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Control TheoryMathematical PhysicsQuantum Information·Captain: mikedeng1

Stabilizing qubit coherence via tracking-control: Under Pure Dephasing, Coherence Can Be Held Constant Exactly Until t_b = v_z(0)²/(2γc), Where the Control Fields DivergeResearch Paper

Motivation

A qubit coupled to an environment loses the phase relation between its basis states ∣0⟩|0\rangle∣0⟩ and ∣1⟩|1\rangle∣1⟩: the off-diagonal entries of its density matrix decay. This decoherence is the main obstacle to storing quantum information, and a large body of work tries to counter it with external control fields. Lidar and Schneider (arXiv:quant-ph/0410048, Quantum Information and Computation 2005) ask a sharp question in the simplest nontrivial setting: if the controller may observe the state and choose the Hamiltonian at every instant (tracking control), can it keep the coherence of a dephasing qubit exactly constant, and for how long?

Their answer, stated in the abstract, is that "it is possible to maintain coherence for finite time durations, until the control field diverges." It was known that Hamiltonian control cannot hold the purity Tr⁡ρ2\operatorname{Tr}\rho^2Trρ2 of a Markovian open system at its initial value (Ketterle and Pritchard, Phys. Rev. A 46, 4051 (1992), and Tannor and Bartana, J. Phys. Chem. A 103, 10359 (1999), refs. [25, 26] of the paper), and the paper's §II.A shows that under a unital Lindbladian the purity decreases whatever the Hamiltonian; the present result locates exactly how much of the coherence, as opposed to the purity, control can protect.

Setting

A qubit state is a complex 2×22\times22×2 matrix ρ\rhoρ with Tr⁡ρ=1\operatorname{Tr}\rho=1Trρ=1, ρ10=ρ01∗\rho_{10}=\rho_{01}^*ρ10​=ρ01∗​ and Tr⁡(ρ2)≤1\operatorname{Tr}(\rho^2)\le1Tr(ρ2)≤1. With the Pauli matrices σx,σy,σz\sigma_x,\sigma_y,\sigma_zσx​,σy​,σz​, its Bloch vector is v⃗=(vx,vy,vz)\vec v=(v_x,v_y,v_z)v=(vx​,vy​,vz​), vα=Tr⁡(ρσα)v_\alpha=\operatorname{Tr}(\rho\sigma_\alpha)vα​=Tr(ρσα​), so that ρ=12(I+v⃗⋅σ⃗)\rho=\tfrac12(I+\vec v\cdot\vec\sigma)ρ=21​(I+v⋅σ) (eq. (9)). The coherence is the squared radius of v⃗\vec vv in the xxx–yyy plane,

c=vx2+vy2=4∣ρ01∣2(eq. (11)).c=v_x^2+v_y^2=4|\rho_{01}|^2 \quad\text{(eq. (11))}.c=vx2​+vy2​=4∣ρ01​∣2(eq. (11)).

The controller applies the Hamiltonian H(t)=ℏ2(ω0(t)σz+ω1(t)σx−ω2(t)σy)H(t)=\tfrac{\hbar}{2}\bigl(\omega_0(t)\sigma_z+\omega_1(t)\sigma_x-\omega_2(t)\sigma_y\bigr)H(t)=2ℏ​(ω0​(t)σz​+ω1​(t)σx​−ω2​(t)σy​) (eq. (13)) with three real fields ω0,ω1,ω2\omega_0,\omega_1,\omega_2ω0​,ω1​,ω2​, and the qubit undergoes pure dephasing at rate γ>0\gamma>0γ>0:

∂ρ∂t=−iℏ[H,ρ]+γ2(σzρσz−ρ)(eq. (32)).\frac{\partial\rho}{\partial t}=-\frac{i}{\hbar}[H,\rho]+\frac{\gamma}{2}(\sigma_z\rho\sigma_z-\rho)\quad\text{(eq. (32))}.∂t∂ρ​=−ℏi​[H,ρ]+2γ​(σz​ρσz​−ρ)(eq. (32)).

Equivalently the Bloch vector obeys v⃗˙=M(t)v⃗\dot{\vec v}=M(t)\vec vv˙=M(t)v with

M(t)=(−γ−ω0−ω2ω0−γ−ω1ω2ω10)(eq. (30)).M(t)=\begin{pmatrix}-\gamma&-\omega_0&-\omega_2\\ \omega_0&-\gamma&-\omega_1\\ \omega_2&\omega_1&0\end{pmatrix}\quad\text{(eq. (30))}.M(t)=​−γω0​ω2​​−ω0​−γω1​​−ω2​−ω1​0​​(eq. (30)).

Without control the coherence decays as e−2γtce^{-2\gamma t}ce−2γtc. The breakdown time of an initial state with coherence c>0c>0c>0 is

tb=vz(0)22γc(eq. (38)).t_b=\frac{v_z(0)^2}{2\gamma c}\quad\text{(eq. (38))}.tb​=2γcvz​(0)2​(eq. (38)).

The tracking fields are, with s=sign⁡vz(0)s=\operatorname{sign}v_z(0)s=signvz​(0), an arbitrary ω0\omega_0ω0​, and R(t)=vz(0)2−2γctR(t)=v_z(0)^2-2\gamma ctR(t)=vz​(0)2−2γct,

ω2(t)=s −γvx(0)−ω0(t)vy(0)R(t),ω1(t)=s −γvy(0)+ω0(t)vx(0)R(t)(eqs. (41)–(42)),\omega_2(t)=s\,\frac{-\gamma v_x(0)-\omega_0(t)v_y(0)}{\sqrt{R(t)}},\qquad \omega_1(t)=s\,\frac{-\gamma v_y(0)+\omega_0(t)v_x(0)}{\sqrt{R(t)}}\quad\text{(eqs. (41)–(42))},ω2​(t)=sR(t)​−γvx​(0)−ω0​(t)vy​(0)​,ω1​(t)=sR(t)​−γvy​(0)+ω0​(t)vx​(0)​(eqs. (41)–(42)),

and the tracked state is 12(I+v⃗(t)⋅σ⃗)\tfrac12(I+\vec v(t)\cdot\vec\sigma)21​(I+v(t)⋅σ) with v⃗(t)=(vx(0),vy(0),sR(t))\vec v(t)=(v_x(0),v_y(0),s\sqrt{R(t)})v(t)=(vx​(0),vy​(0),sR(t)​).

Formalization targets

Goal: coherence can be held exactly on [0,tb)[0,t_b)[0,tb​), and no longer

For ℏ>0\hbar>0ℏ>0, γ>0\gamma>0γ>0 and a qubit state ρ0\rho_0ρ0​ with coherence c>0c>0c>0:

  1. No-go. For all controls and every solution ρ(t)\rho(t)ρ(t) of (32) on [0,T)[0,T)[0,T) with ρ(0)=ρ0\rho(0)=\rho_0ρ(0)=ρ0​ and constant coherence ccc,
vz(t)2=vz(0)2−2γc t(t∈[0,T)),T≤tb.v_z(t)^2=v_z(0)^2-2\gamma c\,t\quad(t\in[0,T)),\qquad T\le t_b .vz​(t)2=vz​(0)2−2γct(t∈[0,T)),T≤tb​.
  1. Achievability. If vz(0)≠0v_z(0)\ne0vz​(0)=0, then for every ω0\omega_0ω0​ the tracked state starts at ρ0\rho_0ρ0​, is a qubit state, keeps vx,vyv_x,v_yvx​,vy​ fixed, and solves (32) at every t∈[0,tb)t\in[0,t_b)t∈[0,tb​) with the tracking fields.
  2. Divergence. If vz(0)≠0v_z(0)\ne0vz​(0)=0, then ω1(t)2+ω2(t)2→+∞\omega_1(t)^2+\omega_2(t)^2\to+\inftyω1​(t)2+ω2​(t)2→+∞ as t→tb−t\to t_b^-t→tb−​, whatever ω0\omega_0ω0​ is.

Milestones

The milestones follow the paper's derivation: the Bloch parametrization (§II.B, p. 3); the equivalence of (32) and (30) (§III.B, p. 5); eq. (36), v˙z=−γc/vz\dot v_z=-\gamma c/v_zv˙z​=−γc/vz​ under constant coherence (p. 6); eqs. (37)–(38), vz(t)=(±)vz(0)2−2γctv_z(t)=(\pm)\sqrt{v_z(0)^2-2\gamma ct}vz​(t)=(±)vz​(0)2−2γct​ and T≤tbT\le t_bT≤tb​ (p. 6); eqs. (41)–(42), the tracking fields solve (30) and are forced once vx,vyv_x,v_yvx​,vy​ are frozen (p. 6); and the field-strength identity of §III.C (p. 8),

ω1(t)2+ω2(t)2=(γ2+ω0(t)2) cvz(0)2−2γct.\omega_1(t)^2+\omega_2(t)^2=\frac{(\gamma^2+\omega_0(t)^2)\,c}{v_z(0)^2-2\gamma ct}.ω1​(t)2+ω2​(t)2=vz​(0)2−2γct(γ2+ω0​(t)2)c​.

Significance

The result gives an exact, state-dependent budget for coherence protection under dephasing. The time tbt_btb​ is inversely proportional to the coherence to be maintained and proportional to vz(0)2=p(0)−cv_z(0)^2=p(0)-cvz​(0)2=p(0)−c, where p=∣v⃗∣2p=|\vec v|^2p=∣v∣2 is the purity: the more coherent the initial state, the shorter the protection, and a state of maximal coherence for its purity (vz(0)=0v_z(0)=0vz​(0)=0) cannot be protected at all. The no-go part holds for every control law, so it bounds any tracking strategy, not only the linearized one the paper constructs. The divergence of the fields is the physical cost: protection up to tbt_btb​ requires unbounded control amplitude, which any bounded actuator cuts short.

The paper proves these statements by direct calculation. As far as is known, none of them has a machine-checked proof. The mission turns a physics derivation, in which "the solution is" and "does not stay real" carry the logical weight, into precise statements about solutions of an ODE on a half-open interval, with the sign choice, the degenerate case vz(0)=0v_z(0)=0vz​(0)=0 and the domain of the square roots made explicit.

Difficulty

The calculations are elementary, but the no-go statement quantifies over arbitrary, possibly discontinuous control fields and arbitrary solutions of the matrix equation. Nothing is assumed about the controls beyond being real functions of time, nothing about the solution beyond continuity on [0,T)[0,T)[0,T) and the equation on (0,T)(0,T)(0,T), and the conclusion constrains only the zzz-component while the hypothesis constrains only the xxx–yyy components. The tempting shortcut, assuming that vxv_xvx​ and vyv_yvy​ are frozen as in the paper's explicit construction, proves a strictly weaker statement and is not the goal. On the achievability side, the square root is not differentiable where its argument vanishes, so differentiability has to be established on [0,tb)[0,t_b)[0,tb​), including the endpoint t=0t=0t=0, and the sign sign⁡vz(0)\operatorname{sign}v_z(0)signvz​(0) has to be carried through the derivative.

Formalization scope

Operators are Matrix (Fin 2) (Fin 2) ℂ in the basis ∣0⟩,∣1⟩|0\rangle,|1\rangle∣0⟩,∣1⟩; the Pauli matrices are the published MIPRE.LCS.Pauli.X/Y/Z. Bloch vectors and controls are Fin 3 → ℝ: Bloch components in the order x,y,zx,y,zx,y,z, control components in the order ω0,ω1,ω2\omega_0,\omega_1,\omega_2ω0​,ω1​,ω2​ (with ω0\omega_0ω0​ multiplying σz\sigma_zσz​, as in (13)). The Bloch vector is vα=Re⁡Tr⁡(ρσα)v_\alpha=\operatorname{Re}\operatorname{Tr}(\rho\sigma_\alpha)vα​=ReTr(ρσα​), following eq. (9); eq. (8) prints an extra factor 12\tfrac1221​, which contradicts (9) and is treated as a misprint. A trajectory solves (32) or (30) on [0,T)[0,T)[0,T) if it is continuous on [0,T)[0,T)[0,T) and has the prescribed derivative at every t∈(0,T)t\in(0,T)t∈(0,T). Controls are arbitrary functions R→R\mathbb R\to\mathbb RR→R. The hypotheses γ>0\gamma>0γ>0 and c>0c>0c>0 are added, because tbt_btb​ divides by 2γc2\gamma c2γc; ℏ>0\hbar>0ℏ>0 is a parameter. The sign (±)(\pm)(±) of (37), (41), (42) is sign⁡vz(0)\operatorname{sign}v_z(0)signvz​(0).

Statements about tbt_btb​, the tracked state and the fields are restricted to [0,tb)[0,t_b)[0,tb​), because Lean's square root and division are total (x=0\sqrt{x}=0x​=0 for x<0x<0x<0, x/0=0x/0=0x/0=0); a statement that only asserts that the closed-form curve solves the ODE would be the achievability half alone, and the goal requires the no-go half over all controls as well.

A complete development needs the Bloch dictionary for 2×22\times22×2 matrices, the passage from (32) to (30), and one-variable real analysis on half-open intervals. The Bloch dictionary and the reduction of a Lindblad equation to Bloch form are reusable for other qubit control problems. Proofs of any milestone, and sorry-free lemmas on the Pauli algebra, are welcome.

Selected references

  • D. A. Lidar and S. Schneider, Stabilizing qubit coherence via tracking-control, Quantum Information and Computation (2005); arXiv:quant-ph/0410048v1, 2004. https://arxiv.org/abs/quant-ph/0410048
  • W. Ketterle and D. E. Pritchard, Atom cooling by time-dependent potentials, Physical Review A 46, 4051 (1992). https://doi.org/10.1103/PhysRevA.46.4051
9 thms3 active usersReviewed
AlgebraRepresentation Theory·Captain: mikedeng1

Cyclotomic Birman–Wenzl–Murakami Algebras, II: Admissibility Relations and Freeness: Over an Admissible Integral Domain S, W_{n,S,r} Is a Free S-Module of Rank r^n(2n−1)!!Research Paper

Motivation

The cyclotomic Birman–Wenzl–Murakami algebra is an algebra of braids and contractions equipped with an additional cyclotomic relation. It connects diagram algebras, representation theory, and knot theoretic constructions. For calculations over a coefficient ring, one needs to know whether the diagrammatic spanning elements remain independent after parameters are specialized. The freeness theorem of Goodman and Hauschild Mosley answers that question for admissible integral ground rings: the algebra has a basis of the size predicted by labeled Brauer diagrams. The paper also identifies the algebra with a cyclotomic Kauffman tangle algebra. This mission targets the algebra's freeness and rank assertion.

The cited paper builds on admissibility relations developed with Wilcox and Yu. Its earlier definitions and preliminary statements already appear in Prove2Me mission 92e1197e-907f-4ab8-92be-01ea44f6cfef. The present mission reuses that published layer and poses the deferred freeness theorem and the intermediate results that support it. The distinction matters because two algebras with similar names but different generators or parameter conventions need not have the same rank statement.

Setting

A ground ring SSS is a commutative unital ring with a positive integer rrr and parameters ρ,q,δ0,δ1,…,u1,…,ur\rho,q,\delta_0,\delta_1,\ldots,u_1,\ldots,u_rρ,q,δ0​,δ1​,…,u1​,…,ur​. The parameters ρ,q,δ0,u1,…,ur\rho,q,\delta_0,u_1,\ldots,u_rρ,q,δ0​,u1​,…,ur​ are units, and they satisfy

ρ−1−ρ=(q−1−q)(δ0−1).\rho^{-1}-\rho=(q^{-1}-q)(\delta_0-1).ρ−1−ρ=(q−1−q)(δ0​−1).

The algebra Wn,S,rW_{n,S,r}Wn,S,r​ is generated over SSS by invertible braids gig_igi​, contractions eie_iei​, and an invertible affine generator y1y_1y1​. It obeys the affine BMW relations of Definition 2.1 and the cyclotomic relation ∏j=1r(y1−uj)=0\prod_{j=1}^r(y_1-u_j)=0∏j=1r​(y1​−uj​)=0 of Definition 2.8. The shared published presentation uses indices i=0,…,n−2i=0,\ldots,n-2i=0,…,n−2 for gig_igi​ and eie_iei​, corresponding to the paper's gi+1g_{i+1}gi+1​ and ei+1e_{i+1}ei+1​. At n=0n=0n=0 there are no generators.

The parameters are admissible when q−q−1q-q^{-1}q−q−1 is nonzero and not a zero divisor, weak admissibility holds for every integer shift of the δ\deltaδ relations, and e1,y1e1,…,y1r−1e1e_1,y_1e_1,\ldots,y_1^{r-1}e_1e1​,y1​e1​,…,y1r−1​e1​ are SSS-linearly independent in W2,S,rW_{2,S,r}W2,S,r​. These are the conditions of Definition 3.3, expressed using condition (1) of Theorem 3.2. A morphism of ground rings preserves all δj\delta_jδj​ and uiu_iui​ and permits exactly the four paired sign actions on ρ\rhoρ and qqq in Definition 2.13. Consequently, base change includes the sign twists allowed by the paper.

For the generic case, F=Q(q,u1,…,ur)F=\mathbb Q(q,u_1,\ldots,u_r)F=Q(q,u1​,…,ur​) is the rational function field in algebraically independent variables. Put p=∏jujp=\prod_j u_jp=∏j​uj​, set ρ=p\rho=pρ=p for odd rrr and ρ=q−1p\rho=q^{-1}pρ=q−1p for even rrr, and define δa=∑jγjuja\delta_a=\sum_j\gamma_j u_j^aδa​=∑j​γj​uja​, where γj\gamma_jγj​ is the rational expression in equation (3.6). A shape in Γn\Gamma_nΓn​ is an rrr-tuple of Young diagrams whose total number of boxes is at most nnn and congruent to nnn modulo two. An up–down tableau of shape λ\lambdaλ is a path from the empty tuple to λ\lambdaλ, adding or removing one box at each step. Its set is T(n,λ)T(n,\lambda)T(n,λ).

Formalization targets

The central target is the freeness half of Theorem 6.1. For every admissible integral ground ring SSS and every n≥0n\ge0n≥0,

Wn,S,r≅SS rn(2n−1)!!.W_{n,S,r}\cong_S S^{\,r^n(2n-1)!!}.Wn,S,r​≅S​Srn(2n−1)!!.

Here (−1)!!=1(-1)!!=1(−1)!!=1, so the asserted rank at n=0n=0n=0 is one. A basis indexed by a finite type of that cardinality states both freeness and rank.

The milestone path includes the paper's admissibility equivalences, generic parameter construction, universal admissible integral domain, base change, the spanning family of rn(2n−1)!!r^n(2n-1)!!rn(2n−1)!! elements, the relevant Jones ideal and Hecke quotient results, and the generic structure results. At the generic field, Theorem 4.8 supplies split matrix blocks indexed by Γn\Gamma_nΓn​, with block size ∣T(n,λ)∣|T(n,\lambda)|∣T(n,λ)∣. The count in the proof of Theorem 5.2 is

∑λ∈Γn∣T(n,λ)∣2=rn(2n−1)!!,\sum_{\lambda\in\Gamma_n}|T(n,\lambda)|^2=r^n(2n-1)!!,λ∈Γn​∑​∣T(n,λ)∣2=rn(2n−1)!!,

which agrees with the generic dimension asserted by Theorem 5.2. The final theorem applies over an admissible integral domain, rather than only over FFF.

Significance

The result supplies an exact finite basis for Wn,S,rW_{n,S,r}Wn,S,r​ throughout the admissible integral-domain regime. It fixes the module rank independently of a choice of specialization and gives a numerical benchmark for presentations and representations of these algebras. The generic matrix decomposition also records the simple-block labels and their sizes; the tableau identity explains how those dimensions total the same rank.

Goodman and Hauschild Mosley proved these results. This mission asks for machine-checked proofs of the statements already known in the paper. Its reusable output includes ground-ring morphisms with sign twists, the generic parameter model, and finite tableau types. The published preliminary layer in mission 92e1197e-907f-4ab8-92be-01ea44f6cfef contains two proved and four open results among the six referenced milestones; none of the eight new theorem statements is presented here as already machine proved.

Difficulty

A spanning family alone does not show a basis: specializations can introduce linear dependence, and an equality of dimensions over one field does not itself establish independence over every integral ground ring. The argument also has to maintain the exact admissibility conditions when moving between coefficient rings. Over the generic field, identifying the right semisimple blocks requires the branching shapes and tableau sizes, while the final statement concerns arbitrary admissible integral domains. These are distinct algebraic regimes, and the same presentation and parameter conventions must be kept through each one.

Formalization scope

Lean uses the published GroundParameters, BMW, BMWAdmissible, UAdmissible, and equation (3.6) gamma expression from QAlgorithms.Papers.Independent.Support21.P14. The algebra is the quotient of a free algebra by the source's relations, with zero-based generator indices. The new definition layer records all four sign cases of Definition 2.13, the generic field as a fraction ring of a multivariate polynomial ring over Q\mathbb QQ, and shapes and tableaux as finite-indexed Young diagrams. A generic ground-parameter value is asserted to exist as a theorem because the required unit and compatibility proofs are substantive.

The universal-ring milestone states all five parts of Theorem 3.19 for R‾0\overline R_0R0​ and R‾+\overline R_+R+​; part (5) is read inside FFF, where the universal uuu-admissible ring is the subring generated by q±1q^{\pm1}q±1, (q−1−q)−1(q^{-1}-q)^{-1}(q−1−q)−1, δ0−1\delta_0^{-1}δ0−1​ and ui±1u_i^{\pm1}ui±1​. The base-change statement uses S′⊗SWS'\otimes_S WS′⊗S​W for the source's W⊗SS′W\otimes_S S'W⊗S​S′. Theorem 4.8 is expressed as a product of full matrix algebras with tableau-sized blocks, combining its split and labeling clauses with the block dimensions stated elsewhere in §4. Theorem 6.1's Kauffman-tangle isomorphism is not posed because a corresponding tangle algebra has not been provided here. The cited spanning set is expressed as an indexed family, which remains meaningful when a degenerate coefficient ring identifies elements.

The goal requires an actual basis of cardinality rn(2n−1)!!r^n(2n-1)!!rn(2n−1)!! over an admissible integral domain. A mere dimension equality or spanning claim does not satisfy it. Contributions toward the missing generic decomposition, tableau count, base-change isomorphism, and passage to arbitrary admissible domains are all within scope. The ground-parameter and quotient-presentation definitions are reusable independently of this mission.

Selected references

  • F. M. Goodman and H. Hauschild Mosley, Cyclotomic Birman–Wenzl–Murakami algebras, II: Admissibility Relations and Freeness, 2008, arXiv:math/0612065v5.
16 thms3 active usersReviewed
Dynamical SystemsMathematical PhysicsQuantum Information·Captain: mikedeng1

Highly Efficient Energy Excitation Transfer in Light-Harvesting Complexes: The Fundamental Role of Noise-Assisted Transport: Sink Population 1/(N−1) Without Noise, 1 Under DephasingResearch Paper

Motivation

Photosynthetic light-harvesting complexes move an electronic excitation from the pigment that absorbed a photon to a reaction centre, where its energy is stored chemically. In the Fenna–Matthews–Olson (FMO) complex this transfer is close to lossless, and two-dimensional spectroscopy showed long-lived quantum coherence during it (Engel et al. 2007). This raised a concrete question in open-system quantum dynamics: does the environment, whose noise destroys coherence, hinder transport, or can it help?

Numerical studies of FMO models found that local dephasing raises transfer efficiency compared with purely coherent evolution (Mohseni et al. 2008; Plenio and Huelga 2008; Rebentrost et al. 2009). Caruso, Chin, Datta, Huelga and Plenio (arXiv:0901.4454, J. Chem. Phys. 2009) isolated a mechanism behind this in a model that can be solved exactly: the fully connected network (FCN). There, coherent evolution traps most of the excitation by destructive interference, and any amount of uniform dephasing removes the trap. This mission formalizes that exact result.

Setting

The network has NNN sites. The single-excitation space has orthonormal basis ∣0⟩,∣1⟩,…,∣N⟩,∣N+1⟩|0\rangle, |1\rangle, \dots, |N\rangle, |N+1\rangle∣0⟩,∣1⟩,…,∣N⟩,∣N+1⟩: ∣0⟩|0\rangle∣0⟩ is the zero-exciton state (population lost to the environment), ∣j⟩|j\rangle∣j⟩ for 1≤j≤N1 \le j \le N1≤j≤N is one excitation on site jjj, and ∣N+1⟩|N+1\rangle∣N+1⟩ is the sink (the reaction centre). The operators σj+=∣j⟩⟨0∣\sigma_j^+ = |j\rangle\langle 0|σj+​=∣j⟩⟨0∣ and σj−=∣0⟩⟨j∣\sigma_j^- = |0\rangle\langle j|σj−​=∣0⟩⟨j∣ create and destroy the excitation on site jjj.

The FCN Hamiltonian HHH (with ℏ=1\hbar = 1ℏ=1) has ⟨j∣H∣j⟩=ωj\langle j|H|j\rangle = \omega_j⟨j∣H∣j⟩=ωj​, the site energies, and ⟨i∣H∣j⟩=J\langle i|H|j\rangle = J⟨i∣H∣j⟩=J for every pair of distinct sites, and vanishes on ∣0⟩|0\rangle∣0⟩ and ∣N+1⟩|N+1\rangle∣N+1⟩. For a real rate rrr and an operator ccc write

Dr,c(ρ)=r [2cρc†−{c†c,ρ}].\mathcal D_{r,c}(\rho) = r\,\bigl[2c\rho c^\dagger - \{c^\dagger c, \rho\}\bigr].Dr,c​(ρ)=r[2cρc†−{c†c,ρ}].

The state ρ(t)\rho(t)ρ(t), a complex (N+2)×(N+2)(N+2)\times(N+2)(N+2)×(N+2) matrix, obeys the Lindblad master equation ρ˙=L(ρ)\dot\rho = \mathcal L(\rho)ρ˙​=L(ρ) with

L(ρ)=−i[H,ρ]+∑j=1NDΓj, σj−(ρ)+∑j=1NDγj, ∣j⟩⟨j∣(ρ)+DΓN+1, ∣N+1⟩⟨k∣(ρ).\mathcal L(\rho) = -i[H,\rho] + \sum_{j=1}^N \mathcal D_{\Gamma_j,\,\sigma_j^-}(\rho) + \sum_{j=1}^N \mathcal D_{\gamma_j,\,|j\rangle\langle j|}(\rho) + \mathcal D_{\Gamma_{N+1},\,|N+1\rangle\langle k|}(\rho).L(ρ)=−i[H,ρ]+j=1∑N​DΓj​,σj−​​(ρ)+j=1∑N​Dγj​,∣j⟩⟨j∣​(ρ)+DΓN+1​,∣N+1⟩⟨k∣​(ρ).

The terms are coherent hopping, dissipation to the environment at rates Γj\Gamma_jΓj​, pure dephasing at rates γj\gamma_jγj​, and irreversible decay into the sink from a chosen site kkk at rate ΓN+1\Gamma_{N+1}ΓN+1​. So ρ(t)=etLρ(0)\rho(t) = e^{t\mathcal L}\rho(0)ρ(t)=etLρ(0). The initial state is ρ(0)=∣1⟩⟨1∣\rho(0) = |1\rangle\langle 1|ρ(0)=∣1⟩⟨1∣, and transport is measured by the sink population

psink(t)=2ΓN+1∫0tρkk(t′) dt′.p_{\rm sink}(t) = 2\Gamma_{N+1}\int_0^t \rho_{kk}(t')\,dt'.psink​(t)=2ΓN+1​∫0t​ρkk​(t′)dt′.

The goal concerns the FCN of §II.A: ωj=0\omega_j = 0ωj​=0, Γj=0\Gamma_j = 0Γj​=0, the sink attached at k=Nk = Nk=N, and a uniform dephasing rate γj=γ≥0\gamma_j = \gamma \ge 0γj​=γ≥0.

Formalization targets

Goal: noise-free and dephased limits

For N≥2N \ge 2N≥2, J≠0J \ne 0J=0 and ΓN+1>0\Gamma_{N+1} > 0ΓN+1​>0:

γ=0:lim⁡t→∞psink(t)=1N−1,γ>0:lim⁡t→∞psink(t)=1.\gamma = 0:\quad \lim_{t\to\infty} p_{\rm sink}(t) = \frac{1}{N-1}, \qquad\qquad \gamma > 0:\quad \lim_{t\to\infty} p_{\rm sink}(t) = 1.γ=0:t→∞lim​psink​(t)=N−11​,γ>0:t→∞lim​psink​(t)=1.

The first limit is Eq. (5) of the paper. The second is the claim of §II.C, confirmed for uniform dephasing in Appendix A.3, Eq. (A30). The coupling JJJ, the sink rate and the dephasing rate are left free; neither limit depends on them.

Milestones

  1. (A7) Population sum rule: 1=∑j=1Nρjj(t)+ρ00(t)+psink(t)1 = \sum_{j=1}^N \rho_{jj}(t) + \rho_{00}(t) + p_{\rm sink}(t)1=∑j=1N​ρjj​(t)+ρ00​(t)+psink​(t) for all ttt.
  2. §II.A spectrum. ∣ϕ⟩=N−1/2∑j∣j⟩|\phi\rangle = N^{-1/2}\sum_j |j\rangle∣ϕ⟩=N−1/2∑j​∣j⟩ has energy J(N−1)J(N-1)J(N−1). The states ∣ψj⟩=∣1⟩−∣j⟩|\psi_j\rangle = |1\rangle - |j\rangle∣ψj​⟩=∣1⟩−∣j⟩, j=2,…,Nj = 2,\dots,Nj=2,…,N, have energy −J-J−J, and together with ∣ϕ⟩|\phi\rangle∣ϕ⟩ they span the site space.
  3. Eq. (8). ∣1⟩=1N−1[∑j=2N−1∣ψj⟩+N∣ϕ⟩−∣N⟩]|1\rangle = \frac{1}{N-1}\bigl[\sum_{j=2}^{N-1}|\psi_j\rangle + \sqrt N|\phi\rangle - |N\rangle\bigr]∣1⟩=N−11​[∑j=2N−1​∣ψj​⟩+N​∣ϕ⟩−∣N⟩].
  4. Invariant states. In the noiseless FCN, an eigenstate of HHH with no overlap with site NNN does not evolve, and psink≡0p_{\rm sink} \equiv 0psink​≡0.
  5. Eqs. (6)–(7). For N≥3N \ge 3N≥3, ρ(t)→N−2N−1∣Ψ⟩⟨Ψ∣+1N−1∣N+1⟩⟨N+1∣\rho(t) \to \frac{N-2}{N-1}|\Psi\rangle\langle\Psi| + \frac1{N-1}|N+1\rangle\langle N+1|ρ(t)→N−1N−2​∣Ψ⟩⟨Ψ∣+N−11​∣N+1⟩⟨N+1∣.
  6. (A14). The closed form of ρNN(t)\rho_{NN}(t)ρNN​(t) for the noiseless FCN, N≥3N \ge 3N≥3.
  7. Appendix A.1. The closed linear system of six equations for Λ=∑i,jρij\Lambda = \sum_{i,j}\rho_{ij}Λ=∑i,j​ρij​, X+iY=∑jρNjX + iY = \sum_j \rho_{Nj}X+iY=∑j​ρNj​, ρNN\rho_{NN}ρNN​, ρ00\rho_{00}ρ00​ and psinkp_{\rm sink}psink​ under uniform ω\omegaω, Γ\GammaΓ, γ\gammaγ.

Significance

The result. The noise-free limit 1/(N−1)1/(N-1)1/(N−1) shows that a perfectly coherent, fully symmetric network is a poor transporter: for N=10N = 10N=10 only 1/91/91/9 of the excitation reaches the sink, whereas a classical random walk on the same graph delivers all of it. The dephased limit 111 shows that arbitrarily weak local noise restores complete transfer. Together they are the cleanest exactly solvable instance of dephasing-assisted transport. The invariant-subspace argument behind them (milestones 2–5) also predicts which states are protected from a sink, a mechanism related to coherent population trapping in quantum optics and condensed-matter systems.

Formalizing it. The paper derives these limits from Laplace-domain calculations and residue computations, some of them only sketched. A machine-checked proof would settle the exact constants, the hypotheses under which each limit holds (the necessity of J≠0J \ne 0J=0 and ΓN+1>0\Gamma_{N+1} > 0ΓN+1​>0, and the case N=2N = 2N=2), and the passage from the matrix exponential to the collective variables. As far as is known, none of these results has been formalized. The development also produces reusable pieces: the Lindblad generator of a single-excitation network with a sink, the trace identity (A7), and the spectrum of the complete-graph hopping Hamiltonian.

Difficulty

The obvious route is to compute etLe^{t\mathcal L}etL, but L\mathcal LL acts on an (N+2)2(N+2)^2(N+2)2-dimensional space for arbitrary NNN, so no fixed-size computation applies. The noise-free limit hinges on an exact cancellation: N−2N−1\frac{N-2}{N-1}N−1N−2​ of the weight lies in an HHH-eigenspace that is invisible to the sink, and the remainder must be shown to drain completely, which is a statement about the spectrum of a non-normal generator on the complementary subspace. Under dephasing that invariant subspace no longer exists, but the reduced six-variable system still has to be shown to have psink=1p_{\rm sink} = 1psink​=1 as its only attracting steady state, for every γ>0\gamma > 0γ>0 and every NNN. In the paper this is done through a final-value theorem applied to a fifth-order characteristic polynomial (A26), which is misprinted. A proof that the limit exists, and not only what it equals, is part of the task.

Formalization scope

  • Basis and operators. The basis is Fin (N + 2) in the paper's numbering (0 = zero-exciton state, 1…N = sites, N + 1 = sink), with natural-number indices cast into it. Operators are Matrix (Fin (N + 2)) (Fin (N + 2)) ℂ.
  • Hopping and rates. The hopping is normalized as ⟨i∣H∣j⟩=J\langle i|H|j\rangle = J⟨i∣H∣j⟩=J, which matches (A1), (A34) and the spectrum on p. 4. The rates multiply 2cρc†−{c†c,ρ}2c\rho c^\dagger - \{c^\dagger c,\rho\}2cρc†−{c†c,ρ} with no factor ½, as in Eqs. (2)–(4).
  • Evolution. ρ(t)\rho(t)ρ(t) is semigroupEvolution of the published definition P16, that is, NormedSpace.exp of tLt\mathcal LtL, applied to ∣1⟩⟨1∣|1\rangle\langle 1|∣1⟩⟨1∣.
  • Sink population. psinkp_{\rm sink}psink​ is the interval integral of the real part of ρkk\rho_{kk}ρkk​, as defined on p. 3. It is not the sink entry ρN+1,N+1\rho_{N+1,N+1}ρN+1,N+1​; that the two agree is part of milestone 1.
  • Added hypotheses. The goal assumes N≥2N \ge 2N≥2, J≠0J \ne 0J=0 and ΓN+1>0\Gamma_{N+1} > 0ΓN+1​>0; without any one of them the limits fail. Milestones 5 and 6 assume N≥3N \ge 3N≥3, where ∣Ψ⟩|\Psi\rangle∣Ψ⟩ and the closed form are defined.
  • Uniform dephasing. The dephased clause is stated only for a uniform rate γj=γ\gamma_j = \gammaγj​=γ, which is the case the paper solves. It is quantified over every γ>0\gamma > 0γ>0.

A trivializing formalization is ruled out by construction: NNN and γ\gammaγ are free, psinkp_{\rm sink}psink​ unfolds to an integral of an entry of the matrix exponential of the literal generator, and none of the limits is built into a definition.

Needed infrastructure includes calculus for t↦etLXt \mapsto e^{tL}Xt↦etLX (derivatives, HasDerivAt of entries, the fundamental theorem of calculus for psinkp_{\rm sink}psink​), invariant-subspace arguments for linear ODEs, and asymptotics of linear systems with a stable matrix. Contributions of general lemmas about Lindblad semigroups (trace preservation, Hermiticity preservation, stationary states) are welcome and reusable beyond this mission.

Not formalized here: Eq. (9) (static disorder), Eq. (10) (dissipation), §II.D–§V, the Laplace-domain route (A9)–(A13) and (A25)–(A29), the two-level system (A32), and the general networks of (A39)–(A40).

Selected references

  • F. Caruso, A. W. Chin, A. Datta, S. F. Huelga, M. B. Plenio, Highly efficient energy excitation transfer in light-harvesting complexes: The fundamental role of noise-assisted transport, J. Chem. Phys. 131, 105106 (2009). https://arxiv.org/abs/0901.4454v2 — https://doi.org/10.1063/1.3223548
  • G. S. Engel et al., Evidence for wavelike energy transfer through quantum coherence in photosynthetic systems, Nature 446, 782 (2007). https://doi.org/10.1038/nature05678
  • M. Mohseni, P. Rebentrost, S. Lloyd, A. Aspuru-Guzik, Environment-assisted quantum walks in photosynthetic energy transfer, J. Chem. Phys. 129, 174106 (2008). https://doi.org/10.1063/1.3002335
  • M. B. Plenio, S. F. Huelga, Dephasing-assisted transport: quantum networks and biomolecules, New J. Phys. 10, 113019 (2008). https://doi.org/10.1088/1367-2630/10/11/113019
  • P. Rebentrost, M. Mohseni, I. Kassal, S. Lloyd, A. Aspuru-Guzik, Environment-assisted quantum transport, New J. Phys. 11, 033003 (2009). https://doi.org/10.1088/1367-2630/11/3/033003
  • G. Lindblad, On the generators of quantum dynamical semigroups, Commun. Math. Phys. 48, 119 (1976). https://doi.org/10.1007/BF01608499
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Entanglement-Assisted Classical Capacity of Noisy Quantum ChannelsResearch Paper

Motivation

Prior entanglement between sender and receiver, which exactly doubles the classical capacity of a noiseless quantum channel, can increase the classical capacity of some noisy quantum channels by an arbitrarily large constant factor depending on the channel, relative to the best known classical capacity achievable without entanglement. The enhancement factor is greatest for very noisy channels, with positive classical capacity but zero quantum capacity. Although such quantum channels can be simulated classically, no violation of causality is implied, because the simulation requires at least as much forward classical communication as the entanglement-assisted classical capacity of the channel being simulated. We obtain exact expressions for the entanglement-assisted capacity of depolarizing and erasure channels in d dimensions.

This mission is the statement-level formalization of Entanglement-Assisted Classical Capacity of Noisy Quantum Channels (arXiv:quant-ph/9904023v5). Every numbered result of the paper was scanned. The results stated here are open sorry goals, ready for solvers to prove.

What is formalized

14 statements of the paper are in Lean 4 (Mathlib 0df444a). The goal theorem is Abstract main result / equation (3): depolarizing assisted capacity (Abstract main result / equation (3): depolarizing assisted capacity, PDF p. 3). The milestones are the other numbered results, in the paper's order, each quoting the paper.

The paper's own objects are the definition item of this mission. Objects shared across papers come from the prove2quantum library and from earlier papers' missions, listed as references.

Provenance: prove2quantum's pipeline drafted each statement (gpt-6.1-sol on Stanford's Sherlock cluster). A blind read-back, written without seeing the paper, is attached to every item. An independent moderator compared each statement against the paper and passed the whole paper without edits.

Deferred results

4 results of the paper are not stated yet, because the library lacks an interface they need:

  • Unnumbered C <= CE <= FCCC: A resource-counted finite adaptive bipartite channel-simulation model with arbitrary local ancillas, message-independent prior pure entanglement, free backward classical communication, an actual forward classical arm, and asymptotically faithful reference-preserving simulation. (hard)
  • Erasure flags simulate depolarization and all corresponding capacity inequalities: Source-compatible Q2 from counted noisy-channel calls interleaved with adaptive finite LOCC, initially with no shared entanglement. (hard)
  • Again the difference between the bounds approaches H2(x): A source-pinned noise regime for the asserted limit of the signed quantum-bound gap. (source-ambiguity)
  • Author note [9]: A transpose/label convention or restriction making the three induced classical transition matrices literally identical. (source-ambiguity)

Selected references

  • Entanglement-Assisted Classical Capacity of Noisy Quantum Channels, arXiv:quant-ph/9904023v5, https://arxiv.org/abs/quant-ph/9904023v5
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The operational meaning of quantum conditional informationResearch Paper

Motivation

How correlated are two quantum systems from the perspective of a third? We answer this by providing an optimal quantum state redistribution protocol for multipartite product sources. Specifically, given an arbitrary quantum state of three systems, where Alice holds two and Bob holds one, we identify the cost, in terms of quantum communication and entanglement, for Alice to give one of her parts to Bob. The communication cost gives the first known operational interpretation to quantum conditional mutual information. The optimal procedure is self-dual under time reversal and is perfectly composable. This generalizes known protocols such as the state merging and fully quantum Slepian-Wolf protocols, from which almost every known protocol in quantum Shannon theory can be derived.

This mission is the statement-level formalization of The operational meaning of quantum conditional information (arXiv:quant-ph/0612050v2). Every numbered result of the paper was scanned. The results stated here are open sorry goals, ready for solvers to prove.

What is formalized

8 statements of the paper are in Lean 4 (Mathlib 0df444a). The goal theorem is Exact state-redistribution rate region and optimal corner (Main result: exact state-redistribution rate region and corner, Eqs. (1)–(2), PDF p. 2). The milestones are the other numbered results, in the paper's order, each quoting the paper.

The paper's own objects are the definition item of this mission. Objects shared across papers come from the prove2quantum library and from earlier papers' missions, listed as references.

Provenance: prove2quantum's pipeline drafted each statement (gpt-6.1-sol on Stanford's Sherlock cluster). A blind read-back, written without seeing the paper, is attached to every item. An independent moderator compared each statement against the paper and passed the whole paper without edits.

Deferred results

2 results of the paper are not stated yet, because the library lacks an interface they need:

  • w-state: Independently moderated correction of the printed W-state numerical communication cost (source-ambiguity)
  • zero-communication-entanglement: Independently moderated correction of the printed flagged-state entanglement-cost sign (source-ambiguity)

Selected references

  • The operational meaning of quantum conditional information, arXiv:quant-ph/0612050v2, https://arxiv.org/abs/quant-ph/0612050v2
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Quantum Information·Captain: Goku

Algorithm to compute the rank and a Cartan subalgebra of a matrix Lie algebra with MathematicaResearch Paper

Motivation

We present in this paper a set of routines constructed to compute the rank of a matrix Lie algebra and also to determine a Cartan subalgebra from a given list of elements

This mission is the statement-level formalization of Algorithm to compute the rank and a Cartan subalgebra of a matrix Lie algebra with Mathematica (arXiv:math/0205235v1). Every numbered result of the paper was scanned. The results stated here are open sorry goals, ready for solvers to prove.

What is formalized

16 statements of the paper are in Lean 4 (Mathlib 0df444a). The goal theorem is so(n): BSo ordered basis (so(n): BSo ordered basis, PDF p. 5). The milestones are the other numbered results, in the paper's order, each quoting the paper.

The paper's own objects are the definition item of this mission. Objects shared across papers come from the prove2quantum library and from earlier papers' missions, listed as references.

Provenance: prove2quantum's pipeline drafted each statement (gpt-6.1-sol on Stanford's Sherlock cluster). A blind read-back, written without seeing the paper, is attached to every item. An independent moderator compared each statement against the paper and passed the whole paper without edits.

Deferred results

2 results of the paper are not stated yet, because the library lacks an interface they need:

  • Abstract and introduction: rank/Cartan extension algorithm: A valid and fully specified exact Cartan-extension routine on the advertised real semisimple matrix embeddings, including guards and symbolic branch/parameter selection. (source-ambiguity)
  • Introduction, unnumbered Teorema: claimed Cartan characterization: A valid Cartan characterization with the original quantification over all real semisimple matrix embeddings and all their Cartan subalgebras. (source-ambiguity)

Selected references

  • Algorithm to compute the rank and a Cartan subalgebra of a matrix Lie algebra with Mathematica, arXiv:math/0205235v1, https://arxiv.org/abs/math/0205235v1
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Representation of Quantum Circuits with Clifford and π/8π/8π/8 GatesResearch Paper

Motivation

In this paper, we introduce the notion of a normal form of one qubit quantum circuits over the basis {H,P,T}\{H, P, T\}{H,P,T}, where HHH, PPP and TTT denote the Hadamard, Phase and π/8π/8π/8 gates, respectively. This basis is known as the {\it standard set} and its universality has been shown by Boykin et al. [FOCS '99]. Our normal form has several nice properties: (i) Every circuit over this basis can easily be transformed into a normal form, and (ii) Every two normal form circuits compute same unitary matrix if and only if both circuits are identical. We also show that the number of unitary operations that can be represented by a circuit over this basis that contains at most nnn TTT-gates is exactly 192⋅(3⋅2n−2)192 \cdot (3 \cdot 2^n - 2)192⋅(3⋅2n−2).

This mission is the statement-level formalization of Representation of Quantum Circuits with Clifford and π/8π/8π/8 Gates (arXiv:0806.3834v1). Every numbered result of the paper was scanned. The results stated here are open sorry goals, ready for solvers to prove.

What is formalized

20 statements of the paper are in Lean 4 (Mathlib 0df444a). The goal theorem is Theorem 1 (seed paper result): unique exact normal form (Theorem 1 (seed paper result): unique exact normal form, PDF p. 6). The milestones are the other numbered results, in the paper's order, each quoting the paper.

The paper's own objects are the definition item of this mission. Objects shared across papers come from the prove2quantum library and from earlier papers' missions, listed as references.

Provenance: prove2quantum's pipeline drafted each statement (gpt-6.1-sol on Stanford's Sherlock cluster). A blind read-back, written without seeing the paper, is attached to every item. An independent moderator compared each statement against the paper and passed the whole paper without edits.

Selected references

  • Representation of Quantum Circuits with Clifford and π/8π/8π/8 Gates, arXiv:0806.3834v1, https://arxiv.org/abs/0806.3834v1
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Quantum Information·Captain: Goku

Remarks on Matsumoto and Amano's normal form for single-qubit Clifford+T operatorsResearch Paper

Motivation

Matsumoto and Amano (2008) showed that every single-qubit Clifford+T operator can be uniquely written of a particular form, which we call the Matsumoto-Amano normal form. In this mostly expository paper, we give a detailed and streamlined presentation of Matsumoto and Amano's results, simplifying some proofs along the way. We also point out some corollaries to Matsumoto and Amano's work, including an intrinsic characterization of the Clifford+T subgroup of SO(3), which also yields an efficient T-optimal exact single-qubit synthesis algorithm. Interestingly, this also gives an alternative proof of Kliuchnikov, Maslov, and Mosca's exact synthesis result for the Clifford+T subgroup of U(2).

This mission is the statement-level formalization of Remarks on Matsumoto and Amano's normal form for single-qubit Clifford+T operators (arXiv:1312.6584v2). Every numbered result of the paper was scanned. The results stated here are open sorry goals, ready for solvers to prove.

What is formalized

26 statements of the paper are in Lean 4 (Mathlib 0df444a). The goal theorem is §1 main result: MA existence, uniqueness, optimality and effective normalization (§1 main result: MA existence, uniqueness, optimality and effective normalization, PDF p. 1). The milestones are the other numbered results, in the paper's order, each quoting the paper.

The paper's own objects are the definition item of this mission. Objects shared across papers come from the prove2quantum library and from earlier papers' missions, listed as references.

Provenance: prove2quantum's pipeline drafted each statement (gpt-6.1-sol on Stanford's Sherlock cluster). A blind read-back, written without seeing the paper, is attached to every item. An independent moderator compared each statement against the paper and passed the whole paper without edits.

Deferred results

4 results of the paper are not stated yet, because the library lacks an interface they need:

  • Theorem 5.1: matrix-input optimal exact synthesis: An operational exact-arithmetic synthesis machine over encoded quadratic/cyclotomic coefficients, implementing parity-driven U -> N^{-1}U recursion with a fixed Clifford lookup and charged arithmetic operations, while preserving absolute phase (or the specified Bloch image) and returning actual normal-form/elementary-word data. (hard)
  • Theorem 6.5: SO(3) ring characterization and synthesis: An operational exact-arithmetic synthesis machine over encoded quadratic/cyclotomic coefficients, implementing parity-driven U -> N^{-1}U recursion with a fixed Clifford lookup and charged arithmetic operations, while preserving absolute phase (or the specified Bloch image) and returning actual normal-form/elementary-word data. (hard)
  • Remark 6.6: linear SO(3) synthesis: An operational exact-arithmetic synthesis machine over encoded quadratic/cyclotomic coefficients, implementing parity-driven U -> N^{-1}U recursion with a fixed Clifford lookup and charged arithmetic operations, while preserving absolute phase (or the specified Bloch image) and returning actual normal-form/elementary-word data. (hard)
  • Section 8.1 Clifford E/X/S/omega coordinates: A correct coordinate range for the claimed unique E^a X^b S^c omega^d parametrization. (source-ambiguity)

Selected references

  • Remarks on Matsumoto and Amano's normal form for single-qubit Clifford+T operators, arXiv:1312.6584v2, https://arxiv.org/abs/1312.6584v2
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The capacity of the quantum depolarizing channelResearch Paper

Motivation

The information carrying capacity of the d-dimensional depolarizing channel is computed. It is shown that this capacity can be achieved by encoding messages as products of pure states belonging to an orthonormal basis of the state space, and using measurements which are products of projections onto this same orthonormal basis. In other words, neither entangled signal states nor entangled measurements give any advantage for information capacity. The result follows from an additivity theorem for the capacity of the product of the depolarizing channel with an arbitrary channel. We establish the Amosov-Holevo-Werner p-norm conjecture for this product channel for all p >= 1, and deduce from this the additivity of the minimal entropy and of the Holevo quantity.

This mission is the statement-level formalization of The capacity of the quantum depolarizing channel (arXiv:quant-ph/0204172v2). Every numbered result of the paper was scanned. The results stated here are open sorry goals, ready for solvers to prove.

What is formalized

14 statements of the paper are in Lean 4 (Mathlib 0df444a). The goal theorem is Depolarizing channel: exact unassisted classical capacity (Theorem 1 / abstract: exact unassisted classical capacity and basis strategy, PDF p. 7). The milestones are the other numbered results, in the paper's order, each quoting the paper.

The paper's own objects are the definition item of this mission. Objects shared across papers come from the prove2quantum library and from earlier papers' missions, listed as references.

Provenance: prove2quantum's pipeline drafted each statement (gpt-6.1-sol on Stanford's Sherlock cluster). A blind read-back, written without seeing the paper, is attached to every item. An independent moderator compared each statement against the paper and passed the whole paper without edits.

Selected references

  • The capacity of the quantum depolarizing channel, arXiv:quant-ph/0204172v2, https://arxiv.org/abs/quant-ph/0204172v2
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Capacities of Quantum Erasure ChannelsResearch Paper

Motivation

The quantum analog of the classical erasure channel provides a simple example of a channel whose asymptotic capacity for faithful transmission of intact quantum states, with and without the assistance of a two-way classical side channel, can be computed exactly. We derive the quantum and classical capacities for the quantum erasure channel and related channels, and compare them to the depolarizing channel, for which only upper and lower bounds on the capacities are known.

This mission is the statement-level formalization of Capacities of Quantum Erasure Channels (arXiv:quant-ph/9701015v2). Every numbered result of the paper was scanned. The results stated here are open sorry goals, ready for solvers to prove.

What is formalized

8 statements of the paper are in Lean 4 (Mathlib 0df444a). The goal theorem is Exact capacities of the qubit quantum erasure channel (Eq. (2), PDF p. 2). The milestones are the other numbered results, in the paper's order, each quoting the paper.

The paper's own objects are the definition item of this mission. Objects shared across papers come from the prove2quantum library and from earlier papers' missions, listed as references.

Provenance: prove2quantum's pipeline drafted each statement (gpt-6.1-sol on Stanford's Sherlock cluster). A blind read-back, written without seeing the paper, is attached to every item. An independent moderator compared each statement against the paper and passed the whole paper without edits.

Selected references

  • Capacities of Quantum Erasure Channels, arXiv:quant-ph/9701015v2, https://arxiv.org/abs/quant-ph/9701015v2
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Quantum Information·Captain: Goku

Remarks on the classical capacity of quantum channelResearch Paper

Motivation

A direct proof of the relation between the one-shot classical capacity and the minimal output entropy for covariant quantum channels is suggested. The structure of covariant channels is described in some detail. A simple proof of a general inequality for entanglement-assisted classical capacity is given.

This mission is the statement-level formalization of Remarks on the classical capacity of quantum channel (arXiv:quant-ph/0212025v1). Every numbered result of the paper was scanned. The results stated here are open sorry goals, ready for solvers to prove.

What is formalized

7 statements of the paper are in Lean 4 (Mathlib 0df444a). The goal theorem is Irreducible covariance gives bistochasticity and the capacity–entropy identity (§1, theorem; (1)–(3), PDF p. 2). The milestones are the other numbered results, in the paper's order, each quoting the paper.

The paper's own objects are the definition item of this mission. Objects shared across papers come from the prove2quantum library and from earlier papers' missions, listed as references.

Provenance: prove2quantum's pipeline drafted each statement (gpt-6.1-sol on Stanford's Sherlock cluster). A blind read-back, written without seeing the paper, is attached to every item. An independent moderator compared each statement against the paper and passed the whole paper without edits.

Selected references

  • Remarks on the classical capacity of quantum channel, arXiv:quant-ph/0212025v1, https://arxiv.org/abs/quant-ph/0212025v1
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Quantum Information·Captain: Goku

An additive and operational entanglement measure: conditional entanglement of mutual informationResearch Paper

Motivation

Based on the monogamy of entanglement, we develop the technique of quantum conditioning to build an {\it additive} entanglement measure: the conditional entanglement of mutual information. Its {\it operational} meaning is elaborated to be the minimal net "flow of qubits" in the process of partial state merging. The result and conclusion can also be generalized to multipartite entanglement cases.

This mission is the statement-level formalization of An additive and operational entanglement measure: conditional entanglement of mutual information (arXiv:0804.3683v2). Every numbered result of the paper was scanned. The results stated here are open sorry goals, ready for solvers to prove.

What is formalized

12 statements of the paper are in Lean 4 (Mathlib 0df444a). The goal theorem is Proposition 1: bipartite additivity (Proposition 1: bipartite additivity (the page-1 seed pinned to its numbered theorem), PDF p. 3). The milestones are the other numbered results, in the paper's order, each quoting the paper.

The paper's own objects are the definition item of this mission. Objects shared across papers come from the prove2quantum library and from earlier papers' missions, listed as references.

Provenance: prove2quantum's pipeline drafted each statement (gpt-6.1-sol on Stanford's Sherlock cluster). A blind read-back, written without seeing the paper, is attached to every item. An independent moderator compared each statement against the paper and passed the whole paper without edits.

Deferred results

4 results of the paper are not stated yet, because the library lacks an interface they need:

  • Unnumbered: fixed-extension partial state merging cost and route independence: Admissible resource/protocol class and ancillary-work accounting for the signed net-qubit PSM/PSD minimum (source-ambiguity)
  • Proposition 2: CEMI as optimized partial state merging cost: Admissible resource/protocol class and ancillary-work accounting for the signed net-qubit PSM/PSD minimum (source-ambiguity)
  • Proposition 4: multipartite CEMI as optimized partial state merging cost: Admissible resource/protocol class and ancillary-work accounting for the signed net-qubit PSM/PSD minimum (source-ambiguity)
  • Unnumbered: reversed process partial state distribution: Admissible resource/protocol class and ancillary-work accounting for the signed net-qubit PSM/PSD minimum (source-ambiguity)

Selected references

  • An additive and operational entanglement measure: conditional entanglement of mutual information, arXiv:0804.3683v2, https://arxiv.org/abs/0804.3683v2
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Quantum Information·Captain: Goku

Quantum data processing and error correctionResearch Paper

Motivation

This paper investigates properties of noisy quantum information channels. We define a new quantity called {\em coherent information} which measures the amount of quantum information conveyed in the noisy channel. This quantity can never be increased by quantum information processing, and it yields a simple necessary and sufficient condition for the existence of perfect quantum error correction.

This mission is the statement-level formalization of Quantum data processing and error correction (arXiv:quant-ph/9604022v1). Every numbered result of the paper was scanned. The results stated here are open sorry goals, ready for solvers to prove.

What is formalized

8 statements of the paper are in Lean 4 (Mathlib 0df444a). The goal theorem is Coherent information bound and environment factorization criterion (§4, Eq.(4) and equality criterion, PDF p. 10). The milestones are the other numbered results, in the paper's order, each quoting the paper.

The paper's own objects are the definition item of this mission. Objects shared across papers come from the prove2quantum library and from earlier papers' missions, listed as references.

Provenance: prove2quantum's pipeline drafted each statement (gpt-6.1-sol on Stanford's Sherlock cluster). A blind read-back, written without seeing the paper, is attached to every item. An independent moderator compared each statement against the paper and passed the whole paper without edits.

Selected references

  • Quantum data processing and error correction, arXiv:quant-ph/9604022v1, https://arxiv.org/abs/quant-ph/9604022v1
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Computational Complexity·Captain: Lucas

PRIMES is in P: the polynomial Fermat congruence, the introspective groups, and the correctness of the Agrawal-Kayal-Saxena algorithmResearch Paper

PRIMES is in P: the polynomial Fermat congruence, the introspective groups, and the correctness of the Agrawal-Kayal-Saxena algorithm

1. Motivation

Agrawal, Kayal, and Saxena's "PRIMES is in P" (Annals of Mathematics 160 (2004) 781-793) settled a question open since the birth of complexity theory: primality has an unconditional, deterministic, polynomial-time test. The paper's algorithm is elementary - six steps: reject perfect powers; fix a small r; reject trivial factor witnesses; accept small inputs; test the congruence (X + a)^n = X^n + a modulo X^r - 1 for a = 1, ..., ell; accept. The mathematical heart is Lemma 2.1, a generalization of Fermat's Little Theorem to polynomial rings: for n at least 2 and a coprime to n, n is prime if and only if (X + a)^n = X^n + a in Z_n[X]. The correctness of the harder direction runs through the introspective machinery of Section 4: for a prime factor p of n with o_r(p) > 1, the numbers of I = {(n/p)^i p^j} are introspective for the polynomials of P = {the products of the generators X, X+1, ..., X+ell}; the residues of I generate a group G modulo r of size t > log^2 n; the images of P generate a group G-cal in the field F = F_p[X]/(h), h an irreducible factor of the r-th cyclotomic polynomial over F_p; Lenstra's lower bound and the Kalai-Sahai-Sudan upper bound on the size of G-cal collide unless n is a power of p, and step 1 excludes prime powers, so n is prime. Section 5 bounds the arithmetic work: O~(log^(21/2) n), unconditionally.

The mission formalizes the paper's mathematical content in Lean 4. The goal statement is Theorem 4.1: the algorithm of the algorithm layer returns PRIME if and only if n is prime. The milestones are the ingredients in attack order: the polynomial Fermat characterization (Lemma 2.1); the lcm lower bound (Lemma 3.1); the existence of a small r with large order (Lemma 4.3); the closure of introspection under multiplication (Lemmas 4.5 and 4.6); Lenstra's injectivity bound (Lemma 4.7); the Kalai-Sahai-Sudan collision bound (Lemma 4.8); and the polynomial work bound of Section 5 (Theorem 5.1, in generous integer form).

The source document is the uploaded paper (annals-v160-n2-p12.pdf in the mission materials).

2. The formalization fragment and conventions

The formalization is a two-layer development in the namespace AKS. The polynomial layer (AKS_poly) carries the congruences: congruence (1) as an equality in Z_n[X], congruence (2) as divisibility by X^r - 1 in Z_n[X], Definition 4.4's introspection relation over F_p[X], and the set P of products of the generators. The algorithm layer (AKS_alg) carries the arithmetic scaffolding and the algorithm itself: the integer logarithm, the multiplicative order, the lcm of the first numbers, the perfect-power predicate, the search for r, the loop bound, the six-step decision function, the set I and the residue group G, and the work measure of Section 5.

The following choices are disclosed explicitly.

  1. Compile verification by CI substitution. The authoring environment has no local Lean toolchain, so the compile check demanded by the mission is performed by the continuous integration of the repository (Lean 4.33 with Mathlib): all Lean code below was compiled there before this proposal was submitted, and the code attached to the items is byte-identical to the compiled modules.

  2. The theorem drafts carry sorry. The eight theorem statements are submitted as drafts for human review; each proof body is a single sorry marking the work the mission proposes to complete. The compilation therefore succeeds with exactly one "declaration uses 'sorry'" warning per theorem file.

  3. Generous integer encodings of the logarithms. The paper's real-valued log n appears in the algorithm only through the threshold o_r(n) > log^2 n of step 2 and the loop bound ell = floor(sqrt(phi(r)) log n) of step 5. The mission encodes both with logUp n = floor(log2 n) + 1, which is strictly larger than log2 n: step 2 searches for the smallest r with ordR r n > logUp(n)^2, and ell is the floor of the product of the square root of phi(r) and logUp n, encoded exactly as the floor of the square root of phi(r) logUp(n)^2. Both encodings are generous in the directions that preserve correctness: primes pass congruence (2) for every a and r, so a larger threshold and a longer loop never reject a prime; and for the converse the larger threshold and loop only strengthen the group bounds that force composites out. The integer bookkeeping of the final chain - floor(sqrt t) logUp n + 1 at least sqrt t log2 n - is part of the proposed work of the goal, with the generosity supplying the slack.

  4. The algorithm layer transcribes the six steps literally, with computable searches inside provable windows and classical decision where only the extension matters. ordR r a is the least k < r with a^k = 1 (mod r) - the window k < r is faithful because every multiplicative order divides phi(r) < r - and 0 when gcd(a, r) > 1. smallestR n searches the window bounded by the r_exists milestone's bound. aksDecide is stated with classical decision (open Classical, noncomputable): no execution of the test is ever needed, only its extensional behavior. aksWork is a computable schoolbook work measure charging logUp(n)^6 for step 1, r(logUp n + 1) for the searches of steps 2 and 3, and ell r n (logUp n + 1)(r + 1)^2 for the congruence loop of step 5.

  5. The groups are encoded by witness windows, and the two bounds are stated in the paper's forms. G is the Finset of residues modulo r of the numbers of I, encoded by the witness window i, j < r - faithful under the coprimality of n/p and p to r, because both orders then divide phi(r) at most r, so every residue of an I-number is achieved inside the window. Lemma 4.7 is stated in the paper's form: two distinct polynomials of P, both of degree less than t, map to distinct elements of F = F_p[X]/(h) (the field is AdjoinRoot h; the hypotheses carry h dividing X^r - 1, the primitivity - h not dividing X^k - 1 for 0 < k < r - irreducibility by instance, the introspectivity of I for P, and t at most the size of G). Lemma 4.8 is stated in the collision form: unless n is a power of p, there are m2 < m1 at most n^(floor(sqrt t)), colliding modulo r inside the bounded set I-hat, such that every image of P in F satisfies y^m1 = y^m2. The cardinality bookkeeping between these forms and the size of G-cal - stars-and-bars for the lower bound with the unique factorization of the generator products, and the root bound of a polynomial over a field for the upper - is carried by Mathlib and is part of the goal's proposed work.

  6. The field F = F_p[X]/(h) is taken with its factor h as an explicit parameter. The statements do not construct h; they carry h dividing X^r - 1, primitivity, and irreducibility as hypotheses (the latter two as Fact-class instances). The existence of h - an irreducible factor of the r-th cyclotomic polynomial over F_p of degree o_r(p), the standard fact of Lidl and Niederreiter cited as [LN] - is part of the mission's proposed work toward the goal.

  7. The "is in P" claim is anchored by an explicit work measure, with the bit-cost correspondence in prose. Milestone 7 bounds aksWork by C logUp(n)^15, a generous integer form of Theorem 5.1's O~(log^(21/2) n) - the generous exponent absorbs the schoolbook charging model and the logUp slack. The correspondence between arithmetic-work measures and Turing-machine bit complexity - the standard O~(m) arithmetic on m-bit numbers of the paper's Section 5 - is carried in prose; a machine-level formalization is out of scope.

  8. Pruned content. The paper's Section 5 refinements (Fouvry's Lemma 5.2 and the O~(log^(15/2) n) of Theorem 5.3, and the Lenstra-Pomerance variant), the conjectures (Artin's, the Sophie Germain density, Conjecture 6.1), and the historical survey of Section 1 are out of scope; the mission carries the unconditional Section 5 analysis only, in generous integer form, and the correctness theorem (Theorem 4.1) as the goal.

  9. Due diligence. Before creating the proposal, the creation script searches the platform for prior definitions and theorems matching the paper's ingredients; the search results are recorded in the repository's results directory for the reviewer.

  10. Definition names and module stems. The two definition bundles are published under names equal to their module stems (AKS_poly, AKS_alg), so that the platform imports Definitions.Def_AKS_* in the theorem preambles resolve, in dependency order poly, then alg (which imports poly).

3. Formalization targets

The mission has ten items: two reference definitions and eight theorem drafts, in the following order.

Reference definitions (the formalization fragment):

  • AKS_poly: the polynomial layer. Congruence (1) as the equality (X + a)^n = X^n + a in Z_n[X]; congruence (2) as divisibility by X^r - 1 in Z_n[X]; Definition 4.4's introspection relation over F_p[X]; and the set P of products of the generators X, X+1, ..., X+ell.
  • AKS_alg: the algorithm layer. The integer logarithm logUp; the multiplicative order ordR; the lcm of the first numbers; the perfect-power predicate; the six-step decision function aksDecide with its search smallestR and loop bound ell; the set I and the residue group G; and the work measure aksWork.

Theorem drafts (milestones in attack order, then the goal):

  1. AKS.poly_fermat: Lemma 2.1 - for n at least 2 and a coprime to n, n is prime if and only if (X + a)^n = X^n + a in Z_n[X] (Section 2).
  2. AKS.lcm_lower: Lemma 3.1 - the lcm of the first m numbers is at least 2^m for m at least 7 (Section 3).
  3. AKS.r_exists: Lemma 4.3 - for n > 1 there is an r with 1 < r at most max 3 (logUp n)^5 and ordR r n > logUp(n)^2 (Section 4).
  4. AKS.introspective_closure: Lemmas 4.5-4.6 - introspective numbers are closed under products, and introspectivity is closed under products of polynomials (Section 4).
  5. AKS.group_inj: Lemma 4.7 (Hendrik Lenstra Jr.) - two distinct polynomials of P, both of degree less than t, map to distinct elements of F = F_p[X]/(h), under the primitivity and introspectivity hypotheses, with t at most the size of the residue group G (Section 4).
  6. AKS.group_upper: Lemma 4.8 (Kalai-Sahai-Sudan) - unless n is a power of p, there are m2 < m1 at most n^(floor(sqrt t)), colliding modulo r inside the bounded set I-hat, such that every image of P in F satisfies y^m1 = y^m2 (Section 4).
  7. AKS.poly_time: the work bound - there is a constant C with aksWork n at most C logUp(n)^15 for every n, the generous integer form of Theorem 5.1 (Section 5).
  8. AKS.prime_iff (the goal): Theorem 4.1 - aksDecide n = PRIME if and only if n is prime (Section 4).

Milestones 1 to 7 correspond to the theorem drafts 1 to 7; the goal is draft 8.

4. Significance

The paper is one of the landmark results of computational number theory: a problem open since the 1960s - an unconditional, deterministic, polynomial-time primality test - solved by elementary means, in a proof whose only ingredients are the binomial theorem, Euler's function, and the root bound of a polynomial over a field. The formal account forces exactly what the prose leaves to convention: the precise ring in which each congruence lives, the precise windows in which the searches find their witnesses, the precise generosity of each integer rounding, and the precise content of the two group bounds. The paper's difficulty lies not in any single deep theorem but in the assembly of many small lemmas under one bound chain; a formalization makes each link explicit and checkable, and the mission's readback discipline gives an independent restatement check of every statement before review.

5. Difficulty

Milestone 1 is a commutation: the forward direction is the freshman's dream in Z_p[X] plus Fermat's little theorem for the base; the backward direction isolates the coefficient of X^q for a prime q with q^k dividing n exactly and computes its q-adic valuation below k. Milestone 2 is Nair's argument: the product of the primes in (m/2, m] divides the lcm. Milestone 3 is the counting argument: every bad r divides a single product below the lcm of the window, so some r in the window escapes. Milestone 4 is two ring commutations: f^(m m') = f(X^(m m')) along f(X^m)^(m') = f(X^(m m')), and the product rule for introspectivity. Milestone 5 is Lenstra's argument: from a collision in F and introspection, f(Y) - g(Y) acquires the t distinct primitive r-th roots indexed by G, exceeding its degree. Milestone 6 is the pigeonhole of I-hat against G, the non-power distinctness, and the collision equation transported by introspection. Milestone 7 is arithmetic over the windows. The goal assembles: Lemma 4.2's direction is the congruences for primes; the step-4 case is the factor below the square root; and the step-6 case is the chain of Lemma 4.9 - the injectivity lower bound, the collision upper bound, and the integer bookkeeping that the generous encodings close with slack.

6. Scope

Included: the two congruences and the introspection relation; the set P and the set I with the residue group G; the six-step algorithm; and the eight statements - the Fermat characterization, the lcm bound, the small-r existence, the two closure lemmas, the two group bounds, the work bound, and the correctness theorem.

Excluded, as disclosed in items 7 and 8 of section 2: the machine-level bit-cost formalization of "is in P" (carried in prose, anchored by the explicit aksWork measure); the Section 5 refinements (Fouvry's Lemma 5.2, the O~(log^(15/2) n) of Theorem 5.3, the Lenstra-Pomerance variant of [LP1]); the conjectures of Section 5 and Conjecture 6.1; and the historical survey of Section 1.

7. References

  • Manindra Agrawal, Neeraj Kayal, and Nitin Saxena, "PRIMES is in P", Annals of Mathematics 160 (2004) 781-793. The source document is the uploaded paper (annals-v160-n2-p12.pdf).
  • M. Nair, "On Chebyshev-type inequalities for primes", American Mathematical Monthly 89 (1982) 126-129 (the reference for Lemma 3.1).
  • Rudolf Lidl and Harald Niederreiter, Introduction to Finite Fields and their Applications, Cambridge University Press, 1986 (the reference [LN] for the factorization of the cyclotomic polynomial over F_p).
  • Hendrik W. Lenstra Jr., "Primality testing with cyclotomic rings", unpublished, August 2002 (the source of Lemma 4.7).
  • Adam Kalai, Amit Sahai, and Madhu Sudan, private communication, August 2002 (the source of the proof of Lemma 4.8).
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Metrology·Captain: Lucas

The CODATA 2022 adjustment: least squares, covariance propagation, and the self-consistency of the recommended valuesResearch Paper

Mission: The CODATA 2022 adjustment — least squares, covariance propagation, and the self-consistency of the recommended values

Motivation

Every value of a fundamental constant used in science — the fine-structure constant, the Newtonian constant of gravitation, the Rydberg constant — comes from one place: the least-squares adjustment periodically carried out by the CODATA Task Group on Fundamental Constants. The 2022 adjustment (P. J. Mohr, D. B. Newell, B. N. Taylor and E. Tiesinga, CODATA recommended values of the fundamental physical constants: 2022) takes 133 input data, determines 79 adjusted constants by weighted least squares with 54 degrees of freedom, applies expansion factors 1.7 and 2.5 to the uncertainties of certain groups of data to reduce all normalized residuals to two or less, obtains a final chi-square of 44.2 with Birge ratio 0.90, treats the sixteen values of the Newtonian constant of gravitation separately (16 data, one adjusted constant, 15 degrees of freedom, chi-square 12.9, expansion factor 3.9, Birge ratio 0.93), and obtains the recommended values from the adjusted constants by propagating their uncertainties and covariances.

The mission formalizes the mathematical skeleton of this process in Lean 4 and audits a representative slice of its output by exact rational arithmetic: the equivalence between minimizers of the chi-square statistic and solutions of the normal equations, the weighted mean as the rank-one case (the situation of the separate adjustment of G), the printed degrees of freedom and Birge ratios, the effect of uncertainty expansion on covariances and correlations, the algebraic laws of relative-uncertainty propagation, the exact derived constants determined by the exact defining values of h, e, k and N_A, and the mutual consistency of the printed uncertainties of the alpha family. The goal theorem packages these into the statement that the 2022 adjustment is self-consistent.

What is being formalized is the statistics and the arithmetic of the adjustment, not any physical measurement: the input data enter only through the abstract structure of a weighted least-squares problem, and the numerical audits compare exact rationals with the digit strings printed in the report's tables.

The fragment and its conventions

The source is the 2022 CODATA report in its two identical published versions: J. Phys. Chem. Ref. Data 54, 033105 (2025), doi 10.1063/5.0279860, and Rev. Mod. Phys. 97, 025002 (2025), doi 10.1103/RevModPhys.97.025002. The mission formalizes section XII, "Least-squares adjustment", and the exact and recommended values of Tables XXXII and XXXIII, under the following disclosed conventions.

Twelve conventions deserve disclosure. First, the platform publishes definitions as modules, so the three definition bundles — the least-squares model, the correlations and uncertainty propagation, and the exact rational values — are published as platform definitions (CODATA_lsa, then CODATA_uncert which imports it, and CODATA_values), attached to the proposal as reference items; the theorem drafts import them; and the creation script reads the definition code and the theorem statements directly from the repository modules that the CI has just compiled, so the code posted to the platform is byte-identical to the code whose compilation the CI verified. Second, the two uploaded PDFs are the same paper in its two published versions; citations reference both, and the table numbering follows the Rev. Mod. Phys. version (Tables XXXII-XXXIII, section XII). Third, the observational equations are taken in linear form; the report's observational equations are linear in the adjusted constants to begin with, but the values of the input data, the design matrix entries and the offset vector are interface data, not formalized: the theorems quantify over all weighted least-squares problems of the recorded dimensions. Fourth, the chi-square distribution and the printed probability values (83 percent for the main adjustment, 61 percent for G) are statistical statements about the chi-square distribution; they are printed data of the report and are not constructed, and no probability theory enters the mission. Fifth, the Newtonian constant of gravitation is treated separately, exactly as in the report: a second least-squares structure with sixteen input data and one adjusted constant, its own expansion factor 3.9, and its own Birge ratio; the goal theorem relates the two adjustments only through their common formalism. Sixth, the expansion factors 1.7 and 2.5 of the main adjustment are recorded in the description but not formalized, because the data they modify are interface data; the expansion factor 3.9 of the G adjustment is formalized through the covariance expansion law applied to the abstract covariance matrix of the sixteen values. Seventh, matrix inversion is expressed by two-sided inverse predicates, written entry by entry against the Kronecker delta, rather than through an inverse operator; this keeps the statements elementary and avoids any dependence on matrix inverse lemmas. Eighth, all arithmetic is rational or real: the exact constants are rationals, the derived quantities K_J, R_K, Phi_0, G_0, G_0⁻¹, F, R and the electronvolt are exact rationals, and the printed digit strings are captured by rational rounding intervals; exact quantities carrying a factor of pi (hbar, the Stefan-Boltzmann constant) and quantities with experimental uncertainty outside the audited family (the dalton, the Newtonian constant itself) are excluded because they are not rational. Ninth, the Birge ratios are captured by the rounding intervals [0.895, 0.905) and [0.925, 0.935), which the printed two-digit values 0.90 and 0.93 determine; the true values are sqrt(44.2/54) and sqrt(12.9/15). Tenth, the alpha family audit is an existential: the printed two-significant-digit uncertainties of alpha, 1/alpha, mu_0, eps_0 and Z_0 are jointly reproduced by a single rational relative-uncertainty witness of order 1.6 × 10⁻¹⁰, supplied explicitly by the prover (for example 156/10¹²); this witnesses consistency without asserting the (irrational, distribution-laden) exact relative uncertainty of alpha. Eleventh, the read-backs attached to the theorem drafts were authored by the same model that produced the statements (readback_model glm-5-latest-short); they are a self-check, not an independent audit, and human review of every item is required before submission. Twelfth, everything is developed against the platform's Mathlib build (0df444a); the compilation check of every item is the repository CI, which builds all definitions and theorem drafts with the same Mathlib version (no local Lean toolchain is available to the drafting agent, and this is disclosed).

Formalization targets

Eleven items: three published definition bundles attached as references, seven milestone theorem drafts, and the goal theorem.

  • The least-squares model of the adjustment (reference): the LSQ structure with data, uncertainties, correlations, design matrix, offsets and the weight matrix as a two-sided inverse of the covariance matrix; residuals, the chi-square statistic, the normal equations, the minimization property, the normal matrix and its two-sided inverses, strict positive definiteness, the covariance matrix, the degrees of freedom N - M, and the Birge ratio sqrt(chi²/nu) (section XII).
  • Correlations and uncertainty propagation (reference): the correlation coefficient of a covariance matrix, the expansion of a covariance matrix by per-entry factors, and the relative-variance functional of the propagation law (section XII).
  • The exact rational values (reference): c, h, e, k and N_A exactly as fixed by the SI revision, the derived exact quantities 2e/h, h/e², h/2e, 2e²/h, h/2e², N_A e, N_A k, the electronvolt and h/e, and the 2022 rational values of alpha, 1/alpha, mu_0, eps_0 and Z_0 (Tables XXXII-XXXIII).
  • The normal equations characterize the minimizers, and the solution is unique at full column rank — milestone.
  • The single adjusted constant is the weighted mean with variance the inverse of the total weight, uniquely determined — milestone.
  • The printed degrees of freedom and Birge ratios: 133 - 79 = 54, 16 - 1 = 15, and the rounding intervals of sqrt(44.2/54) and sqrt(12.9/15) — milestone.
  • Expansion of uncertainties: a common factor squares the covariances and preserves every correlation; equal factors on the two members of a pair suffice — with the expansion factor 3.9 of the G adjustment as the instance — milestone.
  • The laws of propagation of relative uncertainty: unit self-correlations, single-component variances, quadratic scaling, and addition of variances for uncorrelated inputs — milestone.
  • The exact derived constants agree with the printed digit strings of Table XXXIII: K_J, R_K, Phi_0, G_0, G_0⁻¹, F, R, the electronvolt and h in eV Hz⁻¹ — milestone.
  • A single rational relative-uncertainty witness reproduces the printed uncertainties of the whole alpha family — milestone.
  • The 2022 adjustment is self-consistent: the goal, packaging the degrees of freedom, the two minimizations, the two Birge ratios, the correlation preservation under the expansion factor 3.9, the alpha-family witness, and the derived-value audit — the goal.

Significance

The CODATA adjustment is the mechanism by which the values of the fundamental constants become internationally accepted, self-consistent numbers; every precision measurement and every physical theory that quotes a constant inherits from it. The mission makes the three layers of the mechanism checkable by a proof assistant: the statistics (the least-squares theorem that the adjustment procedure is, by construction, the unique minimum of the chi-square statistic), the data hygiene (the effect of uncertainty expansion on covariances and correlations, and the propagation laws by which the recommended values and their uncertainties are derived), and the arithmetic (an exact rational audit confirming that the printed digit strings of the derived constants and the printed Birge statistics are consistent with the exact defining values and the reported chi-squares). Because the 2019 SI revision fixed h, e, k and N_A exactly, a growing family of derived constants is a pure rational computation; the mission verifies a representative slice of that family to the printed precision.

Difficulty

The milestones are honest and of mixed difficulty. The normal-equations milestone is the mathematical heart: the chi-square statistic is a quadratic form in the adjusted constants, strict positive definiteness of the weight matrix makes it convex, and the equivalence with the normal equations plus uniqueness at full column rank is a complete weighted least-squares existence-uniqueness argument, carried out entry by entry without matrix inverse lemmas. The weighted-mean milestone is a direct computation in the rank-one case, complicated only by the bookkeeping of the two-sided inverse predicate for the one-by-one normal matrix. The Birge milestone is real arithmetic: two subtractions and two square-root bounds, each reducible to exact rational comparisons by squaring. The expansion and propagation milestones are algebra over the reals: square roots of products of positive reals and the cancellation of equal factors; their difficulty is bookkeeping, not ideas. The derived-values and alpha-family milestones are exact rational computations with numerators and denominators up to thirty digits; they are fully decidable, and their difficulty is the size of the arithmetic — the prover must exhibit the witness ur and verify fifteen rational interval inclusions — for which norm_num-style automation is intended. The goal assembles the parts. Nothing in the mission requires mathematics beyond convexity of a quadratic form and exact rational arithmetic, and this is the point: the CODATA adjustment, the most authoritative computation in metrology, is at its core an auditable exact computation.

Formalization scope

Every theorem quantifies only over abstract least-squares structures and rational values; no measurement, no physical theory, and no probability distribution enters. The fragment excludes: the 133 input data as concrete vectors and the 79 adjusted constants as concrete quantities; the chi-square distribution and all probability statements; the least-squares fitting of the theoretical expressions (atomic transition frequencies, muonic Lamb shifts, magnetic-moment anomalies); the 2022-versus-2018 value comparisons and the historical narrative; the mises en pratique and the experimental methods; the electroweak and particle-physics input data; the quantities whose exact values involve pi (hbar, the Stefan-Boltzmann constant) or whose values carry experimental uncertainty outside the audited family; and the correlations among the input data as concrete numbers. What is formalized is the statistical skeleton, the covariance algebra, and the exact rational audit of the printed output.

Selected references

  • P. J. Mohr, D. B. Newell, B. N. Taylor and E. Tiesinga, CODATA recommended values of the fundamental physical constants: 2022, J. Phys. Chem. Ref. Data 54, 033105 (2025), doi 10.1063/5.0279860; Rev. Mod. Phys. 97, 025002 (2025), doi 10.1103/RevModPhys.97.025002 — the mission's source (uploaded by the proposer in both versions): section XII and Tables XXXII-XXXIII.
  • Resolution 1 of the 26th CGPM (2018) — the exact defining values of h, e, k and N_A on which the derived-value audit rests.
  • B. N. Taylor and C. E. Kuyatt, Guidelines for evaluating and expressing the uncertainty of NIST measurement results (1994), and the Guide to the Expression of Uncertainty in Measurement (JCGM 100) — the law of propagation of uncertainty that the propagation milestones formalize.
  • R. T. Birge (1932) and the subsequent least-squares tradition of the constants — the Birge ratio R_B = sqrt(chi²/nu) and the normalized-residual criterion that the expansion factors implement.
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Category TheoryFunctional AnalysisTopology·Captain: mikedeng1

Gelfand-type duality for commutative von Neumann algebras: The Opposite Category of Commutative von Neumann Algebras Is Equivalent to Measurable Locales, Hyperstonean Locales and Spaces, and CSLEMSResearch Paper

Motivation

Gelfand duality identifies compact Hausdorff spaces with commutative unital C*-algebras: a space XXX corresponds to the algebra C(X)C(X)C(X) of continuous complex functions, and continuous maps correspond contravariantly to unital *-homomorphisms (Gelfand 1941; in categorical form, Negrepontis 1971). Measure theory has an analogous expectation. A measurable space with a σ-ideal of negligible sets yields the commutative von Neumann algebra L∞L^\inftyL∞ of bounded measurable functions modulo equality almost everywhere, and every commutative von Neumann algebra should arise in this way. Making that expectation precise as an equivalence of categories requires deciding which measurable spaces to allow and which maps between them to identify.

Timeline. Stone (1936–1937) established the duality between Boolean algebras and Stone spaces, and between complete Boolean algebras and extremally disconnected ones. Segal (1951) introduced localizable measure spaces. Dixmier (1951) characterized the Gelfand spectra of commutative von Neumann algebras as the hyperstonean spaces. Loomis (1947) and Sikorski (1948) represented σ-complete Boolean algebras as measurable sets modulo meager sets on their Stone spaces. Von Neumann (1932), Maharam (1958), Ionescu Tulcea (1965), Vesterstrøm–Wils (1969), Edgar (1976) and Graf (1980) gave criteria for lifting homomorphisms of measure algebras to point maps. Pavlov (arXiv:2005.05284, J. Pure Appl. Algebra) assembled these ingredients into one equivalence of categories. That equivalence is the subject of this mission.

Setting

An enhanced measurable space (X,M,N)(X,M,N)(X,M,N) is a set XXX, a σ-algebra MMM of subsets of XXX, and a σ-ideal N⊆MN\subseteq MN⊆M of the power set 2X2^X2X, the negligible sets. A premap f ⁣:(X,M,N)→(X′,M′,N′)f\colon(X,M,N)\to(X',M',N')f:(X,M,N)→(X′,M′,N′) is a map defined on a conegligible subset of XXX with f∗M′⊆Mf^*M'\subseteq Mf∗M′⊆M and f∗N′⊆Nf^*N'\subseteq Nf∗N′⊆N. Two premaps are weakly equal almost everywhere, f≈gf\approx gf≈g, when f∗m⊕g∗m∈Nf^*m\oplus g^*m\in Nf∗m⊕g∗m∈N for every m∈M′m\in M'm∈M′. The space is compact if some compact class K⊆MK\subseteq MK⊆M (a family with the finite intersection property for all subfamilies) has a non-negligible member inside every non-negligible measurable set. It is strictly localizable if it is isomorphic, through premaps, to a coproduct of a small family of spaces carrying faithful finite measures. CSLEMS is the category of compact strictly localizable spaces with ≈\approx≈-classes of premaps.

A frame is a complete lattice in which finite meets distribute over arbitrary joins; the category of locales is the opposite of the category of frames. A complete Boolean algebra is localizable if 111 is the supremum of the elements aaa for which aAaAaA carries a finite faithful continuous valuation. MLoc, the category of measurable locales, is the full subcategory of locales on the localizable Boolean algebras. A hyperstonean locale is a Stonean locale (coherent, regular, ¬x∨¬¬x=1\neg x\vee\neg\neg x=1¬x∨¬¬x=1) in which every nonzero open has a positive normal valuation not vanishing on it. A hyperstonean space is a sober space whose locale of opens is hyperstonean. HStoneanLoc and HStonean take open maps as morphisms. CVNA is the category of commutative von Neumann algebras (C*-algebras with a predual) and normal unital *-homomorphisms.

Formalization targets

Goal: Theorem 1.1

HStonean≃HStoneanLoc,HStoneanLoc≃MLoc,CSLEMS≃MLoc,MLoc≃CVNAop.\mathsf{HStonean}\simeq\mathsf{HStoneanLoc},\qquad \mathsf{HStoneanLoc}\simeq\mathsf{MLoc},\qquad \mathsf{CSLEMS}\simeq\mathsf{MLoc},\qquad \mathsf{MLoc}\simeq\mathsf{CVNA}^{\mathrm{op}}.HStonean≃HStoneanLoc,HStoneanLoc≃MLoc,CSLEMS≃MLoc,MLoc≃CVNAop.

The goal is the existence of the four equivalences. It does not fix the functors.

The four equivalences with their functors

  • Proposition 2.72: the equivalence HStonean≃HStoneanLoc\mathsf{HStonean}\simeq\mathsf{HStoneanLoc}HStonean≃HStoneanLoc is implemented by the locale of opens Ω\OmegaΩ.
  • Proposition 2.73: the equivalence HStoneanLoc≃MLoc\mathsf{HStoneanLoc}\simeq\mathsf{MLoc}HStoneanLoc≃MLoc is implemented by the compact opens COpen\mathrm{COpen}COpen.
  • Theorem 3.20: the equivalence MLoc≃CVNAop\mathsf{MLoc}\simeq\mathsf{CVNA}^{\mathrm{op}}MLoc≃CVNAop has inverse ProjLoc\mathsf{ProjLoc}ProjLoc, given by projections and restriction.
  • Theorem 5.19: the equivalence CSLEMS≃MLoc\mathsf{CSLEMS}\simeq\mathsf{MLoc}CSLEMS≃MLoc is implemented by ML\mathsf{ML}ML, the functor (X,M,N)↦M/N(X,M,N)\mapsto M/N(X,M,N)↦M/N, f↦f∗f\mapsto f^*f↦f∗.

Supporting milestones

The supporting milestones, in proof order:

  • normal valuations versus continuous valuations on compact opens (Lemma 2.58);
  • localizability through valuations (Lemma 2.53);
  • completeness of ProjAlg(A)\mathsf{ProjAlg}(A)ProjAlg(A) (Proposition 3.8);
  • A∗A_*A∗​ as continuous valuations (Proposition 3.9);
  • ProjAlg\mathsf{ProjAlg}ProjAlg as a functor (Lemma 3.11);
  • σ-complete algebras with faithful valuations (Lemma 4.55);
  • strict localizability implies localizability (Proposition 4.54);
  • compactness of induced subspaces (Lemma 4.61);
  • measurable images (Proposition 4.65);
  • TM\mathrm{TM}TM on hyperstonean spaces (Proposition 5.4);
  • ML\mathsf{ML}ML on morphisms (Lemma 5.11);
  • the isomorphism (X,M,N)≅Spec(ML(X,M,N))(X,M,N)\cong\mathrm{Spec}(\mathsf{ML}(X,M,N))(X,M,N)≅Spec(ML(X,M,N)) (Proposition 5.16).

Significance

The result. Theorem 1.1 replaces commutative von Neumann algebras, a class of operator algebras, by measurable locales, which are pointless spaces. It also gives a point-set model, CSLEMS, in which morphisms are measurable maps modulo a null relation. With it, constructions on commutative von Neumann algebras can be carried out measure-theoretically and transported back: products, pushforwards of measures, and the identification of the predual with valuations. It also explains why the obvious choices fail. With localizable instead of strictly localizable spaces, with equality almost everywhere instead of weak equality, or without compactness, the measure-theoretic category is not dual to CVNA (Remarks 4.23 and 5.18).

Formalization. The theorem is proved in the paper. None of the five categories, and none of the equivalences, has a machine-checked form in Mathlib or on the platform. Mathlib has W*-algebras (WStarAlgebra), locales, Stonean spaces and Baire-measurable sets, but no normal homomorphisms, measure algebras or lifting theorems. The published module QAlgorithms_Papers_Independent_Support21_P20 formalizes this paper's valuations, enhanced measurable spaces and premaps, and poses several lemmas, three of which are milestones here. Completing the mission means formalizing Stone and Stonean duality for locales, the spectral theory of commutative von Neumann algebras through projections, and the von Neumann–Maharam lifting theorem for strictly localizable spaces.

Difficulty

The equivalences in §2 restrict classical dualities and are mostly bookkeeping once those dualities are available. Even so, Mathlib's Stone duality is not stated for locales with open maps. The central difficulty is Proposition 5.16. An object of CSLEMS must be isomorphic, through point maps, to the Stone spectrum of its own measure algebra. In one direction this needs a lifting M/N→MM/N\to MM/N→M that is a Boolean homomorphism, and that uses strict localizability through the von Neumann–Maharam theorem. In the other direction it needs a point map from the spectrum back to XXX, constructed from the compact class. The natural first idea, choosing representatives class by class, does not give a homomorphism: liftings exist only through a transfinite construction. A second difficulty is Lemma 5.11. A Boolean homomorphism induced by a measurable map preserves countable suprema, but in general it does not preserve arbitrary ones (Remark 5.12). Compactness and the measurable image of Proposition 4.65 are what rule this out.

Formalization scope

All five categories live in one universe, with objects in Type u. The encoding commits to these conventions:

  • CSLEMS. Morphisms are partial premaps (X → Option Y) modulo weak equality almost everywhere. Theorem 1.1's bullet speaks of maps of sets, but with total maps the theorem is false: (pt,2pt,2pt)(\mathrm{pt},2^{\mathrm{pt}},2^{\mathrm{pt}})(pt,2pt,2pt) has no map to ∅\varnothing∅ (Remarks 4.9, 4.15). Strict localizability uses a small index family and isomorphism in PreEMS; the faithful finite measures of its σ-finite pieces are countably additive maps M→CM\to\mathbb CM→C with absolutely convergent sums (Remark 4.29), because Definition 4.28's saturation clause alone would also admit merely finitely additive ones. Compactness quantifies over arbitrary subfamilies, not countable ones.
  • MLoc. The full subcategory of Mathlib's Locale on localizable Boolean algebras.
  • HStoneanLoc and HStonean. Morphisms are open frame maps (Definition 2.15) and open continuous maps. Hyperstonean spaces are sober spaces whose frame of opens is hyperstonean.
  • CVNA. Commutative CStarAlgebras with WStarAlgebra. Normality is stated as "pulls normal functionals back to normal functionals", which is equivalent to Definition 3.3 by Sakai's uniqueness of the predual.
  • No nontriviality. The empty space, the one-element Boolean algebra and the zero algebra are allowed.

The equivalence milestones assert an equivalence together with a description of its functor. They never take a functor as a hypothesis, so none of the statements reduces to rfl or to an instance argument.

Reusable parts:

  • the CSLEMS category, with the category laws of Propositions 4.7 and 4.14 proved inline;
  • the quotient M/NM/NM/N and the pull-back;
  • TM\mathrm{TM}TM and the Stone spectrum;
  • the projection Boolean algebra.

Contributions are welcome at every level: proofs of the milestones, Stone and Stonean duality for locales, and a lifting theorem.

Selected references

  • D. Pavlov, Gelfand-type duality for commutative von Neumann algebras, J. Pure Appl. Algebra 226 (2022); arXiv:2005.05284v3. https://arxiv.org/abs/2005.05284
  • J. Dixmier, Sur certains espaces considérés par M. H. Stone, Summa Brasil. Math. 2 (1951), 151–182.
  • M. H. Stone, Algebraic characterizations of special Boolean rings, Fund. Math. 29 (1937), 223–303. https://eudml.org/doc/212943
  • I. E. Segal, Equivalences of measure spaces, Amer. J. Math. 73 (1951), 275–313. https://doi.org/10.2307/2372178
  • D. Maharam, On a theorem of von Neumann, Proc. Amer. Math. Soc. 9 (1958), 987–994. https://doi.org/10.1090/S0002-9939-1958-0105479-6
  • D. H. Fremlin, Measure Theory, Vol. 3 (Measure algebras), Torres Fremlin, 2002.
  • P. T. Johnstone, Stone Spaces, Cambridge University Press, 1982.
  • S. Sakai, C*-algebras and W*-algebras, Springer, 1971.
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ProbabilityQuantum InformationRandom Matrix Theory·Captain: mikedeng1

Asymptotics of random density matrices: The Rescaled Empirical Spectral Measure of an Induced Random Density Matrix Converges Almost Surely to the Marchenko–Pastur LawResearch Paper

Motivation

In quantum mechanics, a system that interacts with an environment is described by a density matrix: a positive semidefinite complex matrix of trace one. When nothing is known about the joint state of the system and its environment, a natural model is to take that joint state to be a uniformly random pure state and to trace out the environment. The resulting law on density matrices, the induced measure of Życzkowski and Sommers (Życzkowski–Sommers 2001), is a standard model of a "typical" mixed state. It is used in quantum information to study the typical entanglement of bipartite pure states, as in Page's conjecture on average entropy (Page 1993).

Nechita (arXiv:quant-ph/0702154v3, Ann. Henri Poincaré 2007) studies the asymptotics of this ensemble. In the regime where the system dimension nnn and the environment dimension k(n)k(n)k(n) grow proportionally, the spectrum of the random density matrix, magnified by cncncn, has the same almost sure limit as the spectrum of a Wishart matrix: the Marchenko–Pastur law (Marchenko–Pastur 1967). The mission formalizes this result (Theorem 5) together with the chain of statements the paper uses to derive it.

Setting

Throughout, NC(0,1)\mathcal N_{\mathbb C}(0,1)NC​(0,1) denotes the law of Z=X+iYZ = X + iYZ=X+iY where X,YX, YX,Y are independent real Gaussians of mean 000 and variance 1/21/21/2, so that E∣Z∣2=1\mathbb E|Z|^2 = 1E∣Z∣2=1.

  • Wishart matrix. If XXX is an n×kn \times kn×k complex matrix with i.i.d. NC(0,1)\mathcal N_{\mathbb C}(0,1)NC​(0,1) entries, W=XX∗W = XX^*W=XX∗ is a Wishart matrix of parameters nnn and kkk.
  • Pure states. A pure state of Cm\mathbb C^mCm is a ray ∣ψ⟩|\psi\rangle∣ψ⟩: a nonzero vector up to a nonzero scalar factor. Its pure density matrix is ∣ψ⟩⟨ψ∣=ψψ∗/∥ψ∥2|\psi\rangle\langle\psi| = \psi\psi^*/\|\psi\|^2∣ψ⟩⟨ψ∣=ψψ∗/∥ψ∥2, a rank-one orthogonal projection. The set EmE_mEm​ of pure states carries a unique probability measure νm\nu_mνm​ invariant under all unitaries U∈U(m)U \in U(m)U∈U(m).
  • Induced measure. Let H=Cn\mathcal H = \mathbb C^nH=Cn (the system) and K=Ck\mathcal K = \mathbb C^kK=Ck (the environment). If ∣ψ⟩|\psi\rangle∣ψ⟩ has law νnk\nu_{nk}νnk​ on the pure states of H⊗K\mathcal H\otimes\mathcal KH⊗K, the law of
ρ=Tr⁡K ∣ψ⟩⟨ψ∣\rho = \operatorname{Tr}_{\mathcal K}\,|\psi\rangle\langle\psi|ρ=TrK​∣ψ⟩⟨ψ∣

is the induced measure μn,k\mu_{n,k}μn,k​ on n×nn\times nn×n density matrices. Here Tr⁡K\operatorname{Tr}_{\mathcal K}TrK​ is the partial trace over the environment.

  • Empirical spectral measure. For an n×nn \times nn×n matrix AAA with eigenvalues λ1(A),…,λn(A)\lambda_1(A), \dots, \lambda_n(A)λ1​(A),…,λn​(A) (counted with multiplicity) and a scale sss, put Ls(A)=1n∑iδsλi(A)L^s(A) = \frac1n\sum_i \delta_{s\lambda_i(A)}Ls(A)=n1​∑i​δsλi​(A)​.
  • Marchenko–Pastur law. For c>0c > 0c>0, with a=(c−1)2a = (\sqrt c-1)^2a=(c​−1)2 and b=(c+1)2b = (\sqrt c+1)^2b=(c​+1)2,
μc=max⁡{1−c,0} δ0+(x−a)(b−x)2πx 1[a,b](x) dx.\mu_c = \max\{1-c,0\}\,\delta_0 + \frac{\sqrt{(x-a)(b-x)}}{2\pi x}\,\mathbf 1_{[a,b]}(x)\,dx .μc​=max{1−c,0}δ0​+2πx(x−a)(b−x)​​1[a,b]​(x)dx.

Formalization targets

Goal: Theorem 5 (p. 14)

Let c∈(0,∞)c \in (0,\infty)c∈(0,∞), let k(n)k(n)k(n) be integers with k(n)/n→ck(n)/n \to ck(n)/n→c, and let ρn\rho_nρn​ have law μn,k(n)\mu_{n,k(n)}μn,k(n)​ for every nnn. Then, almost surely,

Ln=1n∑i=1nδc n λi(ρn)  ⟹  μcweakly.L_n = \frac1n\sum_{i=1}^n \delta_{c\,n\,\lambda_i(\rho_n)} \;\Longrightarrow\; \mu_c \quad \text{weakly}.Ln​=n1​i=1∑n​δcnλi​(ρn​)​⟹μc​weakly.

Milestones, in the order the proof uses them

  1. Proposition 1 (p. 4): νn\nu_nνn​ exists and is unique.
  2. Proposition 2, item 1 (p. 4): the class of a vector with law NCn(0,In)\mathcal N^n_{\mathbb C}(0,I_n)NCn​(0,In​) has law νn\nu_nνn​.
  3. Eq. (12) (p. 6): if the coordinates ψij\psi_{ij}ψij​ are arranged in an n×kn \times kn×k matrix XXX, then Tr⁡K∣ψ⟩⟨ψ∣=XX∗/Tr⁡(XX∗)\operatorname{Tr}_{\mathcal K}|\psi\rangle\langle\psi| = XX^*/\operatorname{Tr}(XX^*)TrK​∣ψ⟩⟨ψ∣=XX∗/Tr(XX∗).
  4. Lemma 1 (p. 6): if XXX has i.i.d. NC(0,1)\mathcal N_{\mathbb C}(0,1)NC​(0,1) entries, then XX∗/Tr⁡(XX∗)XX^*/\operatorname{Tr}(XX^*)XX∗/Tr(XX∗) has law μn,k\mu_{n,k}μn,k​.
  5. Eq. (24) (p. 9): the eigenvalues of W/Tr⁡WW/\operatorname{Tr} WW/TrW are λi/∑jλj\lambda_i/\sum_j\lambda_jλi​/∑j​λj​.
  6. Theorem 2 (p. 8, quoted from Haagerup–Thorbjørnsen): almost surely, 1n∑iδn−1λi(Wn)⇒μc\frac1n\sum_i\delta_{n^{-1}\lambda_i(W_n)} \Rightarrow \mu_cn1​∑i​δn−1λi​(Wn​)​⇒μc​ for Wishart matrices WnW_nWn​ of parameters nnn and k(n)k(n)k(n).
  7. Lemma 2, (45) (p. 13): Tr⁡Wn/(n k(n))→1\operatorname{Tr} W_n/(n\,k(n)) \to 1TrWn​/(nk(n))→1 almost surely.
  8. The perturbation step (p. 14, eqs. (51)–(53)): dilating the atoms of a weakly convergent sequence by factors tn→1t_n \to 1tn​→1 does not change a compactly supported weak limit.

Significance

The result. Theorem 5 says that the reduced state of a large random bipartite pure state has a deterministic spectral profile at scale 1/(cn)1/(cn)1/(cn). When c<1c < 1c<1, the environment is smaller than the system, and an atom of mass 1−c1-c1−c at 000 records that ρn\rho_nρn​ has rank k(n)<nk(n) < nk(n)<n. When c≥1c \ge 1c≥1, the spectrum fills the interval [a,b][a, b][a,b]. The result transfers the classical Wishart limit to the induced measure, and with it quantitative information on the typical entanglement spectrum of bipartite pure states.

Formalizing it. The theorem is proved on paper, and none of it is machine-checked. The mission produces the induced-measure layer in Lean: complex Gaussian matrices, the invariant law on pure states, the partial-trace construction of μn,k\mu_{n,k}μn,k​, and the Marchenko–Pastur law with its atom. Lemma 1 and eq. (12) connect these objects to Wishart matrices. The step that needs the most new library is Theorem 2, the Marchenko–Pastur theorem itself, which the paper quotes without proof. The perturbation step is posed as a statement about weak convergence. The paper argues it through convergence of moments, and in that argument weak convergence of LnWL_n^WLnW​ is used as if it gave convergence of moments. The statement posed here is true as stated and needs no moment control.

Difficulty

The reduction from Theorem 5 to Theorem 2 is short on paper. The work lies elsewhere.

  • Theorem 2 is a full random-matrix limit theorem. It needs a method that identifies the limit (moments, Stieltjes transforms, or free probability) and concentration strong enough to give almost sure convergence with no coupling between different nnn.
  • Proposition 1 needs the invariant measure on complex projective space and a uniqueness argument for it. Mathlib's Haar-measure uniqueness is stated for groups, not for homogeneous spaces of U(n)U(n)U(n).
  • Lemma 1 needs the unitary invariance of the complex Gaussian vector NCnk(0,I)\mathcal N^{nk}_{\mathbb C}(0,I)NCnk​(0,I) and the image of a law under partial trace.

The naive route of "taking moments" in the perturbation step fails: weak convergence does not give convergence of moments, so (52)–(53) cannot be compared without extra tightness or moment bounds.

Formalization scope

  • Pure states. Rays of Cm\mathbb C^mCm are represented by their rank-one projections (IsPureDensity: Hermitian, idempotent, trace one). A law on EmE_mEm​ is a probability measure on m×mm\times mm×m complex matrices carried by that set. Unitary invariance is invariance under ρ↦UρU∗\rho \mapsto U\rho U^*ρ↦UρU∗ (IsPureStateLaw).
  • Induced law. "ρ\rhoρ has law μn,k\mu_{n,k}μn,k​" is the predicate HasInducedLaw: the law of ρ\rhoρ is the image under the partial trace of some unitarily invariant law on pure states of Cn⊗Ck\mathbb C^n\otimes\mathbb C^kCn⊗Ck. Proposition 1 makes this law unique.
  • Indexing and partial trace. Cn⊗Ck\mathbb C^n\otimes\mathbb C^kCn⊗Ck is indexed by Fin n × Fin k with the environment on the right. The partial trace is the published WildeQIT.partialTraceRight. NC(0,1)\mathcal N_{\mathbb C}(0,1)NC​(0,1) is the published SpikedWishart.SoftEdge.stdComplexGaussian, with variance 1/21/21/2 per real coordinate.
  • Eigenvalues and convergence. Eigenvalues are roots of the characteristic polynomial, counted with multiplicity. Weak convergence is ∫f dLn→∫f dμc\int f\,dL_n \to \int f\,d\mu_c∫fdLn​→∫fdμc​ for all bounded continuous fff, with one null set for all fff.
  • Disclosed conventions. The hypotheses hold for n≥1n \ge 1n≥1 with k(n)≥1k(n)\ge 1k(n)≥1, since there are no pure states in dimension 000. All random matrices live on one probability space, and nothing is assumed about their joint law across different nnn: the paper never couples them, and the almost sure statements hold for every coupling.
  • Trivializations ruled out. Three trivializing formalizations are excluded:
    • stating the law of ρn\rho_nρn​ through the Wishart formula Wn/Tr⁡WnW_n/\operatorname{Tr}W_nWn​/TrWn​, which would make Lemma 1 a hypothesis;
    • dropping the atom of μc\mu_cμc​ or leaving the limit measure free;
    • stating "for each fff, almost surely" in place of one null set for all fff.

Solvers are welcome to contribute in four places:

  • the general measure-theoretic pieces: Gaussian invariance, image laws under partial trace, and the dilation lemma, which are reusable beyond this mission;
  • the deterministic linear algebra of eqs. (12) and (24);
  • Lemma 2 through Borel–Cantelli;
  • any proof of Theorem 2.

Selected references

  • I. Nechita, Asymptotics of random density matrices, Ann. Henri Poincaré 8 (2007); arXiv:quant-ph/0702154v3. https://arxiv.org/abs/quant-ph/0702154v3
  • K. Życzkowski, H.-J. Sommers, Induced measures in the space of mixed quantum states, J. Phys. A 34 (2001) 7111–7125. https://doi.org/10.1088/0305-4470/34/35/335
  • U. Haagerup, S. Thorbjørnsen, Random matrices with complex Gaussian entries, Expo. Math. 21 (2003) 293–335. https://doi.org/10.1016/S0723-0869(03)80036-1
  • V. A. Marchenko, L. A. Pastur, Distribution of eigenvalues for some sets of random matrices, Math. USSR-Sb. 1 (1967) 457–483. https://doi.org/10.1070/SM1967v001n04ABEH001994
  • D. N. Page, Average entropy of a subsystem, Phys. Rev. Lett. 71 (1993) 1291–1294. https://doi.org/10.1103/PhysRevLett.71.1291
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Mathematical PhysicsQuantum InformationQuantum Mechanics·Captain: mikedeng1

Teleportation Stretching for Single-Mode Gaussian Channels: Exact LOCC Simulation of a Pure-Loss Channel from a Finite-Energy Effective Choi StateResearch Paper

Motivation

The ultimate rates of quantum communication over optical fibre — how many secret bits or entangled pairs per channel use a lossy line can carry with unlimited local operations and classical communication (LOCC) — are bounded through a technique called teleportation stretching (Pirandola, Laurenza, Ottaviani, Banchi, arXiv:1510.08863). The idea is that if a channel E\mathcal EE can be simulated by teleporting its input through a fixed resource state ρE\rho_{\mathcal E}ρE​, then any adaptive protocol using E\mathcal EE nnn times can be rewritten as LOCC acting on ρE⊗n\rho_{\mathcal E}^{\otimes n}ρE⊗n​, and every LOCC monotone of ρE\rho_{\mathcal E}ρE​ bounds the protocol's output.

For the pure-loss channel the natural resource is the Choi state I⊗Eη(ΦEPR)\mathcal I\otimes\mathcal E_\eta(\Phi_{\rm EPR})I⊗Eη​(ΦEPR​) of an ideal Einstein–Podolsky–Rosen state, which is not a normalizable state: it is the limit ξ→1\xi\to1ξ→1 of two-mode squeezed states and has infinite energy. R. Namiki (arXiv:1603.05292, 2016) observed that this limit can be avoided for lossy channels. Finite-squeezing teleportation, in the Braunstein–Kimble scheme (Braunstein and Kimble, PRL 80, 869, 1998), does not teleport perfectly, but its imperfection is itself a pure loss. Composing it with a second pure-loss channel therefore reproduces the target channel exactly, with a finite-energy resource.

Setting

A single bosonic mode is described on the Fock space ℓ2(N)\ell^2(\mathbb N)ℓ2(N) with number basis ∣n⟩|n\rangle∣n⟩. Every operator is handled through its number-basis kernel K(m,n)=⟨m∣X∣n⟩K(m,n)=\langle m|X|n\rangleK(m,n)=⟨m∣X∣n⟩; an operator on two modes has kernel K((r,b),(r′,b′))K((r,b),(r',b'))K((r,b),(r′,b′)), the first index labelling the first mode.

  • The displacement D(z)=eza†−zˉaD(z)=e^{za^\dagger-\bar z a}D(z)=eza†−zˉa, z∈Cz\in\mathbb Cz∈C, has explicit matrix entries ⟨m∣D(z)∣n⟩\langle m|D(z)|n\rangle⟨m∣D(z)∣n⟩; conjugation LD(z)(X)=D(z)XD(z)†\mathcal L_{D(z)}(X)=D(z)XD(z)^\daggerLD(z)​(X)=D(z)XD(z)† acts on kernels by matrix products.
  • The pure-loss channel Eη\mathcal E_\etaEη​, η∈(0,1)\eta\in(0,1)η∈(0,1), is the vacuum beam splitter of transmissivity η\etaη: a↦η aa\mapsto\sqrt\eta\,aa↦η​a with vacuum noise. I⊗Eη\mathcal I\otimes\mathcal E_\etaI⊗Eη​ applies it to the second mode.
  • The two-mode squeezed state with parameter ξ∈(0,1)\xi\in(0,1)ξ∈(0,1) is ∣ψξ⟩=1−ξ2∑n≥0ξn∣n⟩∣n⟩|\psi_\xi\rangle=\sqrt{1-\xi^2}\sum_{n\ge0}\xi^n|n\rangle|n\rangle∣ψξ​⟩=1−ξ2​∑n≥0​ξn∣n⟩∣n⟩ on modes (A′,B)(A',B)(A′,B).
  • The CV-Bell states are ∣Φβ⟩=(1⊗D†(β))∣Φ0⟩|\Phi_\beta\rangle=(\mathbb 1\otimes D^\dagger(\beta))|\Phi_0\rangle∣Φβ​⟩=(1⊗D†(β))∣Φ0​⟩ with ∣Φ0⟩=(2π)−1/2∑n∣n⟩∣n⟩|\Phi_0\rangle=(2\pi)^{-1/2}\sum_n|n\rangle|n\rangle∣Φ0​⟩=(2π)−1/2∑n​∣n⟩∣n⟩; they are improper vectors with ∬∣Φβ⟩⟨Φβ∣ dx dp=1\iint|\Phi_\beta\rangle\langle\Phi_\beta|\,dx\,dp=\mathbb 1∬∣Φβ​⟩⟨Φβ​∣dxdp=1, where β=(x+ip)/2\beta=(x+ip)/\sqrt2β=(x+ip)/2​.

Alice holds a two-mode state ρRS\rho_{RS}ρRS​ (SSS the signal, RRR a reference) and Alice and Bob share a resource ωA′B\omega_{A'B}ωA′B​. The unnormalized branch for outcome β\betaβ is the kernel on (R,B)(R,B)(R,B)

⟨Φβ∣SA′(ρ⊗ω)∣Φβ⟩SA′=12π∑n,n′,k,k′⟨n∣D(β)∣k⟩ ρ((⋅,n),(⋅,n′)) ω((k,⋅),(k′,⋅)) ⟨n′∣D(β)∣k′⟩‾.\langle\Phi_\beta|_{SA'}(\rho\otimes\omega)|\Phi_\beta\rangle_{SA'}=\frac1{2\pi}\sum_{n,n',k,k'}\langle n|D(\beta)|k\rangle\,\rho\big((\cdot,n),(\cdot,n')\big)\,\omega\big((k,\cdot),(k',\cdot)\big)\,\overline{\langle n'|D(\beta)|k'\rangle}.⟨Φβ​∣SA′​(ρ⊗ω)∣Φβ​⟩SA′​=2π1​n,n′,k,k′∑​⟨n∣D(β)∣k⟩ρ((⋅,n),(⋅,n′))ω((k,⋅),(k′,⋅))⟨n′∣D(β)∣k′⟩​.

Formalization targets

Goal: the Theorem (26)–(27), corrected protocol

For 0<η<ξ2<10<\eta<\xi^2<10<η<ξ2<1 put η′=η/ξ2\eta'=\eta/\xi^2η′=η/ξ2 and ρE′=I⊗Eη′(ψξ)\rho_{\mathcal E'}=\mathcal I\otimes\mathcal E_{\eta'}(\psi_\xi)ρE′​=I⊗Eη′​(ψξ​), the effective Choi state. For every two-mode density ρAB\rho_{AB}ρAB​,

I⊗Eη(ρAB)=∬R2L1⊗D(η′ξβˉ)(⟨Φβ∣SA′(ρAB⊗ρE′)∣Φβ⟩SA′) dx dp,\mathcal I\otimes\mathcal E_\eta(\rho_{AB})=\iint_{\mathbb R^2}\mathcal L_{\mathbb 1\otimes D(\sqrt{\eta'}\xi\bar\beta)}\Big(\langle\Phi_\beta|_{SA'}(\rho_{AB}\otimes\rho_{\mathcal E'})|\Phi_\beta\rangle_{SA'}\Big)\,dx\,dp ,I⊗Eη​(ρAB​)=∬R2​L1⊗D(η′​ξβˉ​)​(⟨Φβ​∣SA′​(ρAB​⊗ρE′​)∣Φβ​⟩SA′​)dxdp,

entry by entry, with every series and integral convergent, and η≤η′<1\eta\le\eta'<1η≤η′<1. The parameters and the protocol are independent of ρAB\rho_{AB}ρAB​.

Milestones

  1. (18) Displacement covariance: Eη(D(β)ρD†(β))=D(ηβ)Eη(ρ)D†(ηβ)\mathcal E_\eta(D(\beta)\rho D^\dagger(\beta))=D(\sqrt\eta\beta)\mathcal E_\eta(\rho)D^\dagger(\sqrt\eta\beta)Eη​(D(β)ρD†(β))=D(η​β)Eη​(ρ)D†(η​β) for every density.
  2. Composition (App. B): Eη∘Eη′=Eηη′\mathcal E_\eta\circ\mathcal E_{\eta'}=\mathcal E_{\eta\eta'}Eη​∘Eη′​=Eηη′​.
  3. (20), coherent input, corrected: ⟨Φβ∣(∣α⟩⟨α∣⊗ψξ)∣Φβ⟩=1−ξ22πe−(1−ξ2)∣α−βˉ∣2∣ξ(α−βˉ)⟩⟨ξ(α−βˉ)∣\langle\Phi_\beta|(|\alpha\rangle\langle\alpha|\otimes\psi_\xi)|\Phi_\beta\rangle=\frac{1-\xi^2}{2\pi}e^{-(1-\xi^2)|\alpha-\bar\beta|^2}|\xi(\alpha-\bar\beta)\rangle\langle\xi(\alpha-\bar\beta)|⟨Φβ​∣(∣α⟩⟨α∣⊗ψξ​)∣Φβ​⟩=2π1−ξ2​e−(1−ξ2)∣α−βˉ​∣2∣ξ(α−βˉ​)⟩⟨ξ(α−βˉ​)∣.
  4. (22), coherent input: the weights 1−ξ22πe−(1−ξ2)∣α−βˉ∣2\frac{1-\xi^2}{2\pi}e^{-(1-\xi^2)|\alpha-\bar\beta|^2}2π1−ξ2​e−(1−ξ2)∣α−βˉ​∣2 integrate to 111 over dx dpdx\,dpdxdp.
  5. (23), coherent input, corrected: after Eη\mathcal E_\etaEη​ the branch of milestone 3 becomes the same weight times ∣ηξ(α−βˉ)⟩⟨ηξ(α−βˉ)∣|\sqrt\eta\xi(\alpha-\bar\beta)\rangle\langle\sqrt\eta\xi(\alpha-\bar\beta)|∣η​ξ(α−βˉ​)⟩⟨η​ξ(α−βˉ​)∣.
  6. (24), every density, corrected: ∬D(ηξβˉ) Eη(Tβ,ξρTβ,ξ†) D†(ηξβˉ) dx dp=Eηξ2(ρ)\iint D(\sqrt\eta\xi\bar\beta)\,\mathcal E_\eta(T_{\beta,\xi}\rho T_{\beta,\xi}^\dagger)\,D^\dagger(\sqrt\eta\xi\bar\beta)\,dx\,dp=\mathcal E_{\eta\xi^2}(\rho)∬D(η​ξβˉ​)Eη​(Tβ,ξ​ρTβ,ξ†​)D†(η​ξβˉ​)dxdp=Eηξ2​(ρ).

Significance

The result. The Theorem shows that one use of a pure-loss channel, on any input including half of an entangled state, is reproduced exactly by LOCC on the finite-energy state I⊗Eη′(ψξ)\mathcal I\otimes\mathcal E_{\eta'}(\psi_\xi)I⊗Eη′​(ψξ​). In the paper's §II.C this is the step that would let entanglement-measure bounds for nnn adaptive channel uses be evaluated on a genuine density operator, without the limit ξ→1\xi\to1ξ→1 that the ideal-EPR argument needs. The relation (24) also makes precise in which sense the realistic teleportation family {Tβ,ξ}\{T_{\beta,\xi}\}{Tβ,ξ​} is not teleportation-stretching in the finite-dimensional sense, yet simulates the channel after an outcome-dependent displacement.

Formalizing it. The result is proved in the paper by a short computation through the Glauber–Sudarshan PPP representation, which is heuristic for nonclassical inputs. No machine-checked version exists. A formal proof requires an argument valid for every density operator, together with all convergence statements. The formalization also records a sign slip: with the paper's own definitions (4), (16), (A4) and D(β)=eβa†−β∗aD(\beta)=e^{\beta a^\dagger-\beta^*a}D(β)=eβa†−β∗a, the step ⟨α∗∣D(β)=⟨α∗+β∗∣\langle\alpha^*|D(\beta)=\langle\alpha^*+\beta^*|⟨α∗∣D(β)=⟨α∗+β∗∣ in (20) should read ⟨α∗−β∣\langle\alpha^*-\beta|⟨α∗−β∣. Consequently (20) and (23) hold with α−βˉ\alpha-\bar\betaα−βˉ​ in place of α+β\alpha+\betaα+β, and the correction in (24) is D(ηξβˉ)D(\sqrt\eta\xi\bar\beta)D(η​ξβˉ​) rather than D†(ηξβ)D^\dagger(\sqrt\eta\xi\beta)D†(η​ξβ); a numerical evaluation of the printed (24) for the input 0.6∣0⟩+0.8i∣1⟩0.6|0\rangle+0.8i|1\rangle0.6∣0⟩+0.8i∣1⟩ gives an error of 0.380.380.38 in the output matrix, against 8×10−58\times10^{-5}8×10−5 (grid-limited) for the corrected one. The Theorem itself, existential in the protocol, is unaffected.

Difficulty

The obvious route is the paper's: write ρ=∫Pα∣α⟩⟨α∣ d2α\rho=\int P_\alpha|\alpha\rangle\langle\alpha|\,d^2\alphaρ=∫Pα​∣α⟩⟨α∣d2α, compute everything for coherent states, and integrate. For nonclassical states PPP is not a function, or even a measure, so this route is not a proof; passing from coherent inputs to all densities needs a density or continuity argument in trace norm, with interchange of the outcome integral and the infinite Fock series. The Bell projection itself is a contraction against improper vectors, here encoded as an absolutely convergent four-fold series whose convergence for arbitrary trace-class inputs is part of the work. Finally, the composition Eη∘Eη′=Eηη′\mathcal E_\eta\circ\mathcal E_{\eta'}=\mathcal E_{\eta\eta'}Eη​∘Eη′​=Eηη′​ and the covariance (18) are standard on covariance matrices but must be established on number-basis kernels, where they are identities between infinite series with binomial weights.

Formalization scope

  • Representation. All states and outputs are number-basis kernels. Inputs are bounded operators on ℓ2(N)\ell^2(\mathbb N)ℓ2(N) or ℓ2(N×N)\ell^2(\mathbb N\times\mathbb N)ℓ2(N×N) satisfying the published density predicates (trace class, self-adjoint, positive, unit trace), from QAlgorithms_Papers_Independent_Dependency50_P39; the loss channel is the vacuum-loss kernel of QAlgorithms_Papers_Independent_Frontier30_P21; coherent states use its coherentDensity.
  • Bell projection. It is the Fock form of (16) with (A4), with the factor (2π)−1(2\pi)^{-1}(2π)−1 explicit; the CV-Bell states are not formalized as vectors. The outcome is β=(x+ip)/2\beta=(x+ip)/\sqrt2β=(x+ip)/2​ and the average is over R×R\mathbb R\times\mathbb RR×R with Lebesgue measure, the paper's dx dpdx\,dpdxdp.
  • Conventions. The resource has Alice's mode A′A'A′ first and Bob's mode BBB second; the loss of ρE′\rho_{\mathcal E'}ρE′​ acts on BBB. Every series is asserted summable and every integrand integrable as part of the conclusion, so default values of divergent series or non-integrable functions never satisfy a statement.
  • Corrected sign. Milestones (20), (23), (24) and the goal use α−βˉ\alpha-\bar\betaα−βˉ​ and the correction D(η′ξβˉ)D(\sqrt{\eta'}\xi\bar\beta)D(η′​ξβˉ​), as explained above.
  • Coherent-input restriction. Milestones (20), (22), (23) are stated for coherent inputs (PPP a point mass), because the PPP representation (19) is not available for general states; (24) and the goal are stated for every density, as printed.
  • LOCC. The general class of LOCC maps is not formalized; Λ\LambdaΛ is the explicit protocol of (24). An existential "there is a map Λ\LambdaΛ with Λ(ρE′)=I⊗Eη(ρAB)\Lambda(\rho_{\mathcal E'})=\mathcal I\otimes\mathcal E_\eta(\rho_{AB})Λ(ρE′​)=I⊗Eη​(ρAB​)" would be trivially true (take Λ\LambdaΛ constant) and is ruled out by stating the protocol, with η′\eta'η′, ξ\xiξ and the correction fixed before ρAB\rho_{AB}ρAB​; likewise the Bell branch is the defining series, never its closed form.
  • Not covered. The thermal-loss and amplifier versions (§III, (30)–(33)), the nnn-use relative-entropy bound (§II.C), and the finite-dimensional review (§II.A). The statement Eη(∣α⟩⟨α∣)=∣ηα⟩⟨ηα∣\mathcal E_\eta(|\alpha\rangle\langle\alpha|)=|\sqrt\eta\alpha\rangle\langle\sqrt\eta\alpha|Eη​(∣α⟩⟨α∣)=∣η​α⟩⟨η​α∣ used inside (20) is the existing Open goal Frontier30.P21.coherentOutput and is not posed again.
  • Reusable parts. Proofs of displacement covariance and of channel composition on Fock kernels, and summability lemmas for displacement matrices against trace-class kernels, are useful beyond this mission; contributions of such lemmas are welcome.

Selected references

  • R. Namiki, Teleportation stretching for single-mode Gaussian channels, arXiv:1603.05292v1, 2016. https://arxiv.org/abs/1603.05292
  • S. Pirandola, R. Laurenza, C. Ottaviani, L. Banchi, Fundamental limits of repeaterless quantum communications, arXiv:1510.08863v3, 2015. https://arxiv.org/abs/1510.08863
  • S. L. Braunstein, H. J. Kimble, Teleportation of continuous quantum variables, Phys. Rev. Lett. 80, 869, 1998. https://doi.org/10.1103/PhysRevLett.80.869
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Operations ResearchOptimizationProbability·Captain: mikedeng1

Role of Risk Aversion in Price Postponement Under Supply Random Yield: Ex Ante and Responsive Pricing Share One CVaR Risk-Aversion ThresholdResearch Paper

Motivation

Many manufacturing processes deliver only a random fraction of what they start: semiconductor wafers, biologics, agricultural produce and recycled materials all suffer random yield. A firm facing yield risk has two classical levers. It can inflate production to hedge against low yield, and it can postpone pricing until the yield is observed, so that the price clears whatever was actually produced. The operations literature has long studied both levers for a risk-neutral firm, starting from the price-setting newsvendor (Petruzzi and Dada, 1999).

Real firms, and especially small producers exposed to a single bad harvest or batch, care about low-profit outcomes more than about the mean. Kouvelis, Xiao and Yang (Management Science, 2021) model this with the conditional value-at-risk (CVaR) of profit, the criterion introduced by Rockafellar and Uryasev (2000) and used for newsvendor problems by Chen, Xu and Zhang (2009). Their first finding is that a sufficiently risk-averse firm does not produce at all, and that the risk level at which production stops is the same whether or not the firm can postpone its price. This mission formalizes that finding.

Setting

A monopoly firm sells one product to a market with deterministic demand d(p)d(p)d(p), continuous and strictly decreasing in the price p∈[0,p0]p\in[0,p_0]p∈[0,p0​], where p0>0p_0>0p0​>0 is the maximal allowable price, d(p0)=0d(p_0)=0d(p0​)=0. The inverse demand p(x)p(x)p(x) satisfies p(d(p))=pp(d(p))=pp(d(p))=p and d(p(x))=xd(p(x))=xd(p(x))=x for x∈[0,d(0)]x\in[0,d(0)]x∈[0,d(0)]. Assumption 2 of the paper requires the revenue x↦p(x) xx\mapsto p(x)\,xx↦p(x)x to be concave on [0,d(0)][0,d(0)][0,d(0)].

Producing qqq units of input costs cqcqcq and yields qξq\xiqξ sellable units. The yield factor ξ\xiξ is a continuous random variable with law ν\nuν, support [l,u][l,u][l,u] with 0≤l<u≤10\le l<u\le10≤l<u≤1, c.d.f. GGG and mean μ\muμ. The cost satisfies 0≤c≤p0μ0\le c\le p_0\mu0≤c≤p0​μ, so that production is not hopeless. Write G−1(η)=inf⁡{x:G(x)≥η}G^{-1}(\eta)=\inf\{x:G(x)\ge\eta\}G−1(η)=inf{x:G(x)≥η} for the lower quantile and

g(η)=1η∫lG−1(η)ξ dG(ξ),η∈(0,1],g(\eta)=\frac1\eta\int_l^{G^{-1}(\eta)}\xi\,dG(\xi),\qquad \eta\in(0,1],g(η)=η1​∫lG−1(η)​ξdG(ξ),η∈(0,1],

for the mean of the lowest η\etaη-fraction of yields.

For a random profit π\piπ and a risk level η∈(0,1]\eta\in(0,1]η∈(0,1],

CVaRη(π)=max⁡v∈R{v+1η Emin⁡{π−v,0}},\mathrm{CVaR}_\eta(\pi)=\max_{v\in\mathbb R}\Big\{v+\frac1\eta\,\mathbb E\min\{\pi-v,0\}\Big\},CVaRη​(π)=v∈Rmax​{v+η1​Emin{π−v,0}},

the average profit over the worst η\etaη-fraction of outcomes; η=1\eta=1η=1 is risk neutrality and smaller η\etaη means more risk aversion.

Under ex ante pricing the firm picks pa∈[0,p0]p_a\in[0,p_0]pa​∈[0,p0​] and qa≥0q_a\ge0qa​≥0 before the yield realizes and maximizes Πa(pa,qa)=CVaRη(pamin⁡{d(pa),qaξ}−cqa)\Pi_a(p_a,q_a)=\mathrm{CVaR}_\eta\big(p_a\min\{d(p_a),q_a\xi\}-cq_a\big)Πa​(pa​,qa​)=CVaRη​(pa​min{d(pa​),qa​ξ}−cqa​). Under responsive pricing it picks qr≥0q_r\ge0qr​≥0, observes ξ\xiξ, then picks the revenue-maximizing price, and maximizes

Πr(qr)=CVaRη(max⁡pr∈[0,p0]prmin⁡{d(pr),qrξ}−cqr).\Pi_r(q_r)=\mathrm{CVaR}_\eta\Big(\max_{p_r\in[0,p_0]}p_r\min\{d(p_r),q_r\xi\}-cq_r\Big).Πr​(qr​)=CVaRη​(pr​∈[0,p0​]max​pr​min{d(pr​),qr​ξ}−cqr​).

Since q=0q=0q=0 gives CVaR 000, the firm produces under a scheme when some decision has strictly positive CVaR, and otherwise not producing is optimal.

Formalization targets

Goal: one threshold for both schemes (Proposition 4(i))

There is a single η∗∈[0,1]\eta^*\in[0,1]η∗∈[0,1], either η∗=0\eta^*=0η∗=0 or a solution of p0 g(η∗)=cp_0\,g(\eta^*)=cp0​g(η∗)=c, such that for every η∈(0,1]\eta\in(0,1]η∈(0,1]

ex ante firm produces  ⟺  η>η∗  ⟺  responsive firm produces.\text{ex ante firm produces}\iff\eta>\eta^*\iff\text{responsive firm produces}.ex ante firm produces⟺η>η∗⟺responsive firm produces.

This is the paper's ηa∗(p0,c)=ηr∗(p0,c)\eta_a^*(p_0,c)=\eta_r^*(p_0,c)ηa∗​(p0​,c)=ηr∗​(p0​,c), with the boundary case η=η∗\eta=\eta^*η=η∗ stated correctly (there the optimal CVaR is 000, so the firm is indifferent and "produces" in the strict sense fails).

Milestones

  1. Property 1: for a continuously distributed profit, the maximization formula equals the tail mean E[π∣π≤VaRη(π)]\mathbb E[\pi\mid\pi\le\mathrm{VaR}_\eta(\pi)]E[π∣π≤VaRη​(π)], attained at v=VaRη(π)v=\mathrm{VaR}_\eta(\pi)v=VaRη​(π).
  2. Property 2: the CVaR of a profit concave in the decision is concave in the decision.
  3. Proposition 1: at a fixed price pap_apa​, the optimal ex ante quantity is d(pa)/δd(p_a)/\deltad(pa​)/δ above a threshold price p~\tilde pp~​ and 000 below it.
  4. The tail mean ggg: strictly increasing and continuous on (0,1](0,1](0,1], with g(1)=μg(1)=\mug(1)=μ and g(0+)=lg(0^+)=lg(0+)=l.
  5. Proposition 2: the ex ante threshold ηa∗\eta_a^*ηa∗​.
  6. Lemma 1: the responsive firm's second-stage price is p(min⁡{qrξ,d∗})p(\min\{q_r\xi,d^*\})p(min{qr​ξ,d∗}), where d∗d^*d∗ maximizes revenue.
  7. Proposition 3: Πr\Pi_rΠr​ is concave and the responsive threshold ηr∗\eta_r^*ηr∗​ exists.

Significance

The result says that price postponement, although it raises the profit of a firm that does produce, does not enlarge the set of risk-averse firms willing to produce. The threshold is explicit: η∗=0\eta^*=0η∗=0 when p0l>cp_0l>cp0​l>c, and otherwise η∗\eta^*η∗ solves g(η)=c/p0g(\eta)=c/p_0g(η)=c/p0​. Because ggg depends only on the yield law, the threshold separates cost and price power (c/p0c/p_0c/p0​) from yield risk (ggg), which is what the paper's comparative statics in ccc, p0p_0p0​ and the yield distribution (Proposition 4(ii)–(iv)) build on.

The mission states the paper's threshold results and its two CVaR properties in Lean. None of them is machine-checked anywhere. Proofs of the milestones would also provide a reusable CVaR toolkit on a general probability space: the identification of the maximization formula with the lower-tail mean, and concavity of CVaR in a decision parameter.

Difficulty

The paper's argument uses densities and derivatives throughout: g′(η)>0g'(\eta)>0g′(η)>0, a first-order condition at q=0q=0q=0, L'Hospital's rule for g(0+)g(0^+)g(0+). The model here assumes only an atomless law with full support, so every such step has to be replaced by a measure-theoretic one. CVaR is a supremum of integrals over an unbounded index, so comparisons between the two schemes cannot be read off a closed form. The responsive profit is itself a maximum over prices inside an expectation inside a supremum. Finally, the two schemes have different optimal decisions everywhere except in the limit of vanishing production, so an argument that compares optimal values fails: the content is in comparing whether positive CVaR is attainable at all.

Formalization scope

  • The yield is its law ν : Measure ℝ: a probability measure without atoms (NullSingletonClass), with ν [l,u]ᶜ = 0 and positive mass on every open subinterval of [l,u]. The paper's density is not assumed. Expectations are Bochner integrals against ν.
  • p0p_0p0​ is a finite positive real (the paper also allows p0=∞p_0=\inftyp0​=∞). Demand d and inverse demand P are two functions with both inverse identities on their intervals.
  • CVaR (RiskPostpone.Threshold.cvar) is the real supremum over v∈Rv\in\mathbb Rv∈R of the bracket. The model's profits are bounded on the support, so the supremum is genuine there; the general CVaR properties assume integrability. VaR and the yield quantile use the published MultistageStochastic.valueAtRisk.
  • The responsive maximum is the sSup of the image of [0,p0][0,p_0][0,p0​], which is nonempty and bounded.
  • "Produces" is strict: some decision has CVaR >0>0>0. With ≥\ge≥ the statement would be trivially true at q=0q=0q=0; with a CVaR supremum that could be junk 000, or with two separate thresholds for the two schemes, the goal would lose its content. All three formalizations are ruled out.
  • Assumption 1 of the paper (an IGFR-type condition and increasing price elasticity) is used only for the uniqueness of the optimal ex ante price and is not assumed. Assumption 2 is stated without "twice differentiable". In Lemma 1, d∗d^*d∗ is any maximizer of revenue on [0,d(0)][0,d(0)][0,d(0)] rather than the root of the first-order condition. Proposition 1 excludes the degenerate case c=0=lc=0=lc=0=l (there the optimal quantity does not exist). Property 1 assumes the profit is integrable, essentially bounded above and atomless.
  • Not formalized: the first-order conditions of Propositions 2(ii) and 3(ii), Proposition 4(ii)–(iv), Corollaries 1–4, the linear-demand comparisons of §5.2–§5.4, and the extensions of §7.

Contributions welcome: proofs of the milestones, especially the general CVaR facts (Properties 1 and 2) and the measure-theoretic properties of ggg, which are reusable beyond this model.

Selected references

  • P. Kouvelis, G. Xiao, N. Yang, Role of Risk Aversion in Price Postponement under Supply Random Yield, Management Science 67(8), 4826–4844, 2021. https://doi.org/10.1287/mnsc.2020.3755 (formalized from the accepted manuscript MS-OPM-18-01273.R2)
  • R. T. Rockafellar, S. Uryasev, Optimization of conditional value-at-risk, Journal of Risk 2(3), 21–41, 2000. https://doi.org/10.21314/JOR.2000.038
  • R. T. Rockafellar, S. Uryasev, Conditional value-at-risk for general loss distributions, Journal of Banking & Finance 26(7), 1443–1471, 2002. https://doi.org/10.1016/S0378-4266(02)00271-6
  • Y. Chen, M. Xu, Z. G. Zhang, A risk-averse newsvendor model under the CVaR criterion, Operations Research 57(4), 1040–1044, 2009. https://doi.org/10.1287/opre.1080.0603
  • N. C. Petruzzi, M. Dada, Pricing and the newsvendor problem: a review with extensions, Operations Research 47(2), 183–194, 1999. https://doi.org/10.1287/opre.47.2.183
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Mathematical PhysicsQuantum Information·Captain: mikedeng1

Preparation of Entangled States by Quantum Markov Processes: Every n-Qubit Pure State Is the Unique and Attractive Stationary State of a Dissipative Process with Relaxation Time 1/min_k g_kResearch Paper

Motivation

Quantum technologies usually prepare a desired state by isolating a system and driving it with carefully timed unitary operations; coupling to an environment is treated as noise. Dissipative state preparation reverses this view: one engineers the system–environment coupling so that the open-system dynamics itself drives every initial state into a prescribed target state. Because the target is a fixed point that attracts all initial conditions, the preparation needs no initialization and is self-correcting against perturbations that leave the dynamics unchanged.

In 2008 three closely related papers made this programme concrete. Diehl, Micheli, Kantian, Kraus, Büchler and Zoller showed how cold atoms can be driven into condensed many-body states by engineered dissipation (arXiv:0803.1482); Verstraete, Wolf and Cirac showed that dissipative dynamics can perform universal quantum computation and prepare matrix product and PEPS states (arXiv:0803.1447); and Kraus, Büchler, Diehl, Kantian, Micheli and Zoller, Preparation of entangled states by quantum Markov processes (arXiv:0803.1463), gave the general uniqueness criteria and the explicit construction this mission formalizes. The last paper's central claim is that every pure state of nnn qubits is the unique stationary state of an explicitly given Markovian process, and that this process relaxes on a time scale independent of nnn.

Setting

A quantum Markov process on a ddd-dimensional Hilbert space is a master equation ρ˙=L(ρ)\dot\rho = \mathcal L(\rho)ρ˙​=L(ρ) for a density matrix ρ\rhoρ (a positive semidefinite d×dd\times dd×d complex matrix of trace one). In the paper's Eq. (2) the generator, or Liouvillian, is

LH,cl(ρ)=−i[H,ρ]+∑lgl(2clρcl†−cl†clρ−ρcl†cl),\mathcal L_{H,c_l}(\rho) = -i[H,\rho] + \sum_l g_l\bigl(2c_l\rho c_l^\dagger - c_l^\dagger c_l\rho - \rho c_l^\dagger c_l\bigr),LH,cl​​(ρ)=−i[H,ρ]+l∑​gl​(2cl​ρcl†​−cl†​cl​ρ−ρcl†​cl​),

where HHH is a Hermitian matrix (the Hamiltonian), the clc_lcl​ are arbitrary complex matrices (the jump operators) and glg_lgl​ are rates. The solution is ρ(t)=etL(ρ(0))\rho(t) = e^{t\mathcal L}(\rho(0))ρ(t)=etL(ρ(0)). The paper writes P=∑lglcl†clP = \sum_l g_l c_l^\dagger c_lP=∑l​gl​cl†​cl​, Q=P−iHQ = P - iHQ=P−iH and E(ρ)=2∑lglclρcl†\mathcal E(\rho) = 2\sum_l g_l c_l\rho c_l^\daggerE(ρ)=2∑l​gl​cl​ρcl†​.

A stationary state is a density matrix with L(ρ)=0\mathcal L(\rho) = 0L(ρ)=0. A vector annihilated by every clc_lcl​ and an eigenvector of HHH is a dark vector; the set D=K(P)∩ES(H)D = K(P)\cap ES(H)D=K(P)∩ES(H) of dark vectors, when it is a subspace (all dark vectors share one eigenvalue EEE of HHH), yields the dark states, the density matrices with range inside DDD.

For nnn qubits, σ−(k)=1⊗⋯⊗∣0⟩k⟨1∣⊗⋯⊗1\sigma_-^{(k)} = \mathbb 1\otimes\dots\otimes|0\rangle_k\langle1|\otimes\dots\otimes\mathbb 1σ−(k)​=1⊗⋯⊗∣0⟩k​⟨1∣⊗⋯⊗1 lowers qubit kkk from ∣1⟩|1\rangle∣1⟩ to ∣0⟩|0\rangle∣0⟩. Given any unitary UUU, the target is ∣Ψ⟩=U∣0n⟩|\Psi\rangle = U|0^n\rangle∣Ψ⟩=U∣0n⟩, which ranges over all pure states, and the construction of §IV uses the nnn jump operators ck=Uσ−(k)U†c_k = U\sigma_-^{(k)}U^\daggerck​=Uσ−(k)​U† with rates gkg_kgk​. The relaxation time TrelaxT_{\mathrm{relax}}Trelax​ is the inverse of the least value of −Re⁡μ-\operatorname{Re}\mu−Reμ over the nonzero eigenvalues μ\muμ of L\mathcal LL.

Formalization targets

Goal: unique, attractive, and fast

For n≥1n\ge1n≥1, any unitary UUU and rates g1,…,gn>0g_1,\dots,g_n>0g1​,…,gn​>0:

(a)∀H=H† with H∣Ψ⟩=E∣Ψ⟩:LH,ck(ρ)=0, ρ a density matrix  ⟺  ρ=∣Ψ⟩⟨Ψ∣;\text{(a)}\quad \forall H = H^\dagger \text{ with } H|\Psi\rangle = E|\Psi\rangle:\qquad \mathcal L_{H,c_k}(\rho) = 0,\ \rho \text{ a density matrix} \iff \rho = |\Psi\rangle\langle\Psi|;(a)∀H=H† with H∣Ψ⟩=E∣Ψ⟩:LH,ck​​(ρ)=0, ρ a density matrix⟺ρ=∣Ψ⟩⟨Ψ∣; (b)etL{ck}(ρ)→t→∞∣Ψ⟩⟨Ψ∣ for every density matrix ρ;(c)Trelax=1min⁡kgk.\text{(b)}\quad e^{t\mathcal L_{\{c_k\}}}(\rho)\xrightarrow[t\to\infty]{}|\Psi\rangle\langle\Psi| \text{ for every density matrix } \rho;\qquad \text{(c)}\quad T_{\mathrm{relax}} = \frac{1}{\min_k g_k}.(b)etL{ck​}​(ρ)t→∞​∣Ψ⟩⟨Ψ∣ for every density matrix ρ;(c)Trelax​=mink​gk​1​.

Clause (a) allows every Hamiltonian that has the target as an eigenvector; (b) and (c) concern the purely dissipative process H=0H = 0H=0, the one the paper solves explicitly.

Milestones

  1. Dark states are stationary (§II, p. 2).
  2. Theorem 1 (p. 2): L(∣Φ⟩⟨Φ∣)=0\mathcal L(|\Phi\rangle\langle\Phi|) = 0L(∣Φ⟩⟨Φ∣)=0 iff Q†∣Φ⟩=λ∣Φ⟩Q^\dagger|\Phi\rangle = \lambda|\Phi\rangleQ†∣Φ⟩=λ∣Φ⟩ and cl∣Φ⟩=λl∣Φ⟩c_l|\Phi\rangle = \lambda_l|\Phi\ranglecl​∣Φ⟩=λl​∣Φ⟩ with ∑lgl∣λl∣2=Re⁡λ\sum_l g_l|\lambda_l|^2 = \operatorname{Re}\lambda∑l​gl​∣λl​∣2=Reλ.
  3. D′=DD' = DD′=D (p. 3, footnote [35]): Q†ψ=iλψQ^\dagger\psi = i\lambda\psiQ†ψ=iλψ with λ\lambdaλ real iff ψ\psiψ is dark.
  4. Theorem 2 (p. 3): if no nonzero subspace S⊥DS\perp DS⊥D satisfies clS⊆Sc_lS\subseteq Scl​S⊆S for all lll, the only stationary states are the dark states.
  5. Dark vectors of {ck}\{c_k\}{ck​} (§IV, p. 4): ckφ=0c_k\varphi = 0ck​φ=0 for all kkk iff φ∈C∣Ψ⟩\varphi\in\mathbb C|\Psi\rangleφ∈C∣Ψ⟩.
  6. The monomial claim (§IV, p. 4): for χ⊥∣0n⟩\chi\perp|0^n\rangleχ⊥∣0n⟩, χ≠0\chi\ne0χ=0, some product PPP of the σ−(k)\sigma_-^{(k)}σ−(k)​ has ⟨0n∣P∣χ⟩≠0\langle0^n|P|\chi\rangle\ne0⟨0n∣P∣χ⟩=0.
  7. Unitary covariance (§IV.A, p. 4): L{Uσ−(k)U†}(σ)=UL{σ−(k)}(U†σU)U†\mathcal L_{\{U\sigma_-^{(k)}U^\dagger\}}(\sigma) = U\mathcal L_{\{\sigma_-^{(k)}\}}(U^\dagger\sigma U)U^\daggerL{Uσ−(k)​U†}​(σ)=UL{σ−(k)​}​(U†σU)U†.
  8. One qubit (§IV.A, p. 4): eigenvalues 0,−2g,−g,−g0, -2g, -g, -g0,−2g,−g,−g on ∣0⟩⟨0∣,σz,σx,σy|0\rangle\langle0|, \sigma_z, \sigma_x, \sigma_y∣0⟩⟨0∣,σz​,σx​,σy​.
  9. Product spectrum (§IV.A, p. 4): the explicit operators U(σi1(1)⊗⋯⊗σin(n))U†U(\sigma_{i_1}^{(1)}\otimes\cdots\otimes\sigma_{i_n}^{(n)})U^\daggerU(σi1​(1)​⊗⋯⊗σin​(n)​)U† form an eigenbasis, with eigenvalues ∑kλik\sum_k\lambda_{i_k}∑k​λik​​; these are exactly −∑kmkgk-\sum_k m_kg_k−∑k​mk​gk​, mk∈{0,1,2}m_k\in\{0,1,2\}mk​∈{0,1,2}.

Significance

The result. The goal shows that dissipative preparation is universal for pure states: no pure state, however entangled, is out of reach, and the required jump operators are written down explicitly. Clause (c) states that the time to reach the target is governed by the weakest single coupling and does not grow with the number of qubits. Theorems 1 and 2 are general tools independent of the construction: Theorem 1 characterizes every pure stationary state of every Lindblad generator, and Theorem 2 is a checkable sufficient condition for the absence of other stationary states. The later sections of the paper (stabilizer and graph states, PEPS and the AKLT state, a driven condensate, the η\etaη-condensate) apply these tools to physically local processes.

Formalizing it. The results are classical and proved in the paper, partly in sketched form ("straightforward", "the same arguments as above"). No machine-checked proof of any of them is known. The formalization supplies complete arguments for the sketched steps, fixes the guards the printed statements omit (listed below), and produces a reusable layer of statements about the spectrum and stationary states of Lindblad generators on finite-dimensional spaces.

Difficulty

The first idea for uniqueness is to show that the target is the only pure stationary state, using Theorem 1. That is not enough: a Lindblad generator can have mixed stationary states even when its pure stationary state is unique (with Hermitian jump operators the maximally mixed state is always stationary, Eq. (4)). Excluding mixed stationary states is the content of Theorem 2, whose proof requires a positivity argument for Q†ρ+ρQQ^\dagger\rho + \rho QQ†ρ+ρQ and a decomposition of ρ\rhoρ along D⊕D⊥D\oplus D^\perpD⊕D⊥.

For convergence, uniqueness of the stationary state does not suffice either: a purely imaginary eigenvalue would make etL(ρ)e^{t\mathcal L}(\rho)etL(ρ) oscillate forever. Clauses (b) and (c) need the full spectrum of the 4n4^n4n-dimensional Liouvillian, obtained by reducing to U=1U = \mathbb 1U=1 and decoupling into nnn single-qubit problems; in Lean this means relating the eigenvalues of a generator on 2n×2n2^n\times 2^n2n×2n matrices to those of tensor factors.

Formalization scope

The generator, the semigroup etLe^{t\mathcal L}etL (matrix exponential of the Liouvillian as a linear map), and the predicates stationary (density matrix with Lρ=0\mathcal L\rho = 0Lρ=0), attractive and lazy (nonzero subspace invariant under all jump operators) are reused from the published definition QAlgorithms_Papers_Independent_Dependency50_P16. That layer normalizes the dissipator as ∑kVkρVk†−12{Vk†Vk,ρ}\sum_k V_k\rho V_k^\dagger - \frac12\{V_k^\dagger V_k,\rho\}∑k​Vk​ρVk†​−21​{Vk†​Vk​,ρ}; the paper's rates enter through jump operators Vl=2gl clV_l = \sqrt{2g_l}\,c_lVl​=2gl​​cl​, which reproduces Eq. (2) exactly. Operators are complex d×dd\times dd×d matrices, states are vectors in Cd\mathbb C^dCd, and nnn qubits are indexed by {0,…,2n−1}\{0,\dots,2^n-1\}{0,…,2n−1} with qubit 1 the most significant bit; ∣0n⟩|0^n\rangle∣0n⟩ is the basis vector of index 000. Density matrices are positive semidefinite of trace one, and ∣ψ⟩⟨ψ∣|\psi\rangle\langle\psi|∣ψ⟩⟨ψ∣ is formed without normalization, so unit norm is assumed where the paper says "state". Convergence is entrywise.

Conventions added to the paper and disclosed in each statement:

  • rates gl>0g_l>0gl​>0 (the paper allows gℓ≥0g_\ell\ge0gℓ​≥0; with a zero rate Theorem 1 and uniqueness fail);
  • Theorem 2 quantifies over nonzero subspaces (the zero subspace would make its hypothesis unsatisfiable), and keeps the standing assumption that DDD is a subspace, as a fixed eigenvalue EEE;
  • n≥1n\ge1n≥1 in clause (c); the relaxation rate is a least element and must be positive before its reciprocal is a finite relaxation time;
  • "∣φ⟩=U∣0n⟩|\varphi\rangle = U|0^n\rangle∣φ⟩=U∣0n⟩" is read up to a scalar, and the single-qubit "iff σi∈Σk\sigma_i\in\Sigma_kσi​∈Σk​" as four eigen-equations.

A trivializing formalization is ruled out: the target is not fixed to U=1U = \mathbb 1U=1, the jump operators are the conjugated Uσ−(k)U†U\sigma_-^{(k)}U^\daggerUσ−(k)​U† and not σ−(k)\sigma_-^{(k)}σ−(k)​, clause (a) quantifies over all Hamiltonians with the target as eigenvector rather than only H=0H = 0H=0, and the relaxation time refers to the actual nonzero spectrum of the generator.

A complete development needs: properties of the Lindblad generator under unitary conjugation; positivity arguments for completely positive maps on matrices; the tensor-product structure of 2n×2n2^n\times 2^n2n×2n matrices over qubit wires; and the spectrum and diagonalizability of a sum of commuting single-site generators. The spectral and stationary-state lemmas are reusable for any finite-dimensional open-system mission. Contributions to any milestone, and alternative proofs of Theorem 2 or of the spectrum, are welcome.

Selected references

  • B. Kraus, H. P. Büchler, S. Diehl, A. Kantian, A. Micheli, P. Zoller, Preparation of entangled states by quantum Markov processes, Phys. Rev. A 78 (2008); arXiv:0803.1463v3. https://arxiv.org/abs/0803.1463
  • S. Diehl, A. Micheli, A. Kantian, B. Kraus, H. P. Büchler, P. Zoller, Quantum states and phases in driven open quantum systems with cold atoms, Nature Physics 4 (2008). https://arxiv.org/abs/0803.1482
  • F. Verstraete, M. M. Wolf, J. I. Cirac, Quantum computation and quantum-state engineering driven by dissipation, Nature Physics 5 (2009). https://arxiv.org/abs/0803.1447
  • E. Malvetti et al., Reachability, coolability, and stabilizability of open Markovian quantum systems with fast unitary control, 2023; arXiv:2308.00561. https://arxiv.org/abs/2308.00561
  • G. Lindblad, On the generators of quantum dynamical semigroups, Comm. Math. Phys. 48 (1976). https://doi.org/10.1007/BF01608499
  • V. Gorini, A. Kossakowski, E. C. G. Sudarshan, Completely positive dynamical semigroups of N-level systems, J. Math. Phys. 17 (1976). https://doi.org/10.1063/1.522979
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Noncommutative Lp modules: Every Lp Module over a Finite-Dimensional von Neumann Algebra Is Isometrically Isomorphic, as a Module, to a Principal Column Sum of Projected Lp SpacesResearch Paper

Motivation

A Hilbert space has an orthonormal basis, so every Hilbert space is isometric to some ℓ2(I)\ell^2(I)ℓ2(I). Hilbert C∗^*∗-modules, the analogue of Hilbert spaces in which the inner product takes values in an operator algebra, have no such basis in general. Over a von Neumann algebra M\mathcal MM, Paschke showed that the self-dual Hilbert C∗^*∗-modules are exactly the "ultraweak direct sums" of corners qαMq_\alpha\mathcal Mqα​M cut by projections qα∈Mq_\alpha\in\mathcal Mqα​∈M (Paschke, Trans. AMS 182, 1973).

Junge and Sherman (arXiv:math/0301044v2, 2003, revised 2004) carried this picture to the noncommutative LpL^pLp spaces Lp(M)L^p(\mathcal M)Lp(M), 0<p≤∞0<p\le\infty0<p≤∞. They introduced LpL^pLp modules, whose inner product takes values in Lp/2(M)L^{p/2}(\mathcal M)Lp/2(M), and proved that every LpL^pLp module is a column sum of corners qαLp(M)q_\alpha L^p(\mathcal M)qα​Lp(M). The result organizes the study of module maps between noncommutative LpL^pLp spaces (the paper's §5–§6 on commutants and LpL^pLp bimodules build on it), and it is the LpL^pLp form of the orthonormal-basis theorem. Earlier, Junge had proved a version for a special class of LpL^pLp modules ([J1, Prop. 2.8]).

Setting

Let n∈Nn\in\mathbb Nn∈N and let M\mathcal MM be a unital ∗*∗-subalgebra of the matrix algebra Mn(C)M_n(\mathbb C)Mn​(C); these are exactly the finite-dimensional von Neumann algebras. For real 0<p<∞0<p<\infty0<p<∞, Lp(M)L^p(\mathcal M)Lp(M) is M\mathcal MM with the tracial (quasi)norm

∥a∥p=(Tr (a∗a)p/2)1/p.\|a\|_p=\big(\mathrm{Tr}\,(a^*a)^{p/2}\big)^{1/p}.∥a∥p​=(Tr(a∗a)p/2)1/p.

In the Lean files this is lpNorm p a, the published Schatten norm schattenNorm.

Let X\mathfrak XX be a complex vector space with a right action (ξ,x)↦ξx(\xi,x)\mapsto\xi x(ξ,x)↦ξx of M\mathcal MM (act). An Lp/2L^{p/2}Lp/2-valued inner product (Definition 2.1) is a map ⟨⋅,⋅⟩:X×X→M\langle\cdot,\cdot\rangle:\mathfrak X\times\mathfrak X\to\mathcal M⟨⋅,⋅⟩:X×X→M (ip). It is conjugate linear in the first variable and linear in the second, and satisfies

⟨ξ,ηx⟩=⟨ξ,η⟩x,⟨ξ,η⟩=⟨η,ξ⟩∗,⟨ξ,ξ⟩≥0,⟨ξ,ξ⟩=0  ⟺  ξ=0.\langle\xi,\eta x\rangle=\langle\xi,\eta\rangle x,\qquad\langle\xi,\eta\rangle=\langle\eta,\xi\rangle^*,\qquad\langle\xi,\xi\rangle\ge0,\quad\langle\xi,\xi\rangle=0\iff\xi=0.⟨ξ,ηx⟩=⟨ξ,η⟩x,⟨ξ,η⟩=⟨η,ξ⟩∗,⟨ξ,ξ⟩≥0,⟨ξ,ξ⟩=0⟺ξ=0.

It induces

∥ξ∥=∥⟨ξ,ξ⟩1/2∥p=(Tr ⟨ξ,ξ⟩p/2)1/p\|\xi\|=\big\|\langle\xi,\xi\rangle^{1/2}\big\|_p=\big(\mathrm{Tr}\,\langle\xi,\xi\rangle^{p/2}\big)^{1/p}∥ξ∥=​⟨ξ,ξ⟩1/2​p​=(Tr⟨ξ,ξ⟩p/2)1/p

(gauge p ip ξ). By Proposition 2.2 this is a norm for p≥2p\ge2p≥2 and a p/2p/2p/2-norm for p≤2p\le2p≤2. A right LpL^pLp M\mathcal MM-module (Definition 2.3) is such an X\mathfrak XX that is complete in ∥⋅∥\|\cdot\|∥⋅∥.

Given projections (qα)α∈I(q_\alpha)_{\alpha\in I}(qα​)α∈I​ of M\mathcal MM, the column sum (2.4) is

⨁cqαLp={(ξα)α∈I: ξα∈qαLp, ∑αξα∗ξα converges},⟨(ξα),(ηα)⟩=∑αξα∗ηα.\textstyle\bigoplus_c q_\alpha L^p=\Big\{(\xi_\alpha)_{\alpha\in I}:\ \xi_\alpha\in q_\alpha L^p,\ \sum_\alpha\xi_\alpha^*\xi_\alpha\ \text{converges}\Big\},\qquad\langle(\xi_\alpha),(\eta_\alpha)\rangle=\sum_\alpha\xi_\alpha^*\eta_\alpha.⨁c​qα​Lp={(ξα​)α∈I​: ξα​∈qα​Lp, ∑α​ξα∗​ξα​ converges},⟨(ξα​),(ηα​)⟩=∑α​ξα∗​ηα​.

In Lean this is columnSumSet M q with colIp. The paper calls these modules principal.

Formalization targets

Goal: Theorem 2.5

For every right LpL^pLp M\mathcal MM-module X\mathfrak XX there are an index set III, projections (qα)(q_\alpha)(qα​) of M\mathcal MM and a map T:X→⨁cqαLpT:\mathfrak X\to\bigoplus_c q_\alpha L^pT:X→⨁c​qα​Lp with the following properties: TTT is bijective, complex linear and a module map, and

∥(∑αT(ξ)α∗T(ξ)α)1/2∥p=∥⟨ξ,ξ⟩1/2∥p(ξ∈X).\Big\|\Big(\sum_\alpha T(\xi)_\alpha^*T(\xi)_\alpha\Big)^{1/2}\Big\|_p=\big\|\langle\xi,\xi\rangle^{1/2}\big\|_p\qquad(\xi\in\mathfrak X).​(α∑​T(ξ)α∗​T(ξ)α​)1/2​p​=​⟨ξ,ξ⟩1/2​p​(ξ∈X).

This is the paper's statement as printed: "isometrically isomorphic, as a module". The index set and the projections are not fixed; they are part of the conclusion.

Milestones

  1. Lemma 1.2: Mφ1/p‾=Lps(φ)\overline{\mathcal M\varphi^{1/p}}=L^ps(\varphi)Mφ1/p​=Lps(φ) and φ1/pM‾=s(φ)Lp\overline{\varphi^{1/p}\mathcal M}=s(\varphi)L^pφ1/pM​=s(φ)Lp.
  2. Lemma 1.4: a bounded compatible net ξα=ξαpα\xi_\alpha=\xi_\alpha p_\alphaξα​=ξα​pα​, ξβpα=ξα\xi_\beta p_\alpha=\xi_\alphaξβ​pα​=ξα​ (α<β)(\alpha<\beta)(α<β) in LrL^rLr, r<∞r<\inftyr<∞, converges in norm.
  3. Proposition 2.2: ⟨ξ,η⟩=⟨ξ,ξ⟩1/2T⟨η,η⟩1/2\langle\xi,\eta\rangle=\langle\xi,\xi\rangle^{1/2}T\langle\eta,\eta\rangle^{1/2}⟨ξ,η⟩=⟨ξ,ξ⟩1/2T⟨η,η⟩1/2 with ∥T∥≤1\|T\|\le1∥T∥≤1; ∥⟨ξ,η⟩∥p/2≤∥ξ∥∥η∥\|\langle\xi,\eta\rangle\|_{p/2}\le\|\xi\|\|\eta\|∥⟨ξ,η⟩∥p/2​≤∥ξ∥∥η∥; and ∥⋅∥\|\cdot\|∥⋅∥ is a norm (p≥2p\ge2p≥2) or a p/2p/2p/2-norm (p≤2p\le2p≤2).
  4. (2.4): the column sum is a right LpL^pLp module.
  5. The cyclic case: ξM‾≅s(⟨ξ,ξ⟩1/2)Lp\overline{\xi\mathcal M}\cong s(\langle\xi,\xi\rangle^{1/2})L^pξM​≅s(⟨ξ,ξ⟩1/2)Lp.
  6. Case 2 (p>2p>2p>2): the closed span of an orthogonal family is isomorphic to a column sum, and a vector with 000 as best approximant from that span is orthogonal to the family.

Significance

Theorem 2.5 reduces questions about arbitrary LpL^pLp modules to columns of corners of Lp(M)L^p(\mathcal M)Lp(M). Two consequences follow. Module maps between LpL^pLp modules become matrices of maps between corners, and the paper identifies the commutant of the right action and describes LpL^pLp bimodules in this way. For p=2p=2p=2 the theorem is the orthonormal-basis theorem with M\mathcal MM-valued inner products; for p=∞p=\inftyp=∞ it is Paschke's theorem. In between, there is no Hilbert-space structure to fall back on.

The result is proved in the paper for every von Neumann algebra and every 0<p≤∞0<p\le\infty0<p≤∞. No part of it has been formalized. Mathlib has Hilbert C∗^*∗-modules with the C∗^*∗-norm and the Hermitian functional calculus for matrices, but no noncommutative LpL^pLp spaces, no LpL^pLp modules and no column sums. This mission produces the finite-dimensional theory: the definitions, the Cauchy–Schwarz inequality (2.1)–(2.2) for Lp/2L^{p/2}Lp/2-valued inner products, the column-sum construction and the structure theorem.

Difficulty

Even when M\mathcal MM is finite-dimensional, X\mathfrak XX need not be. An LpL^pLp module may be an infinite column of corners, and the theorem must produce the decomposition without any basis to start from. The obvious idea is to copy Gram–Schmidt and Zorn: take a maximal orthogonal family {ξα}\{\xi_\alpha\}{ξα​} and show that its closed span X0\mathfrak X_0X0​ is everything. For p≠2p\ne2p=2 this step fails as stated. Without an inner product on X\mathfrak XX there is no orthogonal projection onto X0\mathfrak X_0X0​. A best approximation from X0\mathfrak X_0X0​ exists only for p>2p>2p>2 (where X\mathfrak XX is a Banach space and X0\mathfrak X_0X0​ is reflexive), and turning "000 is a best approximant of ζ\zetaζ" into the algebraic identity ⟨ζ,ξλ⟩=0\langle\zeta,\xi_\lambda\rangle=0⟨ζ,ξλ​⟩=0 needs smoothness of the LpL^pLp norm together with the factorization (2.1). The case p<2p<2p<2 is reached by a different route through tensor products with Lq(M)L^q(\mathcal M)Lq(M). A second difficulty is that ∥⋅∥\|\cdot\|∥⋅∥ is the trace norm of ⟨ξ,ξ⟩1/2\langle\xi,\xi\rangle^{1/2}⟨ξ,ξ⟩1/2: it depends on ppp and is not the C∗^*∗-module norm, so Mathlib's C∗^*∗-module results do not apply.

Formalization scope

  • Finite-dimensional algebra. M\mathcal MM is a StarSubalgebra ℂ (Matrix (Fin n) (Fin n) ℂ). Lp(M)L^p(\mathcal M)Lp(M) is M\mathcal MM with the Schatten (quasi)norm of the trace, which is isometric to Haagerup's Lp(M)L^p(\mathcal M)Lp(M). This restriction is forced: Haagerup LpL^pLp spaces of a general von Neumann algebra exist neither in Mathlib nor on the platform. Because Lp/2(M)=ML^{p/2}(\mathcal M)=\mathcal MLp/2(M)=M as a set, the inner-product axioms do not depend on ppp; the norm does.
  • Exponents. Every item assumes 0<p<∞0<p<\infty0<p<∞, and Case 2 items assume p>2p>2p>2 as in the paper. p=∞p=\inftyp=∞ is out of scope.
  • The module. X\mathfrak XX is any complex vector space, of any dimension. The action is a function act with the right-module axioms for elements of M\mathcal MM, and the inner product is the structure LpInnerProduct. Completeness is sequential completeness for ∥⋅∥\|\cdot\|∥⋅∥ (GaugeComplete), since ∥⋅∥\|\cdot\|∥⋅∥ is only a quasi-norm for p<2p<2p<2.
  • Column sums. A column sum is a set of families I→Mn(C)I\to M_n(\mathbb C)I→Mn​(C). Convergence of ∑αξα∗ξα\sum_\alpha\xi_\alpha^*\xi_\alpha∑α​ξα∗​ξα​ is unconditional summability. In the goal, III lives in the universe of X\mathfrak XX.
  • Closures. In Lemma 1.2 and in the cyclic case the closures on the page are of finite-dimensional subspaces and are dropped. The closed span X0\mathfrak X_0X0​ of Case 2 keeps its closure.
  • No trivialization. Several formalizations would make the theorem empty or a different theorem, and none is admissible: measuring X\mathfrak XX in the C∗^*∗-norm ∥⟨ξ,ξ⟩∥1/2\|\langle\xi,\xi\rangle\|^{1/2}∥⟨ξ,ξ⟩∥1/2 (which makes the statement the p=∞p=\inftyp=∞ theorem), assuming X\mathfrak XX finite-dimensional or given with a basis, or asking only for a non-bijective or non-linear TTT.
  • Infrastructure. The development needs the Hermitian functional calculus on matrices (square roots, powers, support projections), Hölder's inequality and the p/2p/2p/2-triangle inequality for Schatten quasinorms, and summability of positive matrix families. These pieces are reusable beyond this mission. Proofs of any milestone are welcome, as are proofs of Theorem 2.5 by routes other than the paper's.

Selected references

  • M. Junge and D. Sherman, Noncommutative LpL^pLp modules, preprint arXiv:math/0301044v2, 2003, revised 14 Sep 2004. arXiv:math/0301044v2
  • W. L. Paschke, Inner product modules over B∗^*∗-algebras, Trans. Amer. Math. Soc. 182 (1973), 443–468 (reference [Pa] of the paper; cited as [P] on p. 10).
  • H. Kosaki, Applications of the complex interpolation method to a von Neumann algebra: noncommutative LpL^pLp-spaces, J. Funct. Anal. 56 (1984), 29–78 (reference [K1] of the paper).
  • U. Haagerup, LpL^pLp-spaces associated with an arbitrary von Neumann algebra, Algèbres d’opérateurs et leurs applications en physique mathématique, CNRS 15 (1979), 175–184 (reference [H] of the paper).
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AlgebraCombinatoricsRepresentation Theory·Captain: mikedeng1

Representations of Temperley–Lieb Algebras: Closed Product Formula for the Gram Determinants of the Cell ModulesResearch Paper

Motivation

The Temperley–Lieb algebra is a family of algebras built from generators that satisfy local relations. It appears in diagrammatic representation theory and provides a tractable setting in which to study cellular bases and Gram determinants. A Gram determinant tests whether the bilinear form on a module is degenerate after specializing its parameter. Thus an explicit determinant formula records information about when a cell module may cease to be simple. Enyang's 2007 paper develops a Murphy-style basis, a commuting family of operators and an orthogonal basis, then gives a closed product for these determinants. The mission targets that final product, with the preceding statements retained as milestones. Enyang, 2007

The generic cellular-algebra definitions and spectral-projector construction have already been formalized in the published package associated with Mathas's work. This mission specializes those objects to the actual Temperley–Lieb presentation and computes its explicit polynomial factors. Mathas, 2006

Setting

Let R=Z[x]R=\mathbb Z[x]R=Z[x], with xxx an indeterminate. For n≥1n\ge1n≥1, the algebra An(x)A_n(x)An​(x) has generators e1,…,en−1e_1,\ldots,e_{n-1}e1​,…,en−1​ and relations

ei2=xei,eiei±1ei=ei,eiej=ejeiwhen ∣i−j∣≥2.e_i^2=xe_i,\qquad e_ie_{i\pm1}e_i=e_i,\qquad e_ie_j=e_je_i\quad\text{when }|i-j|\ge2.ei2​=xei​,ei​ei±1​ei​=ei​,ei​ej​=ej​ei​when ∣i−j∣≥2.

A shape at level nnn is a pair λ=(f,n−2f)\lambda=(f,n-2f)λ=(f,n−2f) with 0≤2f≤n0\le2f\le n0≤2f≤n. A standard up–down tableau of shape λ\lambdaλ is a path of shapes from (0,0)(0,0)(0,0) to λ\lambdaλ: at each level its cup count stays fixed or increases by one. Write Tn(λ)\mathfrak T_n(\lambda)Tn​(λ) for the set of these paths and dim⁡(λ)=∣Tn(λ)∣\dim(\lambda)=|\mathfrak T_n(\lambda)|dim(λ)=∣Tn​(λ)∣. The paper orders paths by comparing their cup counts at every level; u▹tu\triangleright tu▹t means strict pointwise dominance. Enyang, §§1–2

For each shape, mλm_\lambdamλ​ is the product e1e3⋯e2f−1e_1e_3\cdots e_{2f-1}e1​e3​⋯e2f−1​. Ordered generator products wi,jw_{i,j}wi,j​ and their tableau products vt,vt∗v_t,v_t^*vt​,vt∗​ give the Murphy elements muv=vu∗mλvvm_{uv}=v_u^*m_\lambda v_vmuv​=vu∗​mλ​vv​. Lemma 2.3 asserts that they form a cellular basis. The cellular multiplication law computes a Gram form on each cell module CλC^\lambdaCλ. The determinant det⁡(λ)\det(\lambda)det(λ) is the determinant of this computed form in the Murphy basis; it is not assigned the desired closed product by definition. Enyang, Lemma 2.3 and §5

The Jucys–Murphy elements TkT_kTk​ form a commuting family in An(x)A_n(x)An​(x). Their triangular action on a tableau ttt has content rt(k)∈Rr_t(k)\in Rrt​(k)∈R. Over the fraction field F=Frac⁡(R)F=\operatorname{Frac}(R)F=Frac(R), the spectral product FtF_tFt​ produces a vector ft=mtFtf_t=m_tF_tft​=mt​Ft​. These vectors form an orthogonal basis, with squared norms ⟨ft,ft⟩\langle f_t,f_t\rangle⟨ft​,ft​⟩ whose product equals det⁡(λ)\det(\lambda)det(λ). The auxiliary polynomials are fixed by p0=0p_0=0p0​=0, p1=1p_1=1p1​=1 and pi+1=xpi−pi−1p_{i+1}=xp_i-p_{i-1}pi+1​=xpi​−pi−1​. Enyang, §§3–5

Formalization targets

The milestones follow the paper's own sequence: the Murphy cellular basis (Lemma 2.3) and the neighbour criterion for the elements vtv_tvt​ (Corollary 2.2); the basic properties of TiT_iTi​ and ziz_izi​ (Lemma 3.1), the sum identities for pip_ipi​ (Lemma 3.4), the action of ziz_izi​ on the generator of a cell module (Lemma 3.5), the triangular action of TkT_kTk​ and zkz_kzk​ with diagonals rt(k)r_t(k)rt​(k) and zt(k)=pipk−i+1z_t(k)=p_ip_{k-i+1}zt​(k)=pi​pk−i+1​ (Corollaries 3.6, 3.7) and the alternative recursion for Ti+1T_{i+1}Ti+1​ (Corollary 4.2); the seminormal basis (Lemma 4.4), the diagonal coefficients of eke_kek​ on it (Corollary 4.6) and the norm ratio of neighbouring seminormal vectors (Lemma 4.7); the identification of det⁡(λ)\det(\lambda)det(λ) with ∏t⟨ft,ft⟩\prod_t\langle f_t,f_t\rangle∏t​⟨ft​,ft​⟩ (§5) and the branching law (Lemma 5.1). The goal is Lemma 5.2, the closed product. When n>2fn>2fn>2f,

det⁡(f,n−2f)=∏i=1f(pn−2f+i+1pi)dim⁡(f−i,n−2f+2i).\det(f,n-2f)=\prod_{i=1}^{f}\left(\frac{p_{n-2f+i+1}}{p_i}\right)^{\dim(f-i,n-2f+2i)}.det(f,n−2f)=i=1∏f​(pi​pn−2f+i+1​​)dim(f−i,n−2f+2i).

When n=2fn=2fn=2f, the predecessor shape μ=(f−1,1)\mu=(f-1,1)μ=(f−1,1) lies at level n−1n-1n−1, and the target is

det⁡(f,0)=det⁡(μ)xdim⁡(f,0).\det(f,0)=\det(\mu)x^{\dim(f,0)}.det(f,0)=det(μ)xdim(f,0).

The quotient in the first formula is evaluated in FFF; the second equality is in RRR. Both clauses occur in the printed Lemma 5.2. Enyang, Lemma 5.2, p. 20

Significance

The result turns a determinant of a matrix indexed by all tableaux of a shape into a finite product of explicit recursive polynomials. It makes the factors that can vanish under specialization visible and lets later representation-theoretic questions be asked in terms of those factors. The branching law supplies a compatible description across levels of the algebra tower. Enyang, §5

The paper proves the formulas mathematically. The statements in this mission are compiled Lean targets with proof holes; they do not yet constitute machine-checked proofs of Enyang's results. A complete development would supply the cellular-basis theorem, establish the paper's explicit content action, connect the integral and field Gram forms, and prove the norm and determinant formulas. The quotient presentation, tableau encoding and cellular package can be reused for related specializations and diagram-algebra calculations.

Difficulty

The generator relations make local products manageable, but a determinant does not expose its factors directly. The cell module is indexed by whole paths, and the operators act triangularly rather than diagonally in the Murphy basis. Passing to seminormal vectors changes the basis while keeping track of the bilinear form; this requires the local coefficient and norm statements, not just the commutation of the operators. At the boundary n=2fn=2fn=2f, one of the two possible predecessor shapes disappears, so a uniform two-factor branching formula would introduce a nonexistent module. Enyang, §§3–5

Formalization scope

The Lean algebra is a quotient of a free algebra by all three defining relation families. It uses one-based generators; an out-of-range generator is set to zero, and every stated result guards its meaningful indices. Shapes are finite cup-count indices and tableaux are finite paths with a pointwise order. The unrolled products defining vtv_tvt​ and vt∗v_t^*vt∗​ follow the page's multiplication order. The integral statements use R=Z[x]R=\mathbb Z[x]R=Z[x]; seminormal vectors use F=Frac⁡(R)F=\operatorname{Frac}(R)F=Frac(R) and the published cellular-algebra package's coordinate-space cell module and Gram form. Existence of the required Murphy and JM data is asserted, preventing a theorem about an empty class of such data from passing vacuously.

Several printed details need explicit treatment. The page-2 endpoint e2f+1e_{2f+1}e2f+1​ in mλm_\lambdamλ​ is replaced by e2f−1e_{2f-1}e2f−1​, giving exactly fff factors and m(0,n)=1m_{(0,n)}=1m(0,n)​=1. The missing z0z_0z0​ is zero by the paper's sum formula. The rs(k)r_s(k)rs​(k) denominator in the definition of FtF_tFt​ means rt(k)r_t(k)rt​(k). Lemma 4.4(3) says “orthonormal,” but later nonunit norms show that the valid conclusion is pairwise orthogonality. The direction of ▹\triangleright▹ in the printed definition of gλ,μg_{\lambda,\mu}gλ,μ​ and Lemma 5.2 is reversed relative to the formula's denominator and the proof; the target product runs over shapes with fewer cups. Identity (3.3) of Lemma 3.4 is false as printed (at i=j=2i=j=2i=j=2, k=1k=1k=1 it reads x3−2x=xx^3-2x=xx3−2x=x); the target is the form its proof derives, with last factor pj+k−1p_{j+k-1}pj+k−1​. The goal and the cellular milestones take n≥1n\ge1n≥1, since the paper's tower starts at A1(x)=RA_1(x)=RA1​(x)=R; for n=0n=0n=0 the even case of Lemma 5.2 would refer to the non-existent shape (−1,1)(-1,1)(−1,1). Enyang, pp. 2, 10, 17, 19–20

Useful contributions include proofs of the algebraic Murphy-basis statement, the content formulas, the seminormal basis properties, the integral-to-field determinant identification and the branching law. Each has a separate mission item and source index.

Selected references

  • John Enyang, Representations of Temperley–Lieb Algebras, arXiv preprint arXiv:0710.3218v1, 2007. arXiv
  • Andrew Mathas, Seminormal forms and Gram determinants for cellular algebras, arXiv preprint arXiv:math/0604108v4, 2006. arXiv
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Dynamical SystemsMathematical PhysicsProbability+1·Captain: mikedeng1

Entropic Fluctuations in Statistical Mechanics I. Classical Dynamical Systems: Finite-Time Green–Kubo Formula and Onsager Reciprocity from the Generalized Evans–Searles SymmetryResearch Paper

Motivation

In a system driven away from equilibrium, a force changes a reference state and a dynamics, while a corresponding flux records the transported quantity. Statistical mechanics asks how the mean flux changes under a small force. A second question is whether the matrix of these changes is symmetric when the underlying dynamics admit time reversal. Jakšić, Pillet and Rey-Bellet derive both answers at a fixed, finite observation time from a generalized Evans–Searles fluctuation symmetry for classical dynamical systems in their 2010 preprint, §4. This finite-time statement does not require a large-time limit, a stationary nonequilibrium state, or an asymptotic fluctuation theorem.

The paper first develops the entropy cocycle and its time-reversal properties for a single system. Its Proposition 3.3 gives a scalar finite-time Evans–Searles identity. Section 4 lets the dynamics and reference state depend on a vector of forces and introduces a vector of fluxes. Proposition 4.6, the target here, is the section’s stated finite-time Green–Kubo and Onsager result Jakšić, Pillet and Rey-Bellet, pp. 18–21.

Setting

Fix a positive integer NNN and a measurable configuration space MMM. Each force vector X∈RNX\in\mathbb R^NX∈RN determines a continuous-time measurable flow ϕXs:M→M\phi_X^s:M\to MϕXs​:M→M, a probability state ωX\omega_XωX​, and an entropy-production observable σX\sigma_XσX​. The evolved states of each system are equivalent to ωX\omega_XωX​, and the regularity assumption (E1) makes σX\sigma_XσX​ the derivative of the evolved-state density in L1(ωX)L^1(\omega_X)L1(ωX​). The family also has a measurable flux vector ΦX=(ΦX(1),…,ΦX(N))\Phi_X=(\Phi_X^{(1)},\ldots,\Phi_X^{(N)})ΦX​=(ΦX(1)​,…,ΦX(N)​) satisfying the flux relation σX=X⋅ΦX\sigma_X=X\cdot\Phi_XσX​=X⋅ΦX​ almost everywhere. These are the family and flux conventions of §4.1 Jakšić, Pillet and Rey-Bellet, pp. 17–18.

At equilibrium, X=0X=0X=0. Assumption (T1) says only that ω0\omega_0ω0​ is invariant under ϕ0s\phi_0^sϕ0s​; no stationarity is imposed on ωX\omega_XωX​ for nonzero XXX. Assumption (T2) gives each XXX-system a possibly different time reversal ϑX\vartheta_XϑX​ preserving ωX\omega_XωX​, reversing the flow, and sending ΦX\Phi_XΦX​ to −ΦX-\Phi_X−ΦX​ almost everywhere. For t>0t>0t>0, the XXX-system time average is

⟨ΦX(j)⟩t=1t∫0tωX(ΦX(j)∘ϕXs) ds,\langle\Phi_X^{(j)}\rangle_t=\frac1t\int_0^t\omega_X(\Phi_X^{(j)}\circ\phi_X^s)\,ds,⟨ΦX(j)​⟩t​=t1​∫0t​ωX​(ΦX(j)​∘ϕXs​)ds,

and its force derivative at equilibrium is Ljkt=∂Xk⟨ΦX(j)⟩t∣X=0L_{jkt}=\left.\partial_{X_k}\langle\Phi_X^{(j)}\rangle_t\right|_{X=0}Ljkt​=∂Xk​​⟨ΦX(j)​⟩t​​X=0​. The equilibrium correlation with indices j,kj,kj,k is Cjk(s)=ω0(Φ0(k)(Φ0(j)∘ϕ0s))C_{jk}(s)=\omega_0(\Phi_0^{(k)}(\Phi_0^{(j)}\circ\phi_0^s))Cjk​(s)=ω0​(Φ0(k)​(Φ0(j)​∘ϕ0s​)). Thus the time-shifted factor carries index jjj.

The generalized Evans–Searles functional is the log-Laplace transform of the actual integrated flux,

gt(X,Y)=log⁡ωX ⁣(exp⁡[−Y⋅∫0tΦX∘ϕXs ds]),g_t(X,Y)=\log\omega_X\!\left(\exp\left[-Y\cdot\int_0^t\Phi_X\circ\phi_X^s\,ds\right]\right),gt​(X,Y)=logωX​(exp[−Y⋅∫0t​ΦX​∘ϕXs​ds]),

with extended real values when the exponential moment diverges. Proposition 4.3 states gt(X,Y)=gt(X,X−Y)g_t(X,Y)=g_t(X,X-Y)gt​(X,Y)=gt​(X,X−Y) under (T1)–(T2) Jakšić, Pillet and Rey-Bellet, p. 19.

Formalization targets

Generalized finite-time symmetry

Proposition 4.2 relates the law PXtP_X^tPXt​ of the averaged flux to its reflection PˉXt\bar P_X^tPˉXt​ for nonzero ttt: dPˉXt/dPXt(s)=e−tX⋅sd\bar P_X^t/dP_X^t(s)=e^{-tX\cdot s}dPˉXt​/dPXt​(s)=e−tX⋅s. Proposition 4.3 states the equivalent symmetry of gtg_tgt​. Lemma 4.4 is a calculus statement about a C1,2C^{1,2}C1,2 function with that symmetry. These are the three new numbered milestones; the earlier entropy-cocycle results, Propositions 3.1, 3.2 and 3.8, are reused as published references Jakšić, Pillet and Rey-Bellet, pp. 8–12, 19.

Finite-time response

The goal is all of Proposition 4.6, at each fixed t>0t>0t>0:

X↦⟨ΦX⟩t is differentiable at 0,Ljkt=12∫−ttCjk(s)(1−∣s∣t)ds,Ljkt=Lkjt.X\mapsto\langle\Phi_X\rangle_t\text{ is differentiable at }0,\qquad L_{jkt}=\frac12\int_{-t}^{t}C_{jk}(s)\left(1-\frac{|s|}{t}\right)ds,\qquad L_{jkt}=L_{kjt}.X↦⟨ΦX​⟩t​ is differentiable at 0,Ljkt​=21​∫−tt​Cjk​(s)(1−t∣s∣​)ds,Ljkt​=Lkjt​.

The first clause is the paper’s assumption (T3) as a conclusion. The second is the finite-time Green–Kubo formula and the third the finite-time Onsager reciprocity relation Jakšić, Pillet and Rey-Bellet, pp. 20–21.

Significance

The formula determines the first-order response matrix from correlations measured entirely in the equilibrium system. Its triangular weight records a finite observation window. Reciprocity then says that cross-responses agree after exchanging the flux and force coordinates. Both statements are exact at fixed time, so they can be used before an asymptotic transport coefficient is known to exist Jakšić, Pillet and Rey-Bellet, Proposition 4.6 and Remarks 1–2, pp. 20–21.

The paper proves these claims. The formalization task is to express and eventually verify the known result, including the dependent family of states and flows, the extended log moment, and all three clauses of the proposition. The published §3 definitions and cocycle statements provide a reusable base. A checked §4 development would also expose general measure and calculus lemmas for finite-time fluctuation relations. At drafting, these new statements compile as open Lean theorems; compilation does not supply their proofs.

Difficulty

The symmetry is an equality of potentially infinite log moments, while the response matrix uses real derivatives near the origin. Local finiteness must justify passage between those two regimes. The paper’s C1,2C^{1,2}C1,2 convention includes five families of continuous partial derivatives, including both orders of mixed differentiation, but does not demand two XXX derivatives. Treating it as ordinary C2C^2C2 would change the theorem.

There is also a measure-theoretic gap between a time integral of fluxes inside an expectation and an integral of expectations over time. A formal statement must control that interchange and the two-time correlation integral. Stationarity is available only at equilibrium, although both the state and flow vary with XXX in the response derivative. The one-line formula for ⟨f⟩t\langle f\rangle_t⟨f⟩t​ on p. 20 leaves its state implicit; the first display of the proof on p. 21 and the entropy balance used in (4.30) identify it as the XXX-system state for f=ΦXf=\Phi_Xf=ΦX​ Jakšić, Pillet and Rey-Bellet, pp. 20–21.

Formalization scope

The Lean family uses RN\mathbb R^NRN as Fin N → ℝ with N>0N>0N>0, a measurable type MMM, and one published RegularSystem M for each XXX. That type supplies (F1), (F2), (C), and (E1); the new family supplies the flux relation and almost-everywhere time integrability of each coordinate on finite intervals, so the paper's integrated flux is defined. Observable identities in the flux relation and time reversal are ωX\omega_XωX​-almost everywhere. The law PXtP_X^tPXt​ is the pushforward of ωX\omega_XωX​ under the integrated flux divided by ttt. The log-Laplace transform uses a nonnegative integral and EReal, retaining +∞+\infty+∞; a real conversion occurs only on a neighborhood where finiteness is stated.

The goal requires t>0t>0t>0, since its triangular kernel and time average refer to [0,t][0,t][0,t]. Proposition 4.2 requires t≠0t\ne0t=0 because PXtP_X^tPXt​ otherwise contains a division by zero; Proposition 4.3 includes t=0t=0t=0. To make the correlation and Fubini steps meaningful, equilibrium flux coordinates are assumed in L2(ω0)L^2(\omega_0)L2(ω0​) and the XXX-system flux is locally integrable on [0,t]×M[0,t]\times M[0,t]×M near X=0X=0X=0. These are labeled analytic hypotheses, not new physical symmetry assumptions. Coordinate partials are derivatives along coordinate lines, with existence as well as continuity asserted for the five families on an open neighborhood.

The target uses the actual log-Laplace transform and the force derivative of the actual time average. It imposes stationarity only at X=0X=0X=0, uses equilibrium correlations, and keeps precisely C1,2C^{1,2}C1,2 regularity. The family interface and the calculus and integration lemmas needed to prove the milestones are reusable; contributions that close any of the numbered milestones or the analytic interchange obligations fit this scope.

Selected references

  • V. Jakšić, C.-A. Pillet and L. Rey-Bellet, Entropic Fluctuations in Statistical Mechanics I. Classical Dynamical Systems, arXiv preprint arXiv:1009.3248v2, 2010. Preprint.
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Harmonic AnalysisRandom Matrix TheoryRepresentation Theory·Captain: mikedeng1

The Weingarten Calculus: Haar Integrals of Matrix Elements Are Given by a Basis of Invariant Tensors and Its Weingarten Matrix, I = A W A*Research Paper

Motivation

Integrals of polynomial functions of the matrix entries of a random element of a compact group appear across mathematical physics and probability: in random matrix theory (moments of Haar-distributed unitary, orthogonal and symplectic matrices), in lattice gauge theory (the link integrals of U(N)U(N)U(N) gauge fields), and in quantum information (averages of quantum channels over random unitaries, twirling, unitary designs). Weingarten first computed asymptotics of such integrals for U(N)U(N)U(N) in 1978 (Weingarten, J. Math. Phys. 19 (1978)); Collins (IMRN 2003) and Collins–Śniady (CMP 2006) gave exact formulas for the unitary, orthogonal and symplectic groups in terms of what is now called the Weingarten function.

The survey of Collins, Matsumoto and Novak, The Weingarten Calculus (arXiv:2109.14890), isolates the single statement underneath all these formulas, valid for every compact group and every finite-dimensional unitary representation. This mission formalizes that statement, Theorem 2.1 of the survey, together with the steps of its proof as written in Section 2.

Setting

Let GGG be a compact Hausdorff topological group and μ\muμ its Haar probability measure, the unique Borel probability measure on GGG invariant under left translation. Let H=CNH=\mathbb{C}^NH=CN with its standard orthonormal basis e1,…,eNe_1,\dots,e_Ne1​,…,eN​, and let U:G→U(N)U:G\to\mathrm U(N)U:G→U(N) be a continuous group homomorphism into the unitary N×NN\times NN×N matrices. Its matrix elements are Uxy(g)=⟨ex,U(g)ey⟩U_{xy}(g)=\langle e_x,U(g)e_y\rangleUxy​(g)=⟨ex​,U(g)ey​⟩, the (x,y)(x,y)(x,y) entry of U(g)U(g)U(g).

Fix d∈Nd\in\mathbb Nd∈N. A multi-index is a function i:[d]→[N]i:[d]\to[N]i:[d]→[N]; the set of them is Fun(d,N)\mathrm{Fun}(d,N)Fun(d,N). The Weingarten integrals of degree ddd are

Iij=∫G∏x=1dUi(x)j(x)(g) dμ(g),i,j∈Fun(d,N).I_{ij}=\int_G\prod_{x=1}^d U_{i(x)j(x)}(g)\,d\mu(g),\qquad i,j\in\mathrm{Fun}(d,N).Iij​=∫G​x=1∏d​Ui(x)j(x)​(g)dμ(g),i,j∈Fun(d,N).

The tensor power H⊗dH^{\otimes d}H⊗d has the orthonormal basis ei=ei(1)⊗⋯⊗ei(d)e_i=e_{i(1)}\otimes\cdots\otimes e_{i(d)}ei​=ei(1)​⊗⋯⊗ei(d)​, and the tensor-power matrix U⊗d(g)U^{\otimes d}(g)U⊗d(g) has entries Uij⊗d(g)=∏x=1dUi(x)j(x)(g)U^{\otimes d}_{ij}(g)=\prod_{x=1}^dU_{i(x)j(x)}(g)Uij⊗d​(g)=∏x=1d​Ui(x)j(x)​(g). The invariant tensors are

(H⊗d)G={t∈H⊗d:U⊗d(g) t=t for all g∈G},(H^{\otimes d})^G=\{t\in H^{\otimes d}: U^{\otimes d}(g)\,t=t\ \text{for all }g\in G\},(H⊗d)G={t∈H⊗d:U⊗d(g)t=t for all g∈G},

and the Haar average is the matrix P=∫GU⊗d(g) dμ(g)P=\int_GU^{\otimes d}(g)\,d\mu(g)P=∫G​U⊗d(g)dμ(g). Given vectors a1,…,am∈H⊗da_1,\dots,a_m\in H^{\otimes d}a1​,…,am​∈H⊗d, let A=[⟨ei,ax⟩]A=[\langle e_i,a_x\rangle]A=[⟨ei​,ax​⟩] be the Nd×mN^d\times mNd×m matrix whose columns are their coordinates, A∗A^*A∗ its conjugate transpose, A∗A=[⟨ax,ay⟩]A^*A=[\langle a_x,a_y\rangle]A∗A=[⟨ax​,ay​⟩] their Gram matrix, and, when it is invertible, W=(A∗A)−1W=(A^*A)^{-1}W=(A∗A)−1 the Weingarten matrix of a1,…,ama_1,\dots,a_ma1​,…,am​.

Formalization targets

Goal: Theorem 2.1 (p. 4)

If a1,…,ama_1,\dots,a_ma1​,…,am​ is a basis of (H⊗d)G(H^{\otimes d})^G(H⊗d)G, then for all i,j∈Fun(d,N)i,j\in\mathrm{Fun}(d,N)i,j∈Fun(d,N)

Iij=∑x,y=1mAix Wxy Ayj∗.I_{ij}=\sum_{x,y=1}^mA_{ix}\,W_{xy}\,A^*_{yj}.Iij​=x,y=1∑m​Aix​Wxy​Ayj∗​.

The identity is exact and holds for every compact group, every continuous unitary representation, every degree ddd and every choice of basis; nothing is fixed beyond the data.

Milestones (Section 2, pp. 3–4)

  1. Iij=PijI_{ij}=P_{ij}Iij​=Pij​: the Weingarten integrals are the matrix elements of the Haar average.
  2. P∗=PP^*=PP∗=P, P2=PP^2=PP2=P, and im⁡P=(H⊗d)G\operatorname{im}P=(H^{\otimes d})^GimP=(H⊗d)G: PPP is the orthogonal projection onto the invariant tensors (the existing platform theorem that a Haar average of a compact group representation is an idempotent fixing exactly the invariant vectors is included as a supporting reference item).
  3. For linearly independent columns, the selfadjoint idempotent with image span⁡{ax}\operatorname{span}\{a_x\}span{ax​} is A(A∗A)−1A∗A(A^*A)^{-1}A^*A(A∗A)−1A∗.

Significance

Theorem 2.1 reduces a family of analytic problems — Haar integrals of polynomials in matrix entries — to two algebraic ones: find a basis of the invariant tensors of GGG in H⊗dH^{\otimes d}H⊗d (classical invariant theory), and invert its Gram matrix. For U(N)U(N)U(N) the invariants come from Schur–Weyl duality and the Weingarten matrix becomes the Weingarten function on permutations; for O(N)O(N)O(N) and Sp(N)Sp(N)Sp(N) the invariants are indexed by pair partitions; for the symmetric group S(N)S(N)S(N) acting by permutation matrices the invariants are indicators of set partitions. Each of these case-specific formulas, surveyed in Sections 3–5 of the paper, is an instance of Theorem 2.1, so a formal proof of the theorem is the common entry point for formalizing any of them.

The theorem is classical and its proof is elementary once stated; it is not open. No machine-checked proof is known to exist in Mathlib or on this platform: Mathlib has Haar measure, unitary groups and Gram matrices (including the equivalence of linear independence with invertibility of the Gram matrix), but not the averaging projection of a representation in matrix form nor the formula A(A∗A)−1A∗A(A^*A)^{-1}A^*A(A∗A)−1A∗ for orthogonal projections. The mission produces both as reusable lemmas and the Fundamental Theorem itself.

Difficulty

The argument is short on paper; the formal work sits in three places. First, selfadjointness of PPP needs ∫GF(g−1) dμ=∫GF(g) dμ\int_GF(g^{-1})\,d\mu=\int_GF(g)\,d\mu∫G​F(g−1)dμ=∫G​F(g)dμ, i.e. unimodularity of a compact group, which Mathlib does not provide as an instance for non-commutative groups. Second, identifying the image of PPP with the invariant tensors needs both directions: invariant vectors are fixed by PPP, and every vector PtPtPt is invariant, which uses left invariance of μ\muμ inside a matrix-valued Bochner integral. Third, the projection formula needs invertibility of A∗AA^*AA∗A from linear independence and an argument that a selfadjoint idempotent is determined by its image. Commuting the integral with matrix entries and products is routine but must be done with care for the matrix norm chosen.

Formalization scope

  • HHH is CN\mathbb C^NCN with its standard basis (a finite-dimensional Hilbert space with a specified orthonormal basis is the same thing after identification); UUU is a monoid homomorphism G →* Matrix.unitaryGroup (Fin N) ℂ, assumed continuous. Indices are 0-based: [N][N][N] is Fin N, multi-indices are Fin d → Fin N, tensors are (Fin d → Fin N) → ℂ.
  • GGG carries [IsTopologicalGroup G] [CompactSpace G] [T2Space G] [BorelSpace G], and μ\muμ is a Haar measure that is a probability measure. Right invariance is not assumed; it is a consequence that solvers must prove.
  • ddd ranges over all of N\mathbb NN, including d=0d=0d=0, where both sides equal 111; the paper takes ddd positive.
  • The inner product is conjugate-linear in the first slot, so Ayj∗=Ajy‾A^*_{yj}=\overline{A_{jy}}Ayj∗​=Ajy​​ and A∗A^*A∗ is Mathlib's conjugate transpose.
  • PPP is a Bochner integral of matrices, taken with the entrywise sup norm; in finite dimension the integral is independent of the norm.
  • The basis hypothesis is two hypotheses: LinearIndependent ℂ a and span (range a) = invariants U d, with the invariant subspace defined from the representation. Without independence Mathlib's matrix inverse returns 000 on a singular Gram matrix, and the statement would be false; it is therefore not a trivializing gap but a necessary hypothesis.
  • Correction. The paper says "a basis a1,…,ama_1,\dots,a_ma1​,…,am​ of (H)⊗d(H)^{\otimes d}(H)⊗d"; the same paragraph calls the axa_xax​ "the basic invariants", and with a basis of all of H⊗dH^{\otimes d}H⊗d the right-hand side would be the identity. The formal statement uses a basis of (H⊗d)G(H^{\otimes d})^G(H⊗d)G.
  • A trivializing formalization — defining the Weingarten integral as AWA∗AWA^*AWA∗, defining the invariant space as the image of PPP, or assuming that PPP projects onto the span of the axa_xax​ — is excluded: the left side is the Haar integral of the product of matrix elements written out, and the invariant space is defined by U⊗d(g)t=tU^{\otimes d}(g)t=tU⊗d(g)t=t.

Needed infrastructure: matrix-valued Bochner integrals commuting with entries and with matrix multiplication; unimodularity of compact groups; the orthogonal-projection formula. All three are reusable well beyond this mission, and contributions of these general lemmas are welcome.

Selected references

  • B. Collins, S. Matsumoto, J. Novak, The Weingarten Calculus, arXiv preprint, 2021. https://arxiv.org/abs/2109.14890
  • D. Weingarten, Asymptotic behavior of group integrals in the limit of infinite rank, J. Math. Phys. 19 (1978), 999–1001. https://doi.org/10.1063/1.523807
  • B. Collins, Moments and cumulants of polynomial random variables on unitary groups, the Itzykson–Zuber integral, and free probability, Int. Math. Res. Not. 2003, no. 17, 953–982. https://doi.org/10.1155/S107379280320917X
  • B. Collins, P. Śniady, Integration with respect to the Haar measure on unitary, orthogonal and symplectic group, Comm. Math. Phys. 264 (2006), 773–795. https://doi.org/10.1007/s00220-006-1554-3
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CombinatoricsGraph TheoryMachine Learning·Captain: mikedeng1

Geometric Deep Learning IX: Message-Passing GNNs Are No More Powerful Than the Weisfeiler–Lehman Test — Equal Colour Histograms Force Equal OutputsTextbook

Motivation

Graph neural networks (GNNs) compute representations of nodes and whole graphs by repeatedly combining each node's state with information from its neighbours. Soon after they became a standard tool, the question arose of what they cannot do. A natural test case is graph isomorphism: given two graphs that are not isomorphic, can the network attach different representations to them? If it cannot, it is hopeless on any task that needs to tell the two graphs apart.

The yardstick for this question is the Weisfeiler–Lehman (WL) test (Weisfeiler and Leman, 1968), a colour-refinement procedure that is a necessary condition for isomorphism. Bronstein, Bruna, Cohen and Veličković's Geometric Deep Learning (arXiv:2104.13478v2) reports, in its historical chapter (Ch. 7, p. 120), the conclusion of Morris et al. (2019) and Xu et al. (2019): any GNN of the three flavours of §5.3 "cannot be more powerful than the WL test". This mission formalizes that claim, together with the surrounding remarks of the book that make it precise.

Timeline. 1968: Weisfeiler and Leman introduce the refinement. 2011: Shervashidze et al. use the WL iteration to build graph kernels. 2017: Gilmer et al. unify many architectures as message-passing neural networks. 2019: Morris et al. and Xu et al. independently prove that message-passing GNNs are bounded by 1-WL, and that injective aggregation attains the bound (the Graph Isomorphism Network). 2020: Corso et al. show that with continuous features injective aggregation needs several aggregators.

Setting

A graph GGG has node set V={0,…,n−1}V = \{0, \dots, n-1\}V={0,…,n−1} and a symmetric, loopless adjacency relation. The neighbourhood of a node is Nu={v:(u,v)∈E}\mathcal N_u = \{v : (u, v) \in E\}Nu​={v:(u,v)∈E} (eq. (11), p. 34); it does not contain uuu.

The WL colour refinement on a featureless graph starts with the same colour c0(u)c^0(u)c0(u) for every node and sets

cs+1(u)=(cs(u),{ ⁣{cs(v):v∈Nu} ⁣}),c^{s+1}(u) = \big(c^s(u), \{\!\{c^s(v) : v \in \mathcal N_u\}\!\}\big),cs+1(u)=(cs(u),{{cs(v):v∈Nu​}}),

where { ⁣{⋅} ⁣}\{\!\{\cdot\}\!\}{{⋅}} is a multiset. Colours carry their full history, so colours of nodes of two different graphs can be compared directly. The colour histogram at round sss is the multiset { ⁣{cs(u):u∈V} ⁣}\{\!\{c^s(u) : u \in V\}\!\}{{cs(u):u∈V}}. The WL test declares two graphs indistinguishable when their histograms agree at every round.

A message-passing layer (eq. (35), p. 79) has a message function ψ\psiψ, a permutation-invariant aggregator ⨁\bigoplus⨁ and an update ϕ\phiϕ, and updates node features hhh by

hu←ϕ(hu,⨁v∈Nuψ(hu,hv)).h_u \leftarrow \phi\Big(h_u, \bigoplus_{v \in \mathcal N_u} \psi(h_u, h_v)\Big).hu​←ϕ(hu​,v∈Nu​⨁​ψ(hu​,hv​)).

A GNN starts from a constant feature hu0=ch^0_u = chu0​=c and applies layers t=0,1,…t = 0, 1, \dotst=0,1,…, with parameters (ψt,⨁t,ϕt)(\psi_t, \bigoplus_t, \phi_t)(ψt​,⨁t​,ϕt​) shared by all graphs. Its graph-level output after TTT rounds is a read-out of the multiset { ⁣{huT:u∈V} ⁣}\{\!\{h^T_u : u \in V\}\!\}{{huT​:u∈V}}.

Formalization targets

Goal: GNNs are bounded by WL

For every GNN, read-out, depth TTT and pair of graphs GGG, G′G'G′ (of possibly different sizes):

cGt(u)=cG′t(v)  ⟹  hGt(u)=hG′t(v)(t≤T),c^t_G(u) = c^t_{G'}(v) \implies h^t_G(u) = h^t_{G'}(v) \quad (t \le T),cGt​(u)=cG′t​(v)⟹hGt​(u)=hG′t​(v)(t≤T), { ⁣{cGT(u)} ⁣}u={ ⁣{cG′T(v)} ⁣}v  ⟹  readout({ ⁣{hGT(u)} ⁣}u)=readout({ ⁣{hG′T(v)} ⁣}v).\{\!\{c^T_G(u)\}\!\}_u = \{\!\{c^T_{G'}(v)\}\!\}_v \implies \mathrm{readout}\big(\{\!\{h^T_G(u)\}\!\}_u\big) = \mathrm{readout}\big(\{\!\{h^T_{G'}(v)\}\!\}_v\big).{{cGT​(u)}}u​={{cG′T​(v)}}v​⟹readout({{hGT​(u)}}u​)=readout({{hG′T​(v)}}v​).

The statement fixes no architecture and no feature space: it quantifies over all message, aggregation, update and read-out functions.

Milestones

  1. Injective ϕ\phiϕ is one WL step (§4.1, p. 34): for the local layer hu↦ϕ(hu,{ ⁣{hv:v∈Nu} ⁣})h_u \mapsto \phi(h_u, \{\!\{h_v : v \in \mathcal N_u\}\!\})hu​↦ϕ(hu​,{{hv​:v∈Nu​}}) with ϕ\phiϕ injective, if equal features are exactly equal round-sss colours, then equal new features are exactly equal round-(s+1)(s+1)(s+1) colours.
  2. Isomorphic graphs (side-note p. 119): a GNN attaches identical representations to isomorphic graphs.
  3. C6C_6C6​ versus 2K32K_32K3​ (side-note p. 120): the 6-cycle and two disjoint triangles have equal WL histograms at every round but are not isomorphic.
  4. Max and mean (side-note p. 120): the multisets { ⁣{a,b} ⁣}\{\!\{a, b\}\!\}{{a,b}} and { ⁣{a,a,b,b} ⁣}\{\!\{a, a, b, b\}\!\}{{a,a,b,b}} differ but have the same maximum and the same mean.

Companion: reaching the bound

If every layer's update (x,S)↦ϕt(x,⨁y∈Sψt(x,y))(x, S) \mapsto \phi_t(x, \bigoplus_{y \in S} \psi_t(x, y))(x,S)↦ϕt​(x,⨁y∈S​ψt​(x,y)) is injective, then equal features are exactly equal WL colours (Xu et al.).

Significance

The result. The bound says that a GNN's ability to separate graphs is capped by a cheap combinatorial procedure. Every pair of non-isomorphic graphs that WL fails to separate — all regular graphs of the same degree and size, such as C6C_6C6​ and 2K32K_32K3​ — is also inseparable by every message-passing GNN, whatever its width, depth or training. This limitation motivated the higher-order and subgraph-based architectures discussed later in Ch. 7. The companion result explains why architectures with injective (sum-type) aggregation, such as GIN, are the maximally expressive members of the class, and the max/mean example explains why common aggregators fall short of it.

Formalizing it. The results are proved on paper; to the knowledge of this mission none has a machine-checked proof. The formalization makes explicit what the informal statements leave open: that the comparison needs parameters shared across graphs, that it concerns featureless graphs, which flavour of layer is covered, and in what sense "equivalent to one step" holds. It reuses a published 1-WL colour refinement (WLIdentification), so the GNN results connect to the platform's existing WL statements.

Difficulty

The statements are close to their definitions, and the difficulty is in the bookkeeping rather than in an idea. The comparison is between two different graphs, whose node sets are different types, so the relation between features and colours has to be carried across graphs rather than within one; equalities of colour multisets over neighbourhoods have to become equalities of multisets of messages, and histograms of colours have to become multisets of features. The C6C_6C6​ / 2K32K_32K3​ example needs the colours of a regular graph at every round and a separate non-isomorphism argument. A tempting shortcut, defining the GNN's features to be the WL colours, proves nothing: the goal quantifies over all GNNs.

Formalization scope

Graphs are the published OAI.WLIdentification.Graph (order nnn, Boolean symmetric loopless adjacency on Fin n); the WL test is its neighborColor and neighborHistogram, featureless and with history-carrying colours. The book numbers no theorems, so every item is cited by section, equation and printed page.

Conventions committed to:

  • Featureless graphs. The GNN's initial features are a constant, matching the featureless WL refinement (the WL analyses "almost always consider featureless or categorically-featured graphs", side-note p. 120). The featured version is not stated.
  • The message-passing flavour. The goal is posed for layers (35). It covers the attentional flavour (34) and the convolutional flavour (33) when the coefficient cuvc_{uv}cuv​ is a function of the features of uuu and vvv. A coefficient that is an arbitrary function of the graph is outside the claim; with cuvc_{uv}cuv​ the number of triangles through uuu, a convolutional layer separates C6C_6C6​ from 2K32K_32K3​.
  • Shared parameters. One GNN is evaluated on both graphs. A formalization in which each graph receives its own parameters would be trivially satisfiable and is ruled out.
  • Aggregation on multisets. The aggregator is a function of the multiset of messages, so permutation invariance holds by construction; message, aggregate and feature types are arbitrary types.
  • Neighbourhoods exclude the node itself; the node's own state enters through the first argument of ϕ\phiϕ.
  • The page's slips. The WL test is described (p. 120) as "randomly hashing their sums"; the refinement used hashes the multiset injectively. "With summation being a key representative" is not formalized: on real features summation is not injective on multisets, and Xu et al.'s result uses a chosen feature embedding.

Infrastructure needed is light: multiset bijections along equal maps (Multiset.map), induction over rounds, and finite computations on six-node graphs. The induction lemmas relating features to colours across two graphs are reusable for any further GNN-expressivity statement (higher-order WL, subgraph GNNs). Proofs of the milestones, of the companion, and alternative proofs of the goal through the companion are welcome.

Selected references

  • M. M. Bronstein, J. Bruna, T. Cohen, P. Veličković, Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges, arXiv preprint, 2021. https://arxiv.org/abs/2104.13478v2
  • B. Weisfeiler, A. Leman, The reduction of a graph to canonical form and the algebra which appears therein, Nauchno-Technicheskaya Informatsia, 1968 (English translation). https://www.iti.zcu.cz/wl2018/pdf/wl_paper_translation.pdf
  • K. Xu, W. Hu, J. Leskovec, S. Jegelka, How Powerful are Graph Neural Networks?, ICLR, 2019. https://arxiv.org/abs/1810.00826
  • C. Morris, M. Ritzert, M. Fey, W. L. Hamilton, J. E. Lenssen, G. Rattan, M. Grohe, Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks, AAAI, 2019. https://arxiv.org/abs/1810.02244
  • J. Gilmer, S. S. Schoenholz, P. F. Riley, O. Vinyals, G. E. Dahl, Neural Message Passing for Quantum Chemistry, ICML, 2017. https://arxiv.org/abs/1704.01212
  • N. Shervashidze, P. Schweitzer, E. J. van Leeuwen, K. Mehlhorn, K. M. Borgwardt, Weisfeiler-Lehman Graph Kernels, JMLR 12, 2011. https://www.jmlr.org/papers/v12/shervashidze11a.html
  • G. Corso, L. Cavalleri, D. Beaini, P. Liò, P. Veličković, Principal Neighbourhood Aggregation for Graph Nets, NeurIPS, 2020. https://arxiv.org/abs/2004.05718
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