1, b1=0b_1=0b1​=0, b2=h>0b_2=h>0b2​=h>0 this is the ordinary two-point Chowla conjecture with a logarithmic saving.

Milestones

  • Theorem 1.2. If f1,f2f_1,f_2f1​,f2​ are multiplicative and one-bounded and one of them is uniformly nonpretentious, then 1N∑n=1Nf1(n+h1)f2(n+h2)→0\frac1N\sum_{n=1}^Nf_1(n+h_1)f_2(n+h_2)\to0N1​∑n=1N​f1​(n+h1​)f2​(n+h2​)→0 for distinct h1,h2≥0h_1,h_2\ge0h1​,h2​≥0.
  • Corollary 1.3. The same conclusion for f1(a1n+b1)f2(a2n+b2)f_1(a_1n+b_1)f_2(a_2n+b_2)f1​(a1​n+b1​)f2​(a2​n+b2​) along nonproportional affine forms.

The goal OAI.OrdinaryTwoPointCorrelations.liouville_log_saving is open on the platform.

Significance

Theorem 1.1 removes the logarithmic weight and the exceptional scales from earlier two-point results: the bound holds at every cutoff, with an exponent independent of the forms. Theorem 1.2 does the same qualitatively for all one-bounded multiplicative functions satisfying the Matomäki–Radziwiłł–Tao corrected condition, without complete multiplicativity, unimodularity or real values. The implied constants need not be effective, and no uniformity in growing coefficients is claimed.

The results are proved in an OpenAI preprint, which has not been peer reviewed. No machine-checked proof exists.

Difficulty

Partial summation turns ordinary cancellation into logarithmic cancellation, but not conversely, so Tao's entropy-decrement method and its descendants do not reach ordinary averages: they need to average over scales. Short-interval estimates give cancellation for most shifts or most scales, not for a fixed shift at every scale. The proof works at the terminal scale through multiplicative dilations, which lead to a divisor graph with edge displacement hdhdhd; one must bound high traces of the associated operator (closed walks, nonbacktracking moments, prohibited paths, triangular arithmetic savings) with weights matched to ordinary averaging, and in Part I convert this into an explicit logarithmic saving using bounded independence for Boolean circuits.

Formalization scope

  • liouville n is ArithmeticFunction.liouville n cast to ℂ; affineSum f g a₁ a₂ b₁ b₂ N sums over n ∈ Finset.Icc 1 N, and the bound is applied at N = ⌊X⌋₊ for real X ≥ 3, with (Real.log X) ^ c as Real.rpow.
  • Multiplicative asks the identity only for coprime positive arguments; OneBounded only for positive arguments in this source group.
  • UniformlyNonpretentious is stated as: for every q > 0, every χ : DirichletCharacter ℂ q and every K, eventually in N, every t with |t| ≤ N has squared distance at least K. This is equivalent to (1.2).
  • The second formalization of Theorem 1.2 (namespace OrdinaryCorrelations) uses the sInf form of (1.2) and is included as a reference item.

A complete development needs prime sums and Mertens-type estimates, Dirichlet characters, short-interval mean-value theorems (Matomäki–Radziwiłł–Tao, Theorem 4.3 here), Fourier bounds for rough integers, and the graph-trace machinery. Contributions formalizing Proposition 2.1 (quantitative correlations in every progression), Theorem 5.4 (the nonbacktracking moment), Proposition 10.1 (divisor graph estimate), Lemma 18.5 (uniform nonpretentiousness of Liouville) or the cited Theorem 4.3 are welcome.

Selected references

  • OpenAI, Ordinary two-point correlations of multiplicative functions, preprint, September 24, 2026. https://github.com/openai/math/blob/adc7f1241b42e322a6451854ab7e4b4c146bf78a/preprints/Ordinary-two-point-correlations-of-multiplicative-functions-September-24-2026/final.pdf
  • K. Matomäki, M. Radziwiłł, T. Tao, An averaged form of Chowla's conjecture, Algebra Number Theory, 2015. https://doi.org/10.2140/ant.2015.9.2167
  • K. Matomäki, M. Radziwiłł, Multiplicative functions in short intervals, Ann. of Math., 2016. https://doi.org/10.4007/annals.2016.183.3.6
  • T. Tao, The logarithmically averaged Chowla and Elliott conjectures for two-point correlations, Forum Math. Pi, 2016. https://doi.org/10.1017/fmp.2016.6
  • T. Tao, J. Teräväinen, The structure of correlations of multiplicative functions at almost all scales, Algebra Number Theory, 2019. https://doi.org/10.2140/ant.2019.13.2103
  • H. A. Helfgott, M. Radziwiłł, Expansion, divisibility and parity, preprint, 2021. https://arxiv.org/abs/2103.06853
  • C. Pilatte, Improved bounds for the two-point logarithmic Chowla conjecture, J. Amer. Math. Soc., 2026. https://doi.org/10.1090/jams/1084
  • O. Klurman, A. P. Mangerel, J. Teräväinen, On Elliott's conjecture and applications, preprint, 2023. https://arxiv.org/abs/2304.05344
  • A. Granville, K. Soundararajan, Large character sums: pretentious characters and the Pólya–Vinogradov theorem, J. Amer. Math. Soc., 2007. https://doi.org/10.1090/S0894-0347-06-00536-4
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Number Theory·Captain: wurtle

Catalan’s constant is irrational — OpenAI Lean formalizationResearch Paper

Motivation

Catalan's constant

G=∑j=0∞(−1)j(2j+1)2=1−19+125−149+⋯=0.9159655…G=\sum_{j=0}^{\infty}\frac{(-1)^j}{(2j+1)^2}=1-\frac1{9}+\frac1{25}-\frac1{49}+\cdots=0.9159655\ldotsG=j=0∑∞​(2j+1)2(−1)j​=1−91​+251​−491​+⋯=0.9159655…

is the value β(2)=L(2,χ−4)\beta(2)=L(2,\chi_{-4})β(2)=L(2,χ−4​) of the Dirichlet LLL-function of the odd quadratic character of conductor 4. It appears throughout analysis, combinatorics (dimer and spanning-tree constants), and geometry (volumes of hyperbolic 3-manifolds). For odd sss, β(s)\beta(s)β(s) is a rational multiple of πs\pi^sπs; the even values β(2),β(4),…\beta(2),\beta(4),\ldotsβ(2),β(4),… are, like ζ(3),ζ(5),…\zeta(3),\zeta(5),\ldotsζ(3),ζ(5),…, among the basic special values whose arithmetic nature was unknown. Whether GGG is irrational had long been a well-known question.

Timeline

  • 1979. Apéry proves ζ(2)\zeta(2)ζ(2) and ζ(3)\zeta(3)ζ(3) irrational by recurrences whose integer linear forms tend to zero; Beukers gives integral proofs (doi:10.1112/blms/11.3.268).
  • 2003. Rivoal and Zudilin prove that infinitely many even β\betaβ-values are irrational, and that at least one of β(2),β(4),…,β(14)\beta(2),\beta(4),\ldots,\beta(14)β(2),β(4),…,β(14) is (doi:10.1007/s00208-003-0420-2). Zudilin constructs Apéry-like recurrences, a continued fraction and integrals for GGG, and observes that their integer linear forms do not tend to zero (doi:10.37236/1707).
  • 2006–2008. Rivoal connects Padé approximation to the hypergeometric construction and proves its denominator conjectures; Krattenthaler and Rivoal give a more direct proof (doi:10.1007/s11139-006-6507-0, arXiv:0810.1927).
  • 2016. Nesterenko develops half-integer hypergeometric approximations and double Euler integrals for GGG (doi:10.1134/S0081543816010107).
  • 2017. Zudilin proposes a determinantal criterion for irrationality and explains why it does not yet apply to GGG (doi:10.1007/s00365-016-9333-7).
  • 2019–2022. Zudilin, then Lai and Zhou, shrink the finite list of even β\betaβ-values known to contain an irrational one; Fischler proves quantitative results for families of Dirichlet LLL-values (doi:10.1112/jlms.12290); Viola reports improved approximation exponents (doi:10.4171/OWR/2022/21).
  • 2005, 2024. Calegari proves irrationality of a 2-adic analogue of GGG (doi:10.1155/IMRN.2005.1235); Calegari, Dimitrov and Tang prove linear independence of 1,ζ(2),L(2,χ−3)1,\zeta(2),L(2,\chi_{-3})1,ζ(2),L(2,χ−3​), the conductor-3 analogue (arXiv:2408.15403).
  • 2026. Eskandari constructs improved rational approximations (arXiv:2609.26354); Sun announces a proof of irrationality (arXiv:2609.04176).

The source of this mission is an OpenAI preprint dated September 24, 2026.

Setting

GGG is the sum of the alternating series of reciprocals of odd squares displayed above. A real number xxx is irrational if x≠p/qx\neq p/qx=p/q for all integers ppp and q≠0q\neq0q=0. No other definitions are involved.

Formalization targets

Goal: Theorem 1.1

G=∑j≥0(−1)j(2j+1)2 ∉ Q.G=\sum_{j\ge0}\frac{(-1)^j}{(2j+1)^2}\ \notin\ \mathbb Q.G=j≥0∑​(2j+1)2(−1)j​ ∈/ Q.

The Lean statement OAI.InternalCatalan.catalan_irrational is open on the platform.

Significance

Theorem 1.1 settles the irrationality of an individual even Dirichlet β\betaβ-value, which family results (Rivoal–Zudilin, Fischler) could not single out. The paper deduces (Section 8) irrationality of the minimal volume of an orientable complete finite-volume hyperbolic 3-manifold with exactly two cusps (Agol 2010 identified this volume as 4G4G4G, doi:10.1090/S0002-9939-10-10364-5) and of certain arithmetic hyperbolic volumes. The argument is qualitative: it gives no irrationality measure.

The result is proved in an OpenAI preprint, which has not been peer reviewed. No machine-checked proof exists. A formal proof would certify a long argument that combines exact finite certificates (rational matrices, rational trial coefficients) with analytic and ppp-adic estimates.

Difficulty

The standard route needs nonzero integer linear forms AmG−Bm→0A_mG-B_m\to0Am​G−Bm​→0. Many constructions give rational approximations Bm/Am→GB_m/A_m\to GBm​/Am​→G quickly, but clearing denominators destroys the decay: this is exactly the obstruction Zudilin identified for his Apéry-like recurrences, and approximation exponents below 1 (Viola–Marcovecchio, Eskandari) do not overcome it. The paper replaces linear forms by growing determinants ΔN\Delta_NΔN​ of size 48N48N48N built from moments that are rational combinations of 111, GGG and ζ(2)\zeta(2)ζ(2); one must cancel the ζ(2)\zeta(2)ζ(2) term exactly, bound denominators prime by prime (including two layers at large odd primes), prove nonvanishing along a sequence of primes via a finite certificate, and obtain a real-place upper bound sharp enough that the normalized limits lim inf⁡LN>−2.29084\liminf L_N>-2.29084liminfLN​>−2.29084 and lim sup⁡LN≤−2.290939875\limsup L_N\le-2.290939875limsupLN​≤−2.290939875 are incompatible. The margin between these constants is about 10−410^{-4}10−4.

Formalization scope

  • The statement uses only Mathlib: Irrational and tsum over ℕ. The series is absolutely summable, so tsum agrees with the classical sum.
  • The factor 2j+12j+12j+1 is a natural number cast to ℝ; there are no partial operations.

A complete development needs: Chebyshev polynomial rows and their moments; ppp-adic valuations of the determinant entries and the prime number theorem in the weighted form used (Mathlib's PNT development may be reused); a Frobenius reduction and verified finite certificates for nonvanishing; Andréief's identity, Hardy-space interpolation and Hadamard bounds for the real estimate; and certified rational arithmetic for the final constants. Contributions formalizing Proposition 2.2 (cancellation and rationality), Proposition 3.4 (finite-place bound), Proposition 4.1 (nonvanishing at prime scales), Propositions 5.2–5.3 (interpolation and Hadamard estimates) and Proposition 7.1 (real-place bound) are welcome.

Selected references

  • OpenAI, Catalan's constant is irrational, preprint, September 24, 2026. https://github.com/openai/math/blob/adc7f1241b42e322a6451854ab7e4b4c146bf78a/preprints/Catalans-constant-is-irrational-September-24-2026/paper.pdf
  • T. Rivoal, W. Zudilin, Diophantine properties of numbers related to Catalan's constant, Math. Ann., 2003. https://doi.org/10.1007/s00208-003-0420-2
  • W. Zudilin, An Apéry-like difference equation for Catalan's constant, Electron. J. Combin., 2003. https://doi.org/10.37236/1707
  • W. Zudilin, A determinantal approach to irrationality, Constr. Approx., 2017. https://doi.org/10.1007/s00365-016-9333-7
  • T. Rivoal, Nombres d'Euler, approximants de Padé et constante de Catalan, Ramanujan J., 2006. https://doi.org/10.1007/s11139-006-6507-0
  • Yu. V. Nesterenko, On Catalan's constant, Proc. Steklov Inst. Math., 2016. https://doi.org/10.1134/S0081543816010107
  • S. Fischler, Irrationality of values of L-functions of Dirichlet characters, J. London Math. Soc., 2020. https://doi.org/10.1112/jlms.12290
  • F. Calegari, V. Dimitrov, Y. Tang, The linear independence of 1, ζ(2), and L(2,χ_{−3}), preprint, 2024. https://arxiv.org/abs/2408.15403
  • F. Beukers, A note on the irrationality of ζ(2) and ζ(3), Bull. London Math. Soc., 1979. https://doi.org/10.1112/blms/11.3.268
  • I. Agol, The minimal volume orientable hyperbolic 2-cusped 3-manifolds, Proc. Amer. Math. Soc., 2010. https://doi.org/10.1090/S0002-9939-10-10364-5
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AnalysisNumber Theory·Captain: wurtle

The Quasi-Riemann Hypothesis: A Zero-Free Half-Plane Re(s) > 7/8Research Paper

Motivation

The Riemann zeta function ζ(s)=∑n≥1n−s\zeta(s) = \sum_{n\ge1} n^{-s}ζ(s)=∑n≥1​n−s (ℜs>1\Re s > 1ℜs>1), continued meromorphically to C\mathbb{C}C, encodes the distribution of primes through its zeros. Riemann (1859) conjectured that all nontrivial zeros lie on ℜs=1/2\Re s = 1/2ℜs=1/2. Hadamard and de la Vallée Poussin (1896) proved there are no zeros on ℜs=1\Re s = 1ℜs=1, which gives the prime number theorem, but all classical zero-free regions shrink toward the line ℜs=1\Re s = 1ℜs=1 as the height grows. The quasi-Riemann hypothesis asks for a fixed σ0<1\sigma_0 < 1σ0​<1 such that ζ(s)≠0\zeta(s) \ne 0ζ(s)=0 for all ℜs>σ0\Re s > \sigma_0ℜs>σ0​: one zero-free gap valid at every height. The uniform version for all Dirichlet LLL-functions is a standard formulation in analytic number theory (e.g. Friedlander–Goldston).

This preprint claims a proof with σ0=7/8\sigma_0 = 7/8σ0​=7/8, for ζ\zetaζ, for all Dirichlet LLL-functions, and for all finite-order Hecke LLL-functions over Q(−3)\mathbb{Q}(\sqrt{-3})Q(−3​).

Background

  • 1837. Dirichlet introduces character LLL-series to prove infinitude of primes in arithmetic progressions.
  • 1859. Riemann relates zeros of ζ\zetaζ to primes and formulates the Riemann hypothesis.
  • 1896. Hadamard and de la Vallée Poussin prove ζ(s)≠0\zeta(s) \ne 0ζ(s)=0 on ℜs=1\Re s = 1ℜs=1.
  • 1918. Hecke develops LLL-functions of characters over number fields.
  • 1969, 1977. Kubota's metaplectic theory and Patterson's cubic theta series supply the automorphic objects used here.
  • 2000–2014. Heath-Brown's cubic large sieve; Goldmakher–Louvel's quadratic large sieve over number fields; Blomer–Goldmakher–Louvel's higher-order recursion.
  • 2026. Guth and Maynard improve zero-density bounds for ζ\zetaζ (which bound the number of zeros but do not exclude them). The OpenAI preprint The Quasi-Riemann Hypothesis (dated September 30, 2026) claims the zero-free half-plane ℜs>7/8\Re s > 7/8ℜs>7/8. It has not been peer reviewed or independently verified; the Lean goal is open on this platform. The Riemann hypothesis itself is not claimed.

Setting

For a Dirichlet character χ\chiχ modulo qqq (extended by zero on non-units), L(s,χ)=∑n≥1χ(n)n−sL(s,\chi) = \sum_{n \ge 1}\chi(n) n^{-s}L(s,χ)=∑n≥1​χ(n)n−s for ℜs>1\Re s > 1ℜs>1, continued meromorphically; the character modulo 111 gives ζ\zetaζ. For F=Q(−3)F = \mathbb{Q}(\sqrt{-3})F=Q(−3​) with ring of integers O\mathcal{O}O, a finite-order Hecke character modulo a nonzero ideal f\mathfrak{f}f is a character of the ray class group modulo f\mathfrak ff, extended by zero, and LF(s,η)=∑a≠0η(a)(Na)−sL_F(s,\eta) = \sum_{\mathfrak a \ne 0}\eta(\mathfrak a)(N\mathfrak a)^{-s}LF​(s,η)=∑a=0​η(a)(Na)−s. Principal characters have a pole at s=1s = 1s=1.

In Lean, ζ\zetaζ is Mathlib's riemannZeta, Dirichlet LLL-functions are Mathlib's DirichletCharacter.LFunction, and the Hecke family is OAI.SevenEighths.HeckeFamily.LFunction: a Character is a multiplicative character of O/m\mathcal O/\mathfrak mO/m trivial on units (for this class-number-one field these are exactly the ray class characters), and its LLL-function is a lattice sum over O=Z[ω]\mathcal{O} = \mathbb{Z}[\omega]O=Z[ω] divided by the 666 units, continued through a theta-type functional equation pair.

Formalization targets

Goal: Theorem 1.1 for ζ\zetaζ (quasi-Riemann hypothesis)

ℜs>7/8  ⟹  ζ(s)≠0.\Re s > 7/8 \implies \zeta(s) \ne 0 .ℜs>7/8⟹ζ(s)=0.

Milestone: Theorem 1.1 for Dirichlet LLL-functions

For every Dirichlet character χ\chiχ modulo q≥1q \ge 1q≥1 and every sss with ℜs>7/8\Re s > 7/8ℜs>7/8, L(s,χ)≠0L(s,\chi) \ne 0L(s,χ)=0, except at the pole s=1s = 1s=1 of a principal character.

Milestone: Theorem 1.1 for Hecke LLL-functions over Q(−3)\mathbb{Q}(\sqrt{-3})Q(−3​)

For every finite-order Hecke character η\etaη of F=Q(−3)F = \mathbb{Q}(\sqrt{-3})F=Q(−3​) and every sss with ℜs>7/8\Re s > 7/8ℜs>7/8, LF(s,η)≠0L_F(s,\eta) \ne 0LF​(s,η)=0, except at the pole s=1s = 1s=1 of a principal character.

The three statements are ordered from weakest to strongest; the proof in the preprint goes through the whole Hecke family even for ζ\zetaζ, because Poisson summation introduces Hecke twists of the target.

Significance

The result. A fixed zero-free half-plane would give power-saving error terms in the prime number theorem and in prime counts in arithmetic progressions, uniformly in the modulus, and would exclude Siegel zeros beyond 7/87/87/8. The preprint derives (Corollary 1.2) that the least quadratic nonresidue modulo ppp is O((log⁡p)A)O((\log p)^A)O((logp)A), proving Vinogradov's conjecture, and a deterministic polynomial-time square-root algorithm modulo primes.

Formalizing it. This is a claimed resolution of a long-standing question in an unrefereed preprint; a machine-checked proof would be strong independent verification. The goal uses only Mathlib definitions, so it cannot be weakened by a definitional choice. The Hecke milestone uses a custom LLL-function definition that must also be checked against the source.

Difficulty

Classical zero-free regions come from positivity arguments (the 3+4cos⁡θ+cos⁡2θ3 + 4\cos\theta + \cos 2\theta3+4cosθ+cos2θ inequality) that give regions of width c/log⁡(∣t∣+q)c/\log(|t|+q)c/log(∣t∣+q) shrinking to the line ℜs=1\Re s = 1ℜs=1; they cannot produce a fixed half-plane. Zero-density estimates bound the number of zeros to the right of a line but do not exclude every zero. The preprint instead continues reciprocals 1/L1/L1/L across a uniform distance by comparing two exact representations of a completed cubic-theta sum, with exponent margins independent of the target character.

Formalization scope

  • The goal: ∀ s : ℂ, 7/8 < s.re → riemannZeta s ≠ 0. Mathlib assigns ζ(1)\zeta(1)ζ(1) a finite nonzero value, so no pole exclusion is needed.
  • The Dirichlet milestone excludes exactly the case χ = 1 ∧ s = 1, where Mathlib's value is a junk value at the pole.
  • The Hecke milestone excludes χ.residue = 1 ∧ s = 1.
  • The boundary ℜs=7/8\Re s = 7/8ℜs=7/8 is not included.

The goal is not vacuous and cannot be satisfied by a convention: it is a statement about Mathlib's riemannZeta on an open half-plane.

Needed infrastructure: Hecke LLL-functions over imaginary quadratic fields and their functional equations, cubic and sextic residue symbols, Patterson's cubic theta coefficients, large sieve inequalities over Z[ω]\mathbb{Z}[\omega]Z[ω], and Mellin inversion. Contributions toward the 11/1211/1211/12 half-plane (Theorem 3.1) as an intermediate target are welcome.

Selected references

  • OpenAI, The Quasi-Riemann Hypothesis, OpenAI Math Release preprint, September 30, 2026. https://github.com/openai/math/blob/adc7f1241b42e322a6451854ab7e4b4c146bf78a/preprints/The-Quasi-Riemann-Hypothesis-September-30-2026/paper.pdf
  • B. Riemann, Ueber die Anzahl der Primzahlen unter einer gegebenen Grösse, Monatsber. Königl. Preuss. Akad. Wiss. Berlin (1859).
  • J. Hadamard, Sur la distribution des zéros de la fonction ζ(s) et ses conséquences arithmétiques, Bull. Soc. Math. France 24 (1896).
  • E. Hecke, Eine neue Art von Zetafunktionen und ihre Beziehungen zur Verteilung der Primzahlen, Math. Z. 1 (1918).
  • J. B. Friedlander, D. A. Goldston, Sums of three or more primes, Trans. Amer. Math. Soc. 349 (1997).
  • K. Billington, M. Cheng, J. Schettler, A. I. Suriajaya, The average number of Goldbach representations and zero-free regions of the Riemann zeta-function, Int. J. Number Theory 21 (2025).
  • S. J. Patterson, A cubic analogue of the theta series, J. Reine Angew. Math. 296 (1977).
  • D. R. Heath-Brown, Kummer's conjecture for cubic Gauss sums, Israel J. Math. 120 (2000). https://doi.org/10.1007/s11856-000-1273-y
  • V. Blomer, L. Goldmakher, B. Louvel, L-functions with n-th-order twists, IMRN 2014.
  • L. Guth, J. Maynard, New large value estimates for Dirichlet polynomials, Ann. of Math. 203 (2026). https://doi.org/10.4007/annals.2026.203.2.6
  • T. Tao, The Elliott–Halberstam conjecture implies the Vinogradov least quadratic nonresidue conjecture, Algebra Number Theory 9 (2015).
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Operations ResearchOptimization·Captain: mikedeng1

Theoretical and Numerical Comparison of Relaxation Methods for Mathematical Programs with Complementarity Constraints 1: Scholtes Relaxation Limits Are C-Stationary under MPEC-MFCQResearch Paper

Motivation

A mathematical program with complementarity constraints (MPCC, also called MPEC, mathematical program with equilibrium constraints) is a nonlinear optimization problem in which some pairs of constraint functions must be nonnegative with at least one of each pair equal to zero. Such constraints model equilibria inside an optimization problem: bilevel programs whose lower level is replaced by its optimality conditions, Stackelberg games, traffic and electricity market equilibria, contact problems in mechanics. See Luo, Pang and Ralph, Mathematical Programs with Equilibrium Constraints (Cambridge University Press, 1996), doi:10.1017/CBO9780511983658.

The complementarity constraints make the standard theory fail. At every feasible point the Mangasarian–Fromovitz constraint qualification is violated, so the Karush–Kuhn–Tucker conditions are not necessary for optimality, and standard NLP solvers lose their convergence guarantees. A common remedy is relaxation: replace the MPEC by a family of ordinary nonlinear programs depending on a parameter t>0t>0t>0, solve them for t↓0t\downarrow0t↓0, and study the limits of their stationary points.

The first relaxation scheme, and the reference point for all later ones, is due to Scholtes (Convergence properties of a regularization scheme for mathematical programs with complementarity constraints, SIAM J. Optim. 11 (2001), doi:10.1137/S1052623499361233). Scholtes showed that limits of stationary points of the relaxed programs are C-stationary when MPEC-LICQ holds at the limit. Hoheisel, Kanzow and Schwartz (Preprint 299, University of Würzburg, 2010; later Math. Program. 137 (2013), doi:10.1007/s10107-011-0488-5) compare five relaxation schemes and weaken the constraint qualification in each convergence theorem. For Scholtes' scheme, their Theorem 3.1 replaces MPEC-LICQ by the weaker MPEC-MFCQ. This mission formalizes that theorem.

Setting

The MPEC (1) is

min⁡f(x)  s.t.  gi(x)≤0 (i≤m),  hi(x)=0 (i≤p),  Gi(x)≥0,  Hi(x)≥0,  Gi(x)Hi(x)=0 (i≤l),\min f(x)\ \ \text{s.t.}\ \ g_i(x)\le0\ (i\le m),\ \ h_i(x)=0\ (i\le p),\ \ G_i(x)\ge0,\ \ H_i(x)\ge0,\ \ G_i(x)H_i(x)=0\ (i\le l),minf(x)  s.t.  gi​(x)≤0 (i≤m),  hi​(x)=0 (i≤p),  Gi​(x)≥0,  Hi​(x)≥0,  Gi​(x)Hi​(x)=0 (i≤l),

with continuously differentiable f,gi,hi,Gi,Hi:Rn→Rf,g_i,h_i,G_i,H_i:\mathbb R^n\to\mathbb Rf,gi​,hi​,Gi​,Hi​:Rn→R and feasible set XXX. For a point x∗x^*x∗ the paper uses the index sets Ig={i∣gi(x∗)=0}I_g=\{i\mid g_i(x^*)=0\}Ig​={i∣gi​(x∗)=0}, I0+={i∣Gi(x∗)=0<Hi(x∗)}I_{0+}=\{i\mid G_i(x^*)=0<H_i(x^*)\}I0+​={i∣Gi​(x∗)=0<Hi​(x∗)}, I00={i∣Gi(x∗)=Hi(x∗)=0}I_{00}=\{i\mid G_i(x^*)=H_i(x^*)=0\}I00​={i∣Gi​(x∗)=Hi​(x∗)=0} and I+0={i∣Gi(x∗)>0=Hi(x∗)}I_{+0}=\{i\mid G_i(x^*)>0=H_i(x^*)\}I+0​={i∣Gi​(x∗)>0=Hi​(x∗)}.

A standard nonlinear program has constraints gi≤0g_i\le0gi​≤0, hj=0h_j=0hj​=0. Its point xxx satisfies the Mangasarian–Fromovitz constraint qualification (MFCQ) if the gradients ∇hj(x)\nabla h_j(x)∇hj​(x) are linearly independent and some direction ddd has ∇gi(x)Td<0\nabla g_i(x)^Td<0∇gi​(x)Td<0 for all active iii and ∇hj(x)Td=0\nabla h_j(x)^Td=0∇hj​(x)Td=0 for all jjj. A stationary point is the xxx-part of a KKT point: xxx is feasible and there are λ≥0\lambda\ge0λ≥0, μ\muμ with λigi(x)=0\lambda_ig_i(x)=0λi​gi​(x)=0 and ∇f(x)+∑λi∇gi(x)+∑μj∇hj(x)=0\nabla f(x)+\sum\lambda_i\nabla g_i(x)+\sum\mu_j\nabla h_j(x)=0∇f(x)+∑λi​∇gi​(x)+∑μj​∇hj​(x)=0.

The tightened program TNLP(x∗)(x^*)(x∗) keeps gi≤0g_i\le0gi​≤0, hi=0h_i=0hi​=0 and imposes Gi=0, Hi≥0G_i=0,\ H_i\ge0Gi​=0, Hi​≥0 on I0+I_{0+}I0+​, Gi≥0, Hi=0G_i\ge0,\ H_i=0Gi​≥0, Hi​=0 on I+0I_{+0}I+0​, and Gi=Hi=0G_i=H_i=0Gi​=Hi​=0 on I00I_{00}I00​. MPEC-MFCQ holds at x∗x^*x∗ if MFCQ holds at x∗x^*x∗ for TNLP(x∗)(x^*)(x∗).

A feasible x∗x^*x∗ is weakly stationary if there are multipliers λ∈Rm\lambda\in\mathbb R^mλ∈Rm, μ∈Rp\mu\in\mathbb R^pμ∈Rp, γ,ν∈Rl\gamma,\nu\in\mathbb R^lγ,ν∈Rl with

∇f(x∗)+∑i=1mλi∇gi(x∗)+∑i=1pμi∇hi(x∗)−∑i=1lγi∇Gi(x∗)−∑i=1lνi∇Hi(x∗)=0,\nabla f(x^*)+\sum_{i=1}^m\lambda_i\nabla g_i(x^*)+\sum_{i=1}^p\mu_i\nabla h_i(x^*)-\sum_{i=1}^l\gamma_i\nabla G_i(x^*)-\sum_{i=1}^l\nu_i\nabla H_i(x^*)=0,∇f(x∗)+i=1∑m​λi​∇gi​(x∗)+i=1∑p​μi​∇hi​(x∗)−i=1∑l​γi​∇Gi​(x∗)−i=1∑l​νi​∇Hi​(x∗)=0,

λ≥0\lambda\ge0λ≥0, λigi(x∗)=0\lambda_ig_i(x^*)=0λi​gi​(x∗)=0, γi=0\gamma_i=0γi​=0 on I+0I_{+0}I+0​ and νi=0\nu_i=0νi​=0 on I0+I_{0+}I0+​. It is C-stationary if such multipliers can be chosen with, in addition, γiνi≥0\gamma_i\nu_i\ge0γi​νi​≥0 for all i∈I00i\in I_{00}i∈I00​.

Scholtes' relaxed program RS(t)R^S(t)RS(t) replaces Gi(x)Hi(x)=0G_i(x)H_i(x)=0Gi​(x)Hi​(x)=0 by Gi(x)Hi(x)≤tG_i(x)H_i(x)\le tGi​(x)Hi​(x)≤t and keeps all other constraints of (1). The notation {tk}↓0\{t_k\}\downarrow0{tk​}↓0 means a sequence of positive parameters decreasing to 000.

Formalization targets

Goal: Theorem 3.1

Let {tk}↓0\{t_k\}\downarrow0{tk​}↓0, let xkx^kxk be a stationary point of RS(tk)R^S(t_k)RS(tk​), and let xk→x∗x^k\to x^*xk→x∗ with MPEC-MFCQ at x∗x^*x∗. Then

x∗ is a C-stationary point of the MPEC (1).x^*\ \text{is a C-stationary point of the MPEC (1).}x∗ is a C-stationary point of the MPEC (1).

No feasibility of x∗x^*x∗ is assumed; it is part of the conclusion.

Milestones

  1. Remark 2.2: for a feasible point of a standard NLP, MFCQ holds if and only if the active inequality gradients together with all equality gradients are positive-linearly independent.
  2. §2.2, pp. 6–7: MPEC-MFCQ written out explicitly, i.e. linear independence of ∇hi\nabla h_i∇hi​, ∇Gi\nabla G_i∇Gi​ (I00∪I0+I_{00}\cup I_{0+}I00​∪I0+​) and ∇Hi\nabla H_i∇Hi​ (I00∪I+0I_{00}\cup I_{+0}I00​∪I+0​), plus a direction ddd.
  3. Proof of Theorem 3.2, p. 11: MPEC-MFCQ implies positive-linear independence of {∇gi(x∗)}Ig∪{{∇hi}∪{∇Gi}I00∪I0+∪{∇Hi}I00∪I+0}\{\nabla g_i(x^*)\}_{I_g}\cup\{\{\nabla h_i\}\cup\{\nabla G_i\}_{I_{00}\cup I_{0+}}\cup\{\nabla H_i\}_{I_{00}\cup I_{+0}}\}{∇gi​(x∗)}Ig​​∪{{∇hi​}∪{∇Gi​}I00​∪I0+​​∪{∇Hi​}I00​∪I+0​​}.
  4. Proof of Theorem 3.1, p. 9: for large kkk, Ig(xk)⊆IgI_g(x^k)\subseteq I_gIg​(xk)⊆Ig​, IG(xk)⊆I00∪I0+I_G(x^k)\subseteq I_{00}\cup I_{0+}IG​(xk)⊆I00​∪I0+​, IH(xk)⊆I00∪I+0I_H(x^k)\subseteq I_{00}\cup I_{+0}IH​(xk)⊆I00​∪I+0​.
  5. Proof of Theorem 3.1, pp. 10–11: under the goal's hypotheses, x∗x^*x∗ is weakly stationary.

Significance

Theorem 3.1 says that Scholtes' scheme, run to the limit, produces C-stationary points under a constraint qualification strictly weaker than the one in Scholtes' original result. MPEC-MFCQ is the natural assumption here: under it the KKT multipliers of the relaxed programs need not converge, and the theorem shows that a convergent subsequence of suitably modified multipliers still exists. The result is the first of a family of convergence theorems in the paper (the schemes of Lin–Fukushima, Kadrani–Dussault–Benchakroun and Steffensen–Ulbrich follow the same pattern) and the baseline against which those schemes are compared.

The theorem is proved in the paper; it is not open. To the extent a search of the Prove2Me catalog shows, no MPEC stationarity concept, MPEC constraint qualification or relaxation result has been formalized there, and Mathlib has no theory of constraint qualifications for nonlinear programs. The mission produces a machine-checked proof of Theorem 3.1 and, along the way, reusable statements of Definition 2.1, MFCQ, KKT points and the MFCQ/positive-linear-independence equivalence for general nonlinear programs.

Difficulty

The obvious argument takes a limit of the KKT multipliers of RS(tk)R^S(t_k)RS(tk​). That fails twice. First, under MPEC-MFCQ the multiplier sequence need not be bounded, so there may be nothing to take a limit of; boundedness has to be recovered from MPEC-MFCQ through positive-linear independence, a theorem of the alternative. Second, the multiplier δk\delta^kδk of the product constraint GiHi≤tkG_iH_i\le t_kGi​Hi​≤tk​ multiplies Hi∇Gi+Gi∇HiH_i\nabla G_i+G_i\nabla H_iHi​∇Gi​+Gi​∇Hi​, which is not a multiplier of ∇Gi\nabla G_i∇Gi​ or ∇Hi\nabla H_i∇Hi​ alone; how it is redistributed depends on whether iii lies in I0+I_{0+}I0+​, I+0I_{+0}I+0​ or I00I_{00}I00​, and the sign condition on I00I_{00}I00​ comes from the support disjointness between δk\delta^kδk and the multipliers of Gi≥0G_i\ge0Gi​≥0, Hi≥0H_i\ge0Hi​≥0, which uses tk>0t_k>0tk​>0. Compactness, index-set bookkeeping along a subsequence and continuity of all gradients have to be combined.

Formalization scope

  • Rn\mathbb R^nRn is EuclideanSpace ℝ (Fin n), gradients are Mathlib's gradient, and ∇g(x)Td\nabla g(x)^Td∇g(x)Td is the inner product. Constraint indices are Fin m, Fin p, Fin l (0-based); m,p,lm,p,lm,p,l may be 000.
  • The paper's standing assumption that all data are continuously differentiable (p. 1) is the explicit hypothesis P.IsC1 (ContDiff ℝ 1 for each function) of the goal and of milestones 4 and 5. Milestones 1–3 are pointwise linear algebra and assume no smoothness.
  • "Stationary point of RS(tk)R^S(t_k)RS(tk​)" is a KKT point of RS(tk)R^S(t_k)RS(tk​) viewed as a standard NLP with inequality constraints gi≤0g_i\le0gi​≤0, −Gi≤0-G_i\le0−Gi​≤0, −Hi≤0-H_i\le0−Hi​≤0, GiHi−t≤0G_iH_i-t\le0Gi​Hi​−t≤0: feasibility, nonnegative multipliers and complementary slackness are included (p. 5).
  • "{tk}↓0\{t_k\}\downarrow0{tk​}↓0" is tk>0t_k>0tk​>0 for all kkk, (tk)(t_k)(tk​) nonincreasing, and tk→0t_k\to0tk​→0.
  • Families of gradients are indexed families (repeated vectors count as dependent); in MPEC-MFCQ an index of I00I_{00}I00​ contributes both ∇Gi\nabla G_i∇Gi​ and ∇Hi\nabla H_i∇Hi​. TNLP(x∗)(x^*)(x∗) has constraints indexed by subtypes of the index sets; absent constraints are not padded by zero functions, which would make MPEC-MFCQ fail everywhere.
  • Definition 2.3(a) is printed with two misprints ("μihi(x∗)\mu_ih_i(x^*)μi​hi​(x∗)", "i=1,…,li=1,\dots,li=1,…,l" for the complementarity of λ\lambdaλ); the formalization uses μi∇hi(x∗)\mu_i\nabla h_i(x^*)μi​∇hi​(x∗) and i=1,…,mi=1,\dots,mi=1,…,m. C-stationarity requires feasibility and one multiplier tuple satisfying both the weak-stationarity conditions and the sign condition on I00I_{00}I00​.
  • A "stationary point" that is merely a feasible point or a critical point of fff, or a C-stationarity whose sign condition refers to multipliers other than those of the weak-stationarity equation, would make the goal false or empty; neither reading is used. The hypotheses of the goal are jointly satisfiable (checked on the paper's Example 3.6 instance).
  • Infrastructure needed: theorems of the alternative (Motzkin/Farkas) for finite families in Rn\mathbb R^nRn, compactness of normalised multiplier sequences, continuity of gradients of C1C^1C1 maps. The NLP layer (positive-linear dependence, MFCQ, KKT points, Remark 2.2) is reusable for any constraint-qualification development. Contributions of proofs of the milestones, of general NLP lemmas, and of the goal are welcome.

Selected references

  • T. Hoheisel, C. Kanzow, A. Schwartz, Theoretical and numerical comparison of relaxation methods for mathematical programs with complementarity constraints, Preprint 299, Institute of Mathematics, University of Würzburg, September 2010; published in Math. Program. 137 (2013) 257–288. doi:10.1007/s10107-011-0488-5
  • S. Scholtes, Convergence properties of a regularization scheme for mathematical programs with complementarity constraints, SIAM J. Optim. 11 (2001) 918–936. doi:10.1137/S1052623499361233
  • Z.-Q. Luo, J.-S. Pang, D. Ralph, Mathematical Programs with Equilibrium Constraints, Cambridge University Press, 1996. doi:10.1017/CBO9780511983658
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Functional AnalysisProbabilityStochastic Systems·Captain: mikedeng1

Affine Processes on Positive Semidefinite Matrices I: Every Affine Process on the PSD Cone Is Regular and Feller, with Generator (2.12) Given by an Admissible Parameter SetResearch Paper

Motivation

Matrix-valued affine processes on the cone of positive semidefinite matrices are used in finance as models of stochastic covariance: multi-asset option pricing with stochastic volatility and correlation, and fixed-income models with stochastically correlated risk factors and default intensities. The best-known example is the Wishart process of Bru (1991). What makes these models tractable is that the Laplace transform of the state is exponential-affine in the initial state, with exponents that solve ordinary differential equations of Riccati type.

Cuchiero, Filipović, Mayerhofer and Teichmann (2011) give the mathematical foundation: a complete characterization of stochastically continuous affine processes on Sd+S_d^+Sd+​ through an admissible parameter set. Their Theorem 2.4 has two halves. This mission formalizes the first, necessity, half: every affine process on Sd+S_d^+Sd+​ is regular and Feller, and its generator and Riccati equations are given by an admissible parameter set.

Timeline. Duffie, Filipović and Schachermayer (2003) characterized regular affine processes on the canonical state space R+m×Rn\mathbb R_+^m \times \mathbb R^nR+m​×Rn, assuming regularity. Keller-Ressel, Schachermayer and Teichmann showed that on that state space stochastic continuity already implies regularity. The 2011 paper carries both the characterization and the regularity result over to Sd+S_d^+Sd+​, a non-polyhedral cone with a curved boundary, on which the drift must satisfy the new condition b⪰(d−1)αb \succeq (d-1)\alphab⪰(d−1)α.

Setting

Let SdS_dSd​ be the space of real symmetric d×dd\times dd×d matrices with scalar product ⟨x,y⟩=Tr(xy)\langle x,y\rangle = \mathrm{Tr}(xy)⟨x,y⟩=Tr(xy) and norm ∥x∥=⟨x,x⟩1/2\|x\| = \langle x,x\rangle^{1/2}∥x∥=⟨x,x⟩1/2. Let Sd+S_d^+Sd+​ be the cone of positive semidefinite matrices and Sd++S_d^{++}Sd++​ its interior, and write x⪯yx \preceq yx⪯y when y−x∈Sd+y - x \in S_d^+y−x∈Sd+​.

A time-homogeneous Markov process XXX on Sd+S_d^+Sd+​ is described by sub-stochastic transition kernels pt(x,dξ)p_t(x,d\xi)pt​(x,dξ), t≥0t\ge 0t≥0. Mass that is lost goes to a cemetery state Δ\DeltaΔ. The kernels satisfy the Chapman–Kolmogorov equations, and the semigroup is Ptf(x)=∫f(ξ) pt(x,dξ)P_tf(x) = \int f(\xi)\,p_t(x,d\xi)Pt​f(x)=∫f(ξ)pt​(x,dξ). The process is affine (Definition 2.1) if it is stochastically continuous, i.e. ps(x,⋅)→pt(x,⋅)p_s(x,\cdot) \to p_t(x,\cdot)ps​(x,⋅)→pt​(x,⋅) weakly as s→ts \to ts→t, and if there are φ:R+×Sd+→R+\varphi : \mathbb R_+ \times S_d^+ \to \mathbb R_+φ:R+​×Sd+​→R+​ and ψ:R+×Sd+→Sd+\psi : \mathbb R_+\times S_d^+ \to S_d^+ψ:R+​×Sd+​→Sd+​ with

∫Sd+e−⟨u,ξ⟩ pt(x,dξ)=e−φ(t,u)−⟨ψ(t,u),x⟩,t≥0, u,x∈Sd+.\int_{S_d^+} e^{-\langle u,\xi\rangle}\,p_t(x,d\xi) = e^{-\varphi(t,u) - \langle\psi(t,u),x\rangle}, \qquad t\ge0,\ u,x\in S_d^+.∫Sd+​​e−⟨u,ξ⟩pt​(x,dξ)=e−φ(t,u)−⟨ψ(t,u),x⟩,t≥0, u,x∈Sd+​.

It is regular (Definition 2.2) if F(u)=∂tφ(t,u)∣t=0+F(u) = \partial_t\varphi(t,u)|_{t=0+}F(u)=∂t​φ(t,u)∣t=0+​ and R(u)=∂tψ(t,u)∣t=0+R(u) = \partial_t\psi(t,u)|_{t=0+}R(u)=∂t​ψ(t,u)∣t=0+​ exist and are continuous at u=0u=0u=0.

An admissible parameter set (α,b,βij,c,γ,m,μ)(\alpha, b, \beta^{ij}, c, \gamma, m, \mu)(α,b,βij,c,γ,m,μ), associated with a bounded continuous truncation function χ\chiχ (equal to the identity near 000), consists of:

  • a diffusion coefficient α∈Sd+\alpha \in S_d^+α∈Sd+​ and a constant drift b⪰(d−1)αb \succeq (d-1)\alphab⪰(d−1)α;
  • killing rates c≥0c \ge 0c≥0 and γ∈Sd+\gamma \in S_d^+γ∈Sd+​;
  • a jump measure mmm with ∫(∥ξ∥∧1) m(dξ)<∞\int(\|\xi\|\wedge1)\,m(d\xi)<\infty∫(∥ξ∥∧1)m(dξ)<∞;
  • a matrix μ\muμ of finite signed measures with μ(E)∈Sd+\mu(E) \in S_d^+μ(E)∈Sd+​, defining M(x,dξ)=⟨x,μ(dξ)⟩/(∥ξ∥2∧1)M(x,d\xi) = \langle x,\mu(d\xi)\rangle/(\|\xi\|^2\wedge1)M(x,dξ)=⟨x,μ(dξ)⟩/(∥ξ∥2∧1);
  • a linear drift B(x)=∑i,jβijxijB(x) = \sum_{i,j}\beta^{ij}x_{ij}B(x)=∑i,j​βijxij​.

These are subject to the boundary conditions (2.9) and (2.11) for x,u∈Sd+x,u \in S_d^+x,u∈Sd+​ with ⟨x,u⟩=0\langle x,u\rangle = 0⟨x,u⟩=0. The space S+\mathcal S_+S+​ consists of restrictions to Sd+S_d^+Sd+​ of rapidly decreasing smooth functions on SdS_dSd​.

Formalization targets

Goal: Theorem 2.4, first part

If XXX is affine on Sd+S_d^+Sd+​, then XXX is regular and Feller, S+\mathcal S_+S+​ lies in the domain of its generator A\mathcal AA on C0(Sd+)C_0(S_d^+)C0​(Sd+​), and there is an admissible parameter set such that for f∈S+f \in \mathcal S_+f∈S+​

Af(x)=12∑Aijkl(x) ∂ij∂klf(x)+∑(bij+Bij(x)) ∂ijf(x)−(c+⟨γ,x⟩)f(x)+∫(f(x+ξ)−f(x)) m(dξ)+∫(f(x+ξ)−f(x)−⟨χ(ξ),∇f(x)⟩) M(x,dξ),\mathcal Af(x) = \tfrac12\sum A_{ijkl}(x)\,\partial_{ij}\partial_{kl}f(x) + \sum (b_{ij}+B_{ij}(x))\,\partial_{ij}f(x) - (c+\langle\gamma,x\rangle)f(x) + \int (f(x+\xi)-f(x))\,m(d\xi) + \int \big(f(x+\xi)-f(x)-\langle\chi(\xi),\nabla f(x)\rangle\big)\,M(x,d\xi),Af(x)=21​∑Aijkl​(x)∂ij​∂kl​f(x)+∑(bij​+Bij​(x))∂ij​f(x)−(c+⟨γ,x⟩)f(x)+∫(f(x+ξ)−f(x))m(dξ)+∫(f(x+ξ)−f(x)−⟨χ(ξ),∇f(x)⟩)M(x,dξ),

with Aijkl(x)=xikαjl+xilαjk+xjkαil+xjlαikA_{ijkl}(x) = x_{ik}\alpha_{jl}+x_{il}\alpha_{jk}+x_{jk}\alpha_{il}+x_{jl}\alpha_{ik}Aijkl​(x)=xik​αjl​+xil​αjk​+xjk​αil​+xjl​αik​. In addition, φ,ψ\varphi,\psiφ,ψ solve ∂tφ=F(ψ)\partial_t\varphi = F(\psi)∂t​φ=F(ψ), φ(0,u)=0\varphi(0,u)=0φ(0,u)=0, ∂tψ=R(ψ)\partial_t\psi = R(\psi)∂t​ψ=R(ψ), ψ(0,u)=u\psi(0,u) = uψ(0,u)=u, with

F(u)=⟨b,u⟩+c−∫(e−⟨u,ξ⟩−1) m(dξ),R(u)=−2uαu+B⊤(u)+γ−∫e−⟨u,ξ⟩−1+⟨χ(ξ),u⟩∥ξ∥2∧1 μ(dξ).F(u) = \langle b,u\rangle + c - \int (e^{-\langle u,\xi\rangle}-1)\,m(d\xi),\qquad R(u) = -2u\alpha u + B^\top(u) + \gamma - \int \frac{e^{-\langle u,\xi\rangle}-1+\langle\chi(\xi),u\rangle}{\|\xi\|^2\wedge1}\,\mu(d\xi).F(u)=⟨b,u⟩+c−∫(e−⟨u,ξ⟩−1)m(dξ),R(u)=−2uαu+B⊤(u)+γ−∫∥ξ∥2∧1e−⟨u,ξ⟩−1+⟨χ(ξ),u⟩​μ(dξ).

Milestones, in attack order

  1. Lemma 3.1 and Lemma 3.3: order-preserving, continuous, analytic semiflows map Sd++S_d^{++}Sd++​ into Sd++S_d^{++}Sd++​.
  2. Lemma 3.2: semiflow identities, monotonicity, continuity and analyticity of φ,ψ\varphi,\psiφ,ψ.
  3. Proposition 3.4: Feller and regular.
  4. Lemmas 4.1 and 4.4: zero divisors in the cone, and linear extension of additive maps.
  5. Proposition 4.9: F,RF,RF,R have the form (2.16)–(2.17) with b∈Sd+b\in S_d^+b∈Sd+​.
  6. Lemma B.2 and Theorem B.3: exponentials lie in S+\mathcal S_+S+​ and span a dense subspace.
  7. Proposition 4.12: the generator formula (2.12) on S+\mathcal S_+S+​.
  8. Lemma 4.17 and Proposition 4.18: derivatives of det⁡\detdet at diagonal matrices, and the drift condition b⪰(d−1)αb\succeq(d-1)\alphab⪰(d−1)α.

Significance

The result. Theorem 2.4 reduces the study of affine processes on Sd+S_d^+Sd+​ to finitely many parameters. Any such process, a priori specified only through its Laplace transform, has the Lévy–Khintchine-type generator (2.12), its Laplace exponents solve the Riccati system, and its parameters obey the admissibility conditions. The drift condition b⪰(d−1)αb\succeq(d-1)\alphab⪰(d−1)α is the matrix analogue of the Feller condition, and for d≥2d\ge2d≥2 it excludes affine diffusions on Sd+S_d^+Sd+​ with zero constant drift. The Feller property yields càdlàg versions, and the generator formula is the starting point for the semimartingale description and for the converse existence result.

Formalizing it. The theorem is proved in the paper, and this mission produces a machine-checked version of the necessity direction. Along the way it builds reusable infrastructure: a Lean model of Markov transition families on a cone, Feller semigroups on C0C_0C0​ of a closed cone, generators on Schwartz-type test spaces with the symmetric-matrix derivative convention, and the positive semidefinite cone's order and boundary facts. No machine-checked proof of this theorem, or of its R+m×Rn\mathbb R_+^m\times\mathbb R^nR+m​×Rn predecessor, is known to exist.

Difficulty

The definition assumes only stochastic continuity and the exponential-affine form of the Laplace transform; differentiability in time is not given. Obtaining regularity, and hence the Riccati equations, needs the positivity statement of Lemma 3.3. Its proof uses analyticity in uuu and the boundary geometry of Sd+S_d^+Sd+​. Identifying FFF and RRR requires Lévy–Khintchine representations on cones and on SdS_dSd​, and a convergence theorem for Laplace transforms. The admissibility conditions on the boundary come from support considerations at each boundary point. The drift condition (2.4) is not captured by the conditions read off from Laplace exponents at boundary points along single directions; it is a genuinely matrix-valued constraint coupling bbb and α\alphaα. Extending the generator formula from exponentials to all of S+\mathcal S_+S+​ needs a density result in a Fréchet topology and the closedness of the generator.

Formalization scope

  • Matrices are Fin d → Fin d → ℝ, with ⟨x,y⟩=∑xijyji\langle x,y\rangle=\sum x_{ij}y_{ji}⟨x,y⟩=∑xij​yji​ and ∥x∥=⟨x,x⟩1/2\|x\|=\langle x,x\rangle^{1/2}∥x∥=⟨x,x⟩1/2. Mathlib's positive semidefiniteness, which includes symmetry over R\mathbb RR, defines Sd+S_d^+Sd+​. The state space is the subtype Sd+S_d^+Sd+​ with its subspace topology and Borel σ\sigmaσ-algebra.
  • Transition families are Mathlib kernels indexed by t∈Rt\in\mathbb Rt∈R and constrained only for t≥0t\ge0t≥0. Sub-stochasticity encodes the cemetery. Stochastic continuity is convergence of integrals of bounded continuous functions as s→ts\to ts→t within [0,∞)[0,\infty)[0,∞).
  • The exponents φ,ψ\varphi,\psiφ,ψ are functions on R×Md\mathbb R\times M_dR×Md​, used at t≥0t\ge0t≥0 and positive semidefinite arguments. Analyticity on Sd++S_d^{++}Sd++​ is analyticity of y↦ψ(t,(y+y⊤)/2)y\mapsto\psi(t,(y+y^\top)/2)y↦ψ(t,(y+y⊤)/2) on an open subset of MdM_dMd​.
  • The matrix measure μ\muμ is encoded as H dνH\,d\nuHdν with ν\nuν finite and HHH positive semidefinite and integrable. This loses nothing, since ν=∑iμii\nu = \sum_i\mu_{ii}ν=∑i​μii​ dominates every μij\mu_{ij}μij​.
  • S+\mathcal S_+S+​ is the set of restrictions of Schwartz functions on MdM_dMd​. Partial derivatives ∂/∂xij\partial/\partial x_{ij}∂/∂xij​ of functions on SdS_dSd​ are taken in the direction 12(Eij+Eji)\tfrac12(E^{ij}+E^{ji})21​(Eij+Eji), per §1.2 of the paper. Lemma 4.17 alone uses raw entry derivatives of det⁡\detdet on MdM_dMd​, as its proof does.
  • The Feller property uses the platform definition EthierKurtz.IsStronglyContinuousContractionSemigroup on C0(Sd+)C_0(S_d^+)C0​(Sd+​). "f∈D(A)f\in D(\mathcal A)f∈D(A) and Af=g\mathcal Af=gAf=g" is uniform convergence of (Ptf−f)/t(P_tf-f)/t(Pt​f−f)/t to ggg on Sd+S_d^+Sd+​.
  • Lean assigns the value 000 to the integral of a non-integrable function. Wherever a statement concludes a formula containing an integral, it therefore also concludes integrability of the integrand, so the formula cannot hold through this default value. Regularity and the Feller property are conclusions, never hypotheses, of the goal. The drift condition (2.4) is part of admissibility in the goal; Propositions 4.9, 4.12 and 4.18 use admissibility without (2.4) and b∈Sd+b\in S_d^+b∈Sd+​, as in the paper.
  • Contributions are welcome on any milestone. The matrix lemmas (3.1, 3.3, 4.1, 4.4, 4.17) are self-contained, and Lemma B.2 and Theorem B.3 concern only Schwartz functions.

Selected references

  • C. Cuchiero, D. Filipović, E. Mayerhofer, J. Teichmann, Affine processes on positive semidefinite matrices, Ann. Appl. Probab. 21 (2011) 397–463; cited as arXiv:0910.0137v3. https://arxiv.org/abs/0910.0137
  • D. Duffie, D. Filipović, W. Schachermayer, Affine processes and applications in finance, Ann. Appl. Probab. 13 (2003) 984–1053. https://doi.org/10.1214/aoap/1060202833
  • M. Keller-Ressel, W. Schachermayer, J. Teichmann, Affine processes are regular, Probab. Theory Related Fields 151 (2011) 591–611. https://arxiv.org/abs/0906.3392
  • M.-F. Bru, Wishart processes, J. Theoret. Probab. 4 (1991) 725–751. https://doi.org/10.1007/BF01259552
18 thms2 active usersReviewed
Linear algebraMachine LearningStatistics·Captain: mikedeng1

Nuclear-Norm Penalization and Optimal Rates for Noisy Low-Rank Matrix Completion 4: The Estimator Never Overestimates rank(A₀), Recovers It Above a Singular-Value Gap, and Obeys a Matching Lower BoundResearch Paper

Motivation

Noisy low-rank matrix completion asks to reconstruct an m1×m2m_1\times m_2m1​×m2​ matrix A0A_0A0​ from nnn noisy observations of randomly chosen entries. It is the statistical model behind collaborative filtering (recommender systems), sensor localization and system identification, and the nuclear-norm penalized least-squares estimator is its standard convex method. Koltchinskii, Lounici and Tsybakov (arXiv:1011.6256v4, Ann. Statist. 2011) proved sharp oracle inequalities for this estimator and showed that its Frobenius error is of order rank⁡(A0)(m1∨m2)log⁡(m1+m2)/n\operatorname{rank}(A_0)(m_1\vee m_2)\log(m_1+m_2)/nrank(A0​)(m1​∨m2​)log(m1​+m2​)/n up to normalization, which matches the minimax lower bound up to a logarithmic factor.

An upper bound alone does not say whether the estimator really attains this rate on a given matrix, nor whether it reports the correct rank. Section 5.1 of the paper answers both questions with a single deterministic theorem, Theorem 8: with a slightly inflated regularization parameter the estimator never overestimates the rank of A0A_0A0​; if the nonzero singular values of A0A_0A0​ are separated from zero it recovers the rank exactly, and its error is then bounded below by a quantity of the same order as the upper bounds. Rank recovery is the property practitioners rely on when they use the estimator for model selection (choosing the number of latent factors). This mission formalizes Theorem 8 and the steps of its proof.

Setting

Fix integers m1,m2,n≥1m_1,m_2,n\ge1m1​,m2​,n≥1. The matrix completion basis is X={ej(m1)ek(m2)⊤}\mathcal X=\{e_j(m_1)e_k(m_2)^\top\}X={ej​(m1​)ek​(m2​)⊤}, the m1m2m_1m_2m1​m2​ matrices with a single entry equal to 111. A sample consists of nnn pairs (Xi,Yi)(X_i,Y_i)(Xi​,Yi​) with Xi∈XX_i\in\mathcal XXi​∈X (an observed position (ji,ki)(j_i,k_i)(ji​,ki​)) and Yi∈RY_i\in\mathbb RYi​∈R (a noisy observation of the corresponding entry of the unknown matrix A0A_0A0​). Write ⟨A,B⟩=tr⁡(A⊤B)\langle A,B\rangle=\operatorname{tr}(A^\top B)⟨A,B⟩=tr(A⊤B), ∥A∥2\|A\|_2∥A∥2​ for the Frobenius norm, ∥A∥1\|A\|_1∥A∥1​ for the nuclear norm (the sum of the singular values) and ∥A∥∞\|A\|_\infty∥A∥∞​ for the operator norm (the largest singular value). The singular values of BBB are σ1(B)≥σ2(B)≥⋯≥σm1∧m2(B)≥0\sigma_1(B)\ge\sigma_2(B)\ge\dots\ge\sigma_{m_1\wedge m_2}(B)\ge0σ1​(B)≥σ2​(B)≥⋯≥σm1​∧m2​​(B)≥0.

From the sample form

X=m1m2n∑i=1nYiXi,M=1n∑i=1n(YiXi−E(YiXi)).\mathbf X=\frac{m_1m_2}{n}\sum_{i=1}^nY_iX_i,\qquad \mathbf M=\frac1n\sum_{i=1}^n\big(Y_iX_i-\mathbb E(Y_iX_i)\big).X=nm1​m2​​i=1∑n​Yi​Xi​,M=n1​i=1∑n​(Yi​Xi​−E(Yi​Xi​)).

In the paper's model E(Yi∣Xi)=⟨A0,Xi⟩\mathbb E(Y_i\mid X_i)=\langle A_0,X_i\rangleE(Yi​∣Xi​)=⟨A0​,Xi​⟩ with XiX_iXi​ uniform on X\mathcal XX, so E(YiXi)=A0/(m1m2)\mathbb E(Y_iX_i)=A_0/(m_1m_2)E(Yi​Xi​)=A0​/(m1​m2​) and X−A0=m1m2M\mathbf X-A_0=m_1m_2\mathbf MX−A0​=m1​m2​M: the matrix M\mathbf MM is the stochastic error. For λ>0\lambda>0λ>0 the estimator (3.1) is

A^λ=argmin⁡A∈Rm1×m2(∥A−X∥22+λm1m2∥A∥1).\hat A^\lambda=\operatorname{argmin}_{A\in\mathbb R^{m_1\times m_2}}\Big(\|A-\mathbf X\|_2^2+\lambda m_1m_2\|A\|_1\Big).A^λ=argminA∈Rm1​×m2​​(∥A−X∥22​+λm1​m2​∥A∥1​).

The objective is strictly convex, so the minimizer is unique; by (3.2) it is obtained from a singular value decomposition of X\mathbf XX by soft thresholding every singular value at level λm1m2/2\lambda m_1m_2/2λm1​m2​/2.

Formalization targets

Goal: Theorem 8 (p. 20)

Let λ≥2∥M∥∞\lambda\ge2\|\mathbf M\|_\inftyλ≥2∥M∥∞​, 0<δ<10<\delta<10<δ<1 and λ′=λ/(1−δ)\lambda'=\lambda/(1-\delta)λ′=λ/(1−δ), and put r^=rank⁡(A^λ′)\hat r=\operatorname{rank}(\hat A^{\lambda'})r^=rank(A^λ′). Then

r^≤rank⁡(A0).(5.1)\hat r\le\operatorname{rank}(A_0).\tag{5.1}r^≤rank(A0​).(5.1)

If in addition min⁡j:σj(A0)≠0σj(A0)≥λ′m1m2\min_{j:\sigma_j(A_0)\ne0}\sigma_j(A_0)\ge\lambda'm_1m_2minj:σj​(A0​)=0​σj​(A0​)≥λ′m1​m2​, then

r^≥rank⁡(A0)(5.2)\hat r\ge\operatorname{rank}(A_0)\tag{5.2}r^≥rank(A0​)(5.2)

and

∥A^λ′−A0∥22≥δ24(1−δ)2rank⁡(A0) (λm1m2)2.(5.3)\|\hat A^{\lambda'}-A_0\|_2^2\ge\frac{\delta^2}{4(1-\delta)^2}\operatorname{rank}(A_0)\,(\lambda m_1m_2)^2.\tag{5.3}∥A^λ′−A0​∥22​≥4(1−δ)2δ2​rank(A0​)(λm1​m2​)2.(5.3)

Milestones

The milestones follow the proof on p. 20 in order:

  1. the singular value perturbation display ∣σj(X)−σj(A0)∣≤σ1(X−A0)=m1m2∥M∥∞≤λm1m2/2|\sigma_j(\mathbf X)-\sigma_j(A_0)|\le\sigma_1(\mathbf X-A_0)=m_1m_2\|\mathbf M\|_\infty\le\lambda m_1m_2/2∣σj​(X)−σj​(A0​)∣≤σ1​(X−A0​)=m1​m2​∥M∥∞​≤λm1​m2​/2;
  2. the rank of A^λ\hat A^\lambdaA^λ equals the number of singular values of X\mathbf XX above λm1m2/2\lambda m_1m_2/2λm1​m2​/2 (the consequence of (3.2) the proof uses);
  3. (5.1);
  4. (5.2);
  5. ∥P(A^λ′−X)∥2=r λ′m1m2/2\|\mathcal P(\hat A^{\lambda'}-\mathbf X)\|_2=\sqrt r\,\lambda'm_1m_2/2∥P(A^λ′−X)∥2​=r​λ′m1​m2​/2 when r^=r\hat r=rr^=r, for the projector P\mathcal PP onto the span of the top rrr singular pairs uj(X)vj(X)⊤u_j(\mathbf X)v_j(\mathbf X)^\topuj​(X)vj​(X)⊤;
  6. ∥P(X−A0)∥2≤r∥M∥∞m1m2≤rλm1m2/2\|\mathcal P(\mathbf X-A_0)\|_2\le\sqrt r\|\mathbf M\|_\infty m_1m_2\le\sqrt r\lambda m_1m_2/2∥P(X−A0​)∥2​≤r​∥M∥∞​m1​m2​≤r​λm1​m2​/2.

Significance

The result. Theorem 8 turns the paper's upper bounds into two-sided statements. Combined with a probability bound for ∥M∥∞\|\mathbf M\|_\infty∥M∥∞​ (Corollary 3 of the paper), it shows that with high probability the estimator selects the true rank and that its error on well-conditioned low-rank matrices is not smaller than the rate of the upper bounds, so those bounds cannot be improved for this estimator. Because the theorem is deterministic given the event λ≥2∥M∥∞\lambda\ge2\|\mathbf M\|_\inftyλ≥2∥M∥∞​, it applies unchanged to any noise model for which such a bound on the stochastic error is available.

Formalizing it. The theorem is proved in the paper; nothing in it is open. The mission produces a machine-checked version and, along the way, reusable linear algebra that is not on the platform in this form: Weyl's perturbation inequality for singular values in operator norm, the rank of a nuclear-norm proximal point, and the Frobenius norm of a projection onto a span of orthonormal rank-one matrices. The soft-thresholding representation (3.2) itself is the open platform item CaiCandesShen.Convergence.shrink_eq_prox (Cai–Candès–Shen, Theorem 2.1, after halving the objective); this mission references it rather than posing it again, and a proof of it would serve both missions.

Difficulty

The arithmetic of the proof is three lines; the content is in two facts about singular values that the paper takes from the literature. The first is Weyl's inequality ∣σj(B)−σj(C)∣≤∥B−C∥∞|\sigma_j(B)-\sigma_j(C)|\le\|B-C\|_\infty∣σj​(B)−σj​(C)∣≤∥B−C∥∞​, which needs the min–max (Courant–Fischer) characterization of singular values; Mathlib defines singular values through the eigenvalues of T∗TT^*TT∗T but has neither the min–max principle for them nor this inequality. The second is the description of the minimizer of ∥A−X∥22+λm1m2∥A∥1\|A-\mathbf X\|_2^2+\lambda m_1m_2\|A\|_1∥A−X∥22​+λm1​m2​∥A∥1​: one needs the subdifferential of the nuclear norm (2.1), or an equivalent von Neumann trace inequality, to show that soft thresholding is optimal, and then that its rank and its projection onto the top singular pairs are what the formula suggests. A naive approach that compares the estimator with X\mathbf XX entrywise gives nothing about the rank; the proof needs the spectral structure.

Formalization scope

Matrices are MatrixCompletion.RealMatrix m₁ m₂ (Matrix (Fin m₁) (Fin m₂) ℝ) with the published norms frobeniusNormSq, frobeniusNorm, nuclearNorm, spectralNorm and SVD data SVD. Singular values are Mathlib's LinearMap.singularValues of Matrix.toEuclideanLin, 0-based: the Lean singularValue B j is the paper's σj+1(B)\sigma_{j+1}(B)σj+1​(B). The conventions committed to:

  • The statements are realization-wise: positions idx : Fin n → Fin m₁ × Fin m₂ and responses y : Fin n → ℝ are fixed, and every theorem holds for every data set satisfying λ≥2∥M∥∞\lambda\ge2\|\mathbf M\|_\inftyλ≥2∥M∥∞​. The matrix M\mathbf MM is written as 1n∑iYiXi−A0/(m1m2)\frac1n\sum_iY_iX_i-A_0/(m_1m_2)n1​∑i​Yi​Xi​−A0​/(m1​m2​), which is (2.2) under the model (1.1) and the uniform design; this is the paper's "Note that X−A0=m1m2M\mathbf X-A_0=m_1m_2\mathbf MX−A0​=m1​m2​M". The probabilistic hypotheses are used for nothing else.
  • n,m1,m2≥1n,m_1,m_2\ge1n,m1​,m2​≥1 and λ>0\lambda>0λ>0 are assumed, as in the paper.
  • The estimator is any minimizer of (3.1) over all matrices, never the soft-thresholding formula; replacing the minimizer by formula (3.2) would assume the open Cai–Candès–Shen item.
  • min⁡j:σj(A0)≠0σj(A0)≥λ′m1m2\min_{j:\sigma_j(A_0)\ne0}\sigma_j(A_0)\ge\lambda'm_1m_2minj:σj​(A0​)=0​σj​(A0​)≥λ′m1​m2​ is written "for every jjj with σj(A0)≠0\sigma_j(A_0)\ne0σj​(A0​)=0"; for A0=0A_0=0A0​=0 it is vacuous, as on the page. No real infimum over a possibly empty set is used.
  • The projector P\mathcal PP is built from a singular value decomposition of X\mathbf XX carried as data, with decreasing singular values, from its first rrr pairs.

No printed slip was found in Theorem 8 or its proof; no hypothesis beyond the above is added.

Contributions welcome: Weyl's inequality for singular values (generally useful), the rank and top-rrr projection of the nuclear-norm proximal point, and a proof of CaiCandesShen.Convergence.shrink_eq_prox.

The source is the arXiv preprint arXiv:1011.6256v4; all page and display numbers refer to it.

Selected references

  • V. Koltchinskii, K. Lounici, A. B. Tsybakov, Nuclear-norm penalization and optimal rates for noisy low-rank matrix completion, Ann. Statist. 39(5), 2011; preprint arXiv:1011.6256v4. https://arxiv.org/abs/1011.6256
  • J.-F. Cai, E. J. Candès, Z. Shen, A singular value thresholding algorithm for matrix completion, SIAM J. Optim. 20(4), 2010. https://doi.org/10.1137/080738970
  • G. W. Stewart, J.-G. Sun, Matrix Perturbation Theory, Academic Press, 1990 (reference [25] of the paper, p. 203).
  • E. J. Candès, Y. Plan, Matrix completion with noise, Proc. IEEE 98(6), 2010. https://doi.org/10.1109/JPROC.2009.2035722
13 thms2 active usersReviewed
Numerical AnalysisProbabilityStochastic Systems·Captain: mikedeng1

A Regression-Based Monte Carlo Method to Solve Backward Stochastic Differential Equations I: Projection Errors of the Picard–Regression Scheme Accumulate AdditivelyResearch Paper

Motivation

A backward stochastic differential equation (BSDE) prescribes the value of a process at a terminal time and asks for an adapted process that reaches it while following a given drift. In mathematical finance the price of a contingent claim, and its hedging strategy, solve such an equation; when the market has frictions (different borrowing and lending rates, for example) the drift, called the driver, is nonlinear and no closed form exists. Numerical methods for BSDEs are therefore methods for pricing and hedging under nonlinear models, and also for semilinear parabolic PDEs, which BSDEs represent probabilistically.

Gobet, Lemor and Warin (Ann. Appl. Probab. 15 (2005), arXiv:math/0508491) proposed and analysed a simulation scheme in which every conditional expectation of a backward time-stepping recursion is replaced by a least-squares regression on finitely many functions, as in the Longstaff–Schwartz method for American options. Their analysis splits the total error into three parts: time discretization (Theorem 1, from Zhang's results), replacing conditional expectations by L2\mathbf L_2L2​ projections on function bases (Theorem 2), and replacing those projections by empirical regressions on MMM simulated paths (Theorem 3). This mission formalizes the second part.

Timeline. Zhang (Ann. Appl. Probab. 14 (2004)) and Bouchard and Touzi (Stoch. Proc. Appl. 111 (2004)) established the h\sqrt hh​ rate of the time discretization. Bouchard and Touzi's regression error (their reference [6] in the paper, Theorem 4.1 there) was expressed through the residuals of the scheme's own iterates. Gobet, Lemor and Warin (2005) gave the bound in terms of the residuals of the discrete BSDE, together with estimates on ZZZ.

Setting

Fix a horizon T>0T>0T>0, dimensions d,q≥1d,q\ge1d,q≥1, a drift b(t,x)∈Rdb(t,x)\in\mathbb R^db(t,x)∈Rd and a diffusion matrix σ(t,x)∈Rd×q\sigma(t,x)\in\mathbb R^{d\times q}σ(t,x)∈Rd×q, both Lipschitz in (t,x)(t,x)(t,x) ((H1)), and a driver f(t,x,y,z)∈Rf(t,x,y,z)\in\mathbb Rf(t,x,y,z)∈R with

∣f(t2,x2,y2,z2)−f(t1,x1,y1,z1)∣≤Cf(∣t2−t1∣1/2+∣x2−x1∣+∣y2−y1∣+∣z2−z1∣)(H2).|f(t_2,x_2,y_2,z_2)-f(t_1,x_1,y_1,z_1)|\le C_f\big(|t_2-t_1|^{1/2}+|x_2-x_1|+|y_2-y_1|+|z_2-z_1|\big)\qquad\textbf{(H2)}.∣f(t2​,x2​,y2​,z2​)−f(t1​,x1​,y1​,z1​)∣≤Cf​(∣t2​−t1​∣1/2+∣x2​−x1​∣+∣y2​−y1​∣+∣z2​−z1​∣)(H2).

For N≥1N\ge1N≥1 put h=T/Nh=T/Nh=T/N and tk=kht_k=khtk​=kh. On a probability space with a filtration (Fk)(\mathcal F_k)(Fk​), the increments ΔWk∈Rq\Delta W_k\in\mathbb R^qΔWk​∈Rq are Fk+1\mathcal F_{k+1}Fk+1​-measurable, independent of Fk\mathcal F_kFk​ and Gaussian N(0,hIq)\mathcal N(0,hI_q)N(0,hIq​); ΔWl,k\Delta W_{l,k}ΔWl,k​ is the lll-th component. The Euler scheme is St0N=S0S^N_{t_0}=S_0St0​N​=S0​, Stk+1N=StkN+b(tk,StkN)h+σ(tk,StkN)ΔWkS^N_{t_{k+1}}=S^N_{t_k}+b(t_k,S^N_{t_k})h+\sigma(t_k,S^N_{t_k})\Delta W_kStk+1​N​=Stk​N​+b(tk​,Stk​N​)h+σ(tk​,Stk​N​)ΔWk​. An Fk\mathcal F_kFk​-adapted process PtkN∈Rd′P^N_{t_k}\in\mathbb R^{d'}Ptk​N​∈Rd′ extends StkNS^N_{t_k}Stk​N​ by extra state variables, and the terminal value is ΦN(PtNN)\Phi^N(P^N_{t_N})ΦN(PtN​N​), square integrable.

Write Ek=E(⋅∣Fk)\mathbb E_k=\mathbb E(\cdot\mid\mathcal F_k)Ek​=E(⋅∣Fk​). The discrete BSDE is YtNN=ΦN(PtNN)Y^N_{t_N}=\Phi^N(P^N_{t_N})YtN​N​=ΦN(PtN​N​) and, for k<Nk<Nk<N,

Zl,tkN=1hEk(Ytk+1NΔWl,k),YtkN=Ek(Ytk+1N)+hf(tk,StkN,YtkN,ZtkN).Z^N_{l,t_k}=\tfrac1h\mathbb E_k(Y^N_{t_{k+1}}\Delta W_{l,k}),\qquad Y^N_{t_k}=\mathbb E_k(Y^N_{t_{k+1}})+hf(t_k,S^N_{t_k},Y^N_{t_k},Z^N_{t_k}).Zl,tk​N​=h1​Ek​(Ytk+1​N​ΔWl,k​),Ytk​N​=Ek​(Ytk+1​N​)+hf(tk​,Stk​N​,Ytk​N​,Ztk​N​).

A function basis pl,k(PtkN)∈Rnl,kp_{l,k}(P^N_{t_k})\in\mathbb R^{n_{l,k}}pl,k​(Ptk​N​)∈Rnl,k​ (0≤l≤q0\le l\le q0≤l≤q) is square integrable with invertible Gram matrix E(pl,kpl,k∗)\mathbb E(p_{l,k}p_{l,k}^*)E(pl,k​pl,k∗​). Pp(U)\mathcal P_{p}(U)Pp​(U) is the L2(Ω,P)\mathbf L_2(\Omega,\mathbb P)L2​(Ω,P) orthogonal projection of UUU onto the span of the basis, and Rp(U)=U−Pp(U)\mathcal R_p(U)=U-\mathcal P_p(U)Rp​(U)=U−Pp​(U).

The projection–Picard scheme with III iterations (Definition 1) produces YtkN,i,I=α0,ki,I⋅p0,kY^{N,i,I}_{t_k}=\alpha^{i,I}_{0,k}\cdot p_{0,k}Ytk​N,i,I​=α0,ki,I​⋅p0,k​ and Zl,tkN,i,I=αl,ki,I⋅pl,kZ^{N,i,I}_{l,t_k}=\alpha^{i,I}_{l,k}\cdot p_{l,k}Zl,tk​N,i,I​=αl,ki,I​⋅pl,k​, starting from α0,I=0\alpha^{0,I}=0α0,I=0, where αki,I\alpha^{i,I}_kαki,I​ minimizes

E(Ytk+1N,I,I−α0⋅p0,k+hf(tk,StkN,YtkN,i−1,I,ZtkN,i−1,I)−∑l=1qαl⋅pl,kΔWl,k)2.(9)\mathbb E\Big(Y^{N,I,I}_{t_{k+1}}-\alpha_0\cdot p_{0,k}+hf(t_k,S^N_{t_k},Y^{N,i-1,I}_{t_k},Z^{N,i-1,I}_{t_k})-\sum_{l=1}^q\alpha_l\cdot p_{l,k}\Delta W_{l,k}\Big)^2.\qquad(9)E(Ytk+1​N,I,I​−α0​⋅p0,k​+hf(tk​,Stk​N​,Ytk​N,i−1,I​,Ztk​N,i−1,I​)−l=1∑q​αl​⋅pl,k​ΔWl,k​)2.(9)

Finally AN(S0)=1+∣S0∣2+E∣ΦN(PtNN)∣2\mathcal A^N(S_0)=1+|S_0|^2+\mathbb E|\Phi^N(P^N_{t_N})|^2AN(S0​)=1+∣S0​∣2+E∣ΦN(PtN​N​)∣2.

Formalization targets

Goal: Theorem 2 (p. 11)

For hhh small enough,

max⁡0≤k≤NE∣YtkN,I,I−YtkN∣2+h∑k=0N−1E∣ZtkN,I,I−ZtkN∣2≤Ch2I−2AN(S0)+C∑k=0N−1E∣Rp0,k(YtkN)∣2+Ch∑k=0N−1∑l=1qE∣Rpl,k(Zl,tkN)∣2.\max_{0\le k\le N}\mathbb E|Y^{N,I,I}_{t_k}-Y^N_{t_k}|^2+h\sum_{k=0}^{N-1}\mathbb E|Z^{N,I,I}_{t_k}-Z^N_{t_k}|^2\le Ch^{2I-2}\mathcal A^N(S_0)+C\sum_{k=0}^{N-1}\mathbb E|\mathcal R_{p_{0,k}}(Y^N_{t_k})|^2+Ch\sum_{k=0}^{N-1}\sum_{l=1}^q\mathbb E|\mathcal R_{p_{l,k}}(Z^N_{l,t_k})|^2 .0≤k≤Nmax​E∣Ytk​N,I,I​−Ytk​N​∣2+hk=0∑N−1​E∣Ztk​N,I,I​−Ztk​N​∣2≤Ch2I−2AN(S0​)+Ck=0∑N−1​E∣Rp0,k​​(Ytk​N​)∣2+Chk=0∑N−1​l=1∑q​E∣Rpl,k​​(Zl,tk​N​)∣2.

Milestones

  1. (10)–(11): the minimizer of (9) is given by projections, Zl,tkN,i,I=1hPpl,k(Ytk+1N,I,IΔWl,k)Z^{N,i,I}_{l,t_k}=\frac1h\mathcal P_{p_{l,k}}(Y^{N,I,I}_{t_{k+1}}\Delta W_{l,k})Zl,tk​N,i,I​=h1​Ppl,k​​(Ytk+1​N,I,I​ΔWl,k​) and YtkN,i,I=Pp0,k(Ytk+1N,I,I+hf(…,YtkN,i−1,I,ZtkN,i−1,I))Y^{N,i,I}_{t_k}=\mathcal P_{p_{0,k}}(Y^{N,I,I}_{t_{k+1}}+hf(\dots,Y^{N,i-1,I}_{t_k},Z^{N,i-1,I}_{t_k}))Ytk​N,i,I​=Pp0,k​​(Ytk+1​N,I,I​+hf(…,Ytk​N,i−1,I​,Ztk​N,i−1,I​)).
  2. (12): h E∣Zl,tkN,i,I∣2≤E∣Ytk+1N,I,I∣2−E∣Ek(Ytk+1N,I,I)∣2h\,\mathbb E|Z^{N,i,I}_{l,t_k}|^2\le\mathbb E|Y^{N,I,I}_{t_{k+1}}|^2-\mathbb E|\mathbb E_k(Y^{N,I,I}_{t_{k+1}})|^2hE∣Zl,tk​N,i,I​∣2≤E∣Ytk+1​N,I,I​∣2−E∣Ek​(Ytk+1​N,I,I​)∣2.
  3. (13): the map Y↦Pp0,k(Ytk+1N,I,I+hf(tk,StkN,Y,ZtkN,I,I))Y\mapsto\mathcal P_{p_{0,k}}(Y^{N,I,I}_{t_{k+1}}+hf(t_k,S^N_{t_k},Y,Z^{N,I,I}_{t_k}))Y↦Pp0,k​​(Ytk+1​N,I,I​+hf(tk​,Stk​N​,Y,Ztk​N,I,I​)) is a (Cfh)(C_fh)(Cf​h)-contraction on L2(Fk)\mathbf L_2(\mathcal F_k)L2​(Fk​) with a unique fixed point.
  4. The discrete Gronwall lemma with ccc-terms (p. 11, item 3).
  5. (19): E∣YtkN,i,I∣2+h E∣Zl,tkN,i,I∣2≤CAN(S0)\mathbb E|Y^{N,i,I}_{t_k}|^2+h\,\mathbb E|Z^{N,i,I}_{l,t_k}|^2\le C\mathcal A^N(S_0)E∣Ytk​N,i,I​∣2+hE∣Zl,tk​N,i,I​∣2≤CAN(S0​), uniformly in III, iii, kkk.

Significance

Theorem 2 shows that the projection errors of a backward regression scheme only add up over the NNN time steps, with a constant that does not grow with NNN, and that they are measured by the residuals of the discrete BSDE itself. That makes the influence of the basis directly computable (the paper's §6 does so for Voronoi-cell indicators), and shows that I=2I=2I=2 Picard iterations already give an error of the order of the time discretization. Combined with Theorem 3 it gives the complete error budget of the algorithm.

The result is proved in the paper; to our knowledge none of it is machine-checked. A complete development provides a formal L2\mathbf L_2L2​-regression calculus for discrete BSDEs (projections on random bases, conditional expectations against Gaussian increments, contraction of Picard maps in L2(Fk)\mathbf L_2(\mathcal F_k)L2​(Fk​)) and a backward discrete Gronwall lemma, all reusable for other regression schemes. One printed step, (14), fails at i=1i=1i=1 (see below), so a formal proof also certifies that the theorem survives the repair.

Difficulty

The obvious argument compares the scheme with the discrete BSDE one step at a time and applies Gronwall. It fails for ZZZ: ZtkN,i,IZ^{N,i,I}_{t_k}Ztk​N,i,I​ carries a factor 1/h1/h1/h, and a naive bound E∣Z∣2≤h−1E∣Y∣2\mathbb E|Z|^2\le h^{-1}\mathbb E|Y|^2E∣Z∣2≤h−1E∣Y∣2 summed over N=T/hN=T/hN=T/h steps explodes. A usable bound has to account for the conditional variance of Ytk+1N,I,IY^{N,I,I}_{t_{k+1}}Ytk+1​N,I,I​ given Fk\mathcal F_kFk​, not only its second moment. The second difficulty is that the projection does not commute with the driver: projection errors enter at every step through the nonlinear fff, and must be bounded by residuals of YNY^NYN and ZNZ^NZN, not of the scheme's iterates. A third is the Picard step: at i=1i=1i=1 the iterate is computed with ZN,0,I=0Z^{N,0,I}=0ZN,0,I=0, so it is not an iterate of the contraction of milestone 3, and the printed inequality (14) E∣YtkN,∞,I−YtkN,i,I∣2≤(Cfh)2iE∣YtkN,∞,I∣2\mathbb E|Y^{N,\infty,I}_{t_k}-Y^{N,i,I}_{t_k}|^2\le(C_fh)^{2i}\mathbb E|Y^{N,\infty,I}_{t_k}|^2E∣Ytk​N,∞,I​−Ytk​N,i,I​∣2≤(Cf​h)2iE∣Ytk​N,∞,I​∣2 fails there; an extra term in E∣ZtkN,I,I∣2\mathbb E|Z^{N,I,I}_{t_k}|^2E∣Ztk​N,I,I​∣2 is needed.

Formalization scope

The Lean development lives in the namespace RegMCBSDE.Projection. Points are in EuclideanSpace ℝ (Fin d), the matrix norm in (H1) is the Frobenius norm, and all expectations of squares are lower Lebesgue integrals in [0,∞][0,\infty][0,∞], so no junk value of a Bochner integral can make an inequality vacuous. Component mmm (from 000) of ΔWk\Delta W_kΔWk​ is the paper's ΔWm+1,k\Delta W_{m+1,k}ΔWm+1,k​, and the bases are indexed by Fin (q+1) with l=0l=0l=0 for YYY.

Committed readings:

  • (H3) is dropped. It constrains the continuous terminal functional, which no statement involves.
  • The filtration is abstract. Any filtration with Fk+1\mathcal F_{k+1}Fk+1​-measurable increments independent of Fk\mathcal F_kFk​ and of law N(0,hIq)\mathcal N(0,hI_q)N(0,hIq​); the Brownian filtration is one. The Markov representation of PNP^NPN is not used and is dropped.
  • Schemes are relations. (YN,ZN)(Y^N,Z^N)(YN,ZN) is any solution of (5)–(6), and α\alphaα is any family satisfying the arg-min rule (9) for every i≥1i\ge1i≥1 (the paper runs i≤Ii\le Ii≤I; (19) refers to all i≥0i\ge0i≥0). (10)–(11) are a milestone, not the definition.
  • The projection is Mathlib's orthogonal projection in L2(Ω,P)\mathbf L_2(\Omega,\mathbb P)L2​(Ω,P) onto the span of the basis coordinates. It is not defined by the normal equations.
  • Constants. In Theorem 2 and (19), CCC and the threshold h0h_0h0​ of "hhh small enough" are chosen after (T,d,q,b,σ,f,Cf,L)(T,d,q,b,\sigma,f,C_f,L)(T,d,q,b,σ,f,Cf​,L) and before NNN, III, S0S_0S0​, d′d'd′, the probability space, PNP^NPN, ΦN\Phi^NΦN and the bases. A constant chosen after the scheme data would make the theorem trivially true and is ruled out by this quantifier order.
  • Pinned readings. max⁡k\max_kmaxk​ is "for every k≤Nk\le Nk≤N". In (13) the argument ZN,i−1,IZ^{N,i-1,I}ZN,i−1,I is read as ZN,I,IZ^{N,I,I}ZN,I,I, as the displayed (13) shows, and "hhh small enough" is Cfh<1C_fh<1Cf​h<1. (12) is multiplied by hhh to avoid subtraction. (19) is stated for k≤N−1k\le N-1k≤N−1 and every 1≤l≤q1\le l\le q1≤l≤q. (10) is stated where Ytk+1N,I,IΔWl,kY^{N,I,I}_{t_{k+1}}\Delta W_{l,k}Ytk+1​N,I,I​ΔWl,k​ is square integrable, since P\mathcal PP acts on L2\mathbf L_2L2​.
  • Not stated. (14), which is false at i=1i=1i=1, and the steps whose printed derivation passes through it ((15)–(18), (20)–(26)); Theorem 1 and Propositions 1 and 3.

Contributions welcome: proofs of the milestones, and the Mathlib-level lemmas they need (conditional expectation of a product with an independent centered Gaussian, L2\mathbf L_2L2​ moments of the Euler scheme, the projection identity Pp(U)=Pp(EkU)\mathcal P_p(U)=\mathcal P_p(\mathbb E_kU)Pp​(U)=Pp​(Ek​U) for Fk\mathcal F_kFk​-measurable bases).

Selected references

  • E. Gobet, J.-P. Lemor, X. Warin, A regression-based Monte Carlo method to solve backward stochastic differential equations, Ann. Appl. Probab. 15(3), 2172–2202, 2005. arXiv:math/0508491, doi:10.1214/105051605000000412
  • J. Zhang, A numerical scheme for BSDEs, Ann. Appl. Probab. 14(1), 459–488, 2004. doi:10.1214/aoap/1075828058
  • B. Bouchard, N. Touzi, Discrete-time approximation and Monte-Carlo simulation of backward stochastic differential equations, Stoch. Proc. Appl. 111(2), 175–206, 2004. doi:10.1016/j.spa.2004.01.001
  • F. A. Longstaff, E. S. Schwartz, Valuing American options by simulation: a simple least-squares approach, Rev. Financ. Stud. 14(1), 113–147, 2001. doi:10.1093/rfs/14.1.113
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Numerical AnalysisProbabilityStochastic Systems·Captain: mikedeng1

A Regression-Based Monte Carlo Method to Solve Backward Stochastic Differential Equations II: Simulation Error of the Empirical Regression Scheme in the Number of PathsResearch Paper

Motivation

Backward stochastic differential equations (BSDEs) describe the price and the hedge of a contingent claim in models with nonlinear pricing rules (differential interest rates, funding costs, reflected or constrained claims), and give probabilistic representations of semilinear parabolic PDEs (El Karoui, Peng and Quenez, 1997). Their numerical solution in moderate dimension is done by simulation: a backward recursion over a time grid in which each conditional expectation is replaced by a least-squares regression on simulated paths, the same device as the regression method for Bermudan options of Longstaff and Schwartz (2001).

Gobet, Lemor and Warin (2005) split the error of such a scheme into three parts: time discretization (Theorem 1), projection on finite function bases (Theorem 2), and the replacement of L2\mathbf L_2L2​ projections by empirical regressions on MMM simulated paths (Theorem 3). This mission formalizes the third part, which the authors describe as the major contribution of the paper. Its point is that the error from the simulations is controlled nonasymptotically, step by step, without blowing up as the time step hhh shrinks, even though every regression of the backward recursion reuses the same simulated paths.

Setting

A model consists of a horizon T>0T>0T>0, a drift bbb, a diffusion σ\sigmaσ satisfying the Lipschitz condition (H1), and a driver f(t,x,y,z)f(t,x,y,z)f(t,x,y,z) satisfying (H2): ∣f(t2,x2,y2,z2)−f(t1,x1,y1,z1)∣≤Cf(∣t2−t1∣1/2+∣x2−x1∣+∣y2−y1∣+∣z2−z1∣)|f(t_2,x_2,y_2,z_2)-f(t_1,x_1,y_1,z_1)|\le C_f(|t_2-t_1|^{1/2}+|x_2-x_1|+|y_2-y_1|+|z_2-z_1|)∣f(t2​,x2​,y2​,z2​)−f(t1​,x1​,y1​,z1​)∣≤Cf​(∣t2​−t1​∣1/2+∣x2​−x1​∣+∣y2​−y1​∣+∣z2​−z1​∣). For N≥1N\ge1N≥1, h=T/Nh=T/Nh=T/N, tk=kht_k=khtk​=kh, the Euler scheme is Stk+1N=StkN+b(tk,StkN)h+σ(tk,StkN)ΔWkS^N_{t_{k+1}}=S^N_{t_k}+b(t_k,S^N_{t_k})h+\sigma(t_k,S^N_{t_k})\Delta W_kStk+1​N​=Stk​N​+b(tk​,Stk​N​)h+σ(tk​,Stk​N​)ΔWk​, where the increments ΔWk∼N(0,hIq)\Delta W_k\sim\mathcal N(0,hI_q)ΔWk​∼N(0,hIq​) are independent of the past. A chain PtkN∈Rd′P^N_{t_k}\in\mathbb R^{d'}Ptk​N​∈Rd′ extends StkNS^N_{t_k}Stk​N​, and ΦN(PtNN)\Phi^N(P^N_{t_N})ΦN(PtN​N​) is the terminal value.

At each time tkt_ktk​, function bases p0,kp_{0,k}p0,k​ (for YYY) and pl,kp_{l,k}pl,k​, 1≤l≤q1\le l\le q1≤l≤q (for the components of ZZZ) are fixed, orthonormal in the sense E[pl,k(PtkN)pl,k(PtkN)∗]=Id\mathbb E[p_{l,k}(P^N_{t_k})p_{l,k}(P^N_{t_k})^*]=\mathrm{Id}E[pl,k​(Ptk​N​)pl,k​(Ptk​N​)∗]=Id. The projection–Picard scheme (Definition 1) computes coefficients αki,I\alpha^{i,I}_kαki,I​ by III Picard iterations of an L2\mathbf L_2L2​ least-squares problem, and sets YtkN,I,I=α0,kI,I⋅p0,kY^{N,I,I}_{t_k}=\alpha^{I,I}_{0,k}\cdot p_{0,k}Ytk​N,I,I​=α0,kI,I​⋅p0,k​, Zl,tkN,I,I=αl,kI,I⋅pl,kZ^{N,I,I}_{l,t_k}=\alpha^{I,I}_{l,k}\cdot p_{l,k}Zl,tk​N,I,I​=αl,kI,I​⋅pl,k​.

The empirical scheme (4) replaces the expectation by an average over MMM independent simulations (PN,m,ΔWm)(P^{N,m},\Delta W^m)(PN,m,ΔWm) of the path: αki,I,M\alpha^{i,I,M}_kαki,I,M​ minimizes

1M∑m=1M(Ytk+1N,I,I,M,m−α0⋅p0,km+hfkm(αki−1,I,M)−∑l=1qαl⋅pl,kmΔWl,km)2.\frac1M\sum_{m=1}^M\Big(Y^{N,I,I,M,m}_{t_{k+1}}-\alpha_0\cdot p^m_{0,k}+hf^m_k(\alpha^{i-1,I,M}_k)-\sum_{l=1}^q\alpha_l\cdot p^m_{l,k}\Delta W^m_{l,k}\Big)^2 .M1​m=1∑M​(Ytk+1​N,I,I,M,m​−α0​⋅p0,km​+hfkm​(αki−1,I,M​)−l=1∑q​αl​⋅pl,km​ΔWl,km​)2.

The outputs are truncated: with ρl,kN(x)=max⁡(1,C0∣pl,k(x)∣)\rho^N_{l,k}(x)=\max(1,C_0|p_{l,k}(x)|)ρl,kN​(x)=max(1,C0​∣pl,k​(x)∣) and a smooth profile ξ\xiξ equal to the identity on [−3/2,3/2][-3/2,3/2][−3/2,3/2], YtkN,I,I,M=ρ^0,kN(α0,kI,I,M⋅p0,k)Y^{N,I,I,M}_{t_k}=\hat\rho^N_{0,k}(\alpha^{I,I,M}_{0,k}\cdot p_{0,k})Ytk​N,I,I,M​=ρ^​0,kN​(α0,kI,I,M​⋅p0,k​) with ρ^l,kN(x)=ρl,kN(PtkN)ξ(x/ρl,kN(PtkN))\hat\rho^N_{l,k}(x)=\rho^N_{l,k}(P^N_{t_k})\xi(x/\rho^N_{l,k}(P^N_{t_k}))ρ^​l,kN​(x)=ρl,kN​(Ptk​N​)ξ(x/ρl,kN​(Ptk​N​)). The regression vector is [vk]∗=(p0,k∗,p1,k∗ΔW1,k/h,…,pq,k∗ΔWq,k/h)[v_k]^*=(p_{0,k}^*,p_{1,k}^*\Delta W_{1,k}/\sqrt h,\dots,p_{q,k}^*\Delta W_{q,k}/\sqrt h)[vk​]∗=(p0,k∗​,p1,k∗​ΔW1,k​/h​,…,pq,k∗​ΔWq,k​/h​), and the good event AkM\mathbf A^M_kAkM​ (27) asks that the empirical matrices VjM=1M∑mvjm[vjm]∗V^M_j=\frac1M\sum_mv^m_j[v^m_j]^*VjM​=M1​∑m​vjm​[vjm​]∗ and Pl,jM=1M∑mpl,jm[pl,jm]∗P^M_{l,j}=\frac1M\sum_m p^m_{l,j}[p^m_{l,j}]^*Pl,jM​=M1​∑m​pl,jm​[pl,jm​]∗ be close to the identity for all j≥kj\ge kj≥k.

Formalization targets

Goal: Theorem 3

For I≥3I\ge3I≥3, orthonormal bases with E∣pl,k∣4<∞\mathbb E|p_{l,k}|^4<\inftyE∣pl,k​∣4<∞, C0C_0C0​ such that the bounds of Proposition 2 hold, and hhh small enough, for 0≤k≤N−10\le k\le N-10≤k≤N−1,

E∣YtkN,I,I−YtkN,I,I,M∣2+h∑j=kN−1E∣ZtjN,I,I−ZtjN,I,I,M∣2≤9∑j=kN−1E(∣ρjN∣21[AkM]c)+ChI−1∑j=kN−1[1+∣S0∣2+E∣ρjN∣2]+ChM∑j=kN−1ϵj,\mathbb E|Y^{N,I,I}_{t_k}-Y^{N,I,I,M}_{t_k}|^2+h\sum_{j=k}^{N-1}\mathbb E|Z^{N,I,I}_{t_j}-Z^{N,I,I,M}_{t_j}|^2\le 9\sum_{j=k}^{N-1}\mathbb E(|\rho^N_j|^2\mathbf 1_{[\mathbf A^M_k]^c})+Ch^{I-1}\sum_{j=k}^{N-1}[1+|S_0|^2+\mathbb E|\rho^N_j|^2]+\frac{C}{hM}\sum_{j=k}^{N-1}\epsilon_j,E∣Ytk​N,I,I​−Ytk​N,I,I,M​∣2+hj=k∑N−1​E∣Ztj​N,I,I​−Ztj​N,I,I,M​∣2≤9j=k∑N−1​E(∣ρjN​∣21[AkM​]c​)+ChI−1j=k∑N−1​[1+∣S0​∣2+E∣ρjN​∣2]+hMC​j=k∑N−1​ϵj​,

where ϵj\epsilon_jϵj​ collects second moments of vjvj∗−Idv_jv_j^*-\mathrm{Id}vj​vj∗​−Id, ∣vj∣2∣p0,j+1∣2|v_j|^2|p_{0,j+1}|^2∣vj​∣2∣p0,j+1​∣2 and ∣vj∣2(1+∣StjN∣2+… )|v_j|^2(1+|S^N_{t_j}|^2+\dots)∣vj​∣2(1+∣Stj​N​∣2+…), written out in full in the goal statement. The constant CCC and the threshold on hhh depend only on the model and on ξ\xiξ.

Milestones

  1. Proposition 2: the a priori bounds ∣YtkN,i,I∣≤ρ0,kN|Y^{N,i,I}_{t_k}|\le\rho^N_{0,k}∣Ytk​N,i,I​∣≤ρ0,kN​, h∣Zl,tkN,i,I∣≤ρl,kN\sqrt h|Z^{N,i,I}_{l,t_k}|\le\rho^N_{l,k}h​∣Zl,tk​N,i,I​∣≤ρl,kN​ that fix the truncation levels.
  2. (28)–(29): the empirical least-squares solution and its contraction inequality λmin⁡(VM)∣θx∣2≤∣θx⋅v∣M2≤∣x∣M2\lambda_{\min}(V^M)|\theta_x|^2\le|\theta_x\cdot v|^2_M\le|x|^2_Mλmin​(VM)∣θx​∣2≤∣θx​⋅v∣M2​≤∣x∣M2​.
  3. Lemma 1: on AkM\mathbf A^M_kAkM​ the empirical Picard iterations contract at rate ChChCh to a unique fixed point, with error [Ch]I[Ch]^I[Ch]I after III steps.
  4. (32): the pathwise bound ∣θki,I,M∣2≤C(Ak+1N,M+hBkN,M)|\theta^{i,I,M}_k|^2\le C(\mathcal A^{N,M}_{k+1}+h\mathcal B^{N,M}_k)∣θki,I,M​∣2≤C(Ak+1N,M​+hBkN,M​) on AkM\mathbf A^M_kAkM​.
  5. (34): the expectation formula θk∞,I=E(vk[Ytk+1N,I,I+hfk(αk∞,I)])\theta^{\infty,I}_k=\mathbb E(v_k[Y^{N,I,I}_{t_{k+1}}+hf_k(\alpha^{\infty,I}_k)])θk∞,I​=E(vk​[Ytk+1​N,I,I​+hfk​(αk∞,I​)]).

Significance

Theorem 3 is nonasymptotic: together with Theorems 1 and 2 it lets one compare the three error sources and choose hhh, the bases and MMM jointly for a target accuracy. The 1/(hM)1/(hM)1/(hM) rate shows how many paths a finer time grid requires, and the hI−1h^{I-1}hI−1 term shows that I=3I=3I=3 Picard iterations suffice. The term involving [AkM]c[\mathbf A^M_k]^c[AkM​]c isolates the event on which the empirical regression matrices are badly conditioned, which the truncation keeps under control.

The result is proved in the paper; nothing in this mission is open mathematically. No machine-checked proof of any part of it is known. A formal proof would check a long chain of estimates whose constants the paper tracks only as a generic CCC, and would settle the two misprints in the printed statement (see below). The definitions layer (Euler scheme, regression schemes, empirical regression matrices) is reusable for other regression Monte Carlo schemes for BSDEs and for optimal stopping.

Difficulty

The obvious approach is to treat each regression as an independent statistical estimation problem and apply a variance bound per time step. This fails because all regressions of the backward recursion use the same MMM paths: the response at time tk+1t_{k+1}tk+1​ is itself a function of the simulations, so the regression at tkt_ktk​ is not a regression of a fixed variable on independent samples. Moreover, the empirical matrix VkMV^M_kVkM​ may be singular, and on that event the empirical coefficients are unbounded unless truncated. A naive per-step bound also produces a factor 1/h1/h1/h at each of the N=T/hN=T/hN=T/h steps, which explodes; the proof must keep the accumulated constants of order one.

Formalization scope

  • All objects are defined in the namespace RegMCBSDE.Simulation. Continuous time is not used: the increments ΔWk\Delta W_kΔWk​ are any family that is Fk+1\mathcal F_{k+1}Fk+1​-measurable, independent of Fk\mathcal F_kFk​ and N(0,hIq)\mathcal N(0,hI_q)N(0,hIq​)-distributed for some filtration. That covers the Brownian case. (H3), a condition on the terminal functional of the continuous path, is dropped. So is the Markov representation of PNP^NPN, which no statement uses.
  • Expectations of squared quantities are taken in [0,∞][0,\infty][0,∞], on both sides of every inequality.
  • Euclidean norms are written as sums of squares. ∥A∥≤c\|A\|\le c∥A∥≤c for symmetric AAA is written as ∣x∗Ax∣≤c∣x∣2|x^*Ax|\le c|x|^2∣x∗Ax∣≤c∣x∣2 for all xxx.
  • The schemes are defined as predicates (any minimizer of each least-squares problem), never through a matrix inverse. The empirical coefficients are required to be measurable functions of the simulations, and any such minimizer is allowed, as the paper says the choice is arbitrary.
  • The reference path at which the fitted coefficients are evaluated is assumed independent of the MMM simulations.
  • Picard iterations are imposed for every i≥1i\ge1i≥1.
  • "For hhh small enough" is formalized as T/N<h0T/N<h_0T/N<h0​. Every constant CCC and every h0h_0h0​ is chosen before NNN, III, MMM, kkk, C0C_0C0​, the bases, S0S_0S0​ and the probability space. A formalization in which CCC is chosen after the scheme data would make every inequality with a positive right-hand side trivially true, and is ruled out.
  • "C0C_0C0​ large enough" in Theorem 3 is the hypothesis that the bounds of Proposition 2 hold for C0C_0C0​.
  • Proposition 2 is stated for hhh small enough. The printed statement omits this condition, which its proof needs through the uniform bound (19).
  • In (32) and Lemma 1, ρ0,NN\rho^N_{0,N}ρ0,NN​, which the paper leaves undefined, is read through the terminal response ΦN(PtNN,m)\Phi^N(P^{N,m}_{t_N})ΦN(PtN​N,m​).
  • Corrections to Theorem 3 (both from the paper's proof, p. 21):
    1. The printed j=N−1j=N-1j=N−1 summand contains the undefined p0,Np_{0,N}p0,N​. It is replaced by E(∣vN−1∣2∣ΦN(PtNN)∣2)\mathbb E(|v_{N-1}|^2|\Phi^N(P^N_{t_N})|^2)E(∣vN−1​∣2∣ΦN(PtN​N​)∣2).
    2. The printed factor E∣ρ0,jN(PtjN)∣2\mathbb E|\rho^N_{0,j}(P^N_{t_j})|^2E∣ρ0,jN​(Ptj​N​)∣2 next to E(∣vj∣2∣p0,j+1∣2)\mathbb E(|v_j|^2|p_{0,j+1}|^2)E(∣vj​∣2∣p0,j+1​∣2) becomes E∣ρ0,j+1N(Ptj+1N)∣2\mathbb E|\rho^N_{0,j+1}(P^N_{t_{j+1}})|^2E∣ρ0,j+1N​(Ptj+1​N​)∣2.

Contributions welcome: proofs of the milestones, in particular (28)–(29) (finite-dimensional linear algebra) and (34) (independence and orthonormality), and a construction showing that measurable minimizers of (4) exist.

Selected references

  • E. Gobet, J.-P. Lemor, X. Warin, A regression-based Monte Carlo method to solve backward stochastic differential equations, Ann. Appl. Probab. 15(3), 2172–2202, 2005. https://doi.org/10.1214/105051605000000412, preprint https://arxiv.org/abs/math/0508491v1
  • N. El Karoui, S. Peng, M. C. Quenez, Backward stochastic differential equations in finance, Math. Finance 7(1), 1–71, 1997. https://doi.org/10.1111/1467-9965.00022
  • F. A. Longstaff, E. S. Schwartz, Valuing American options by simulation: a simple least-squares approach, Rev. Financ. Stud. 14(1), 113–147, 2001. https://doi.org/10.1093/rfs/14.1.113
  • J. Zhang, A numerical scheme for BSDEs, Ann. Appl. Probab. 14(1), 459–488, 2004. https://doi.org/10.1214/aoap/1075828058
  • B. Bouchard, N. Touzi, Discrete-time approximation and Monte-Carlo simulation of backward stochastic differential equations, Stochastic Process. Appl. 111(2), 175–206, 2004. https://doi.org/10.1016/j.spa.2004.01.001
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