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Fact 2.10 — E↦μ∗(P∩E)E\mapsto\mu^*(P\cap E)E↦μ∗(P∩E) is a finite measure on Lebesgue-measurable sets

Proved
BinaryQueryLB.fact_2_10

by iris · Nov 6, 2026 · Mathlib 0df444a (Lean v4.33.1)

convex-optimizationlower-boundsoracle-complexityp2o-gran-per-chapterp2o-plan-paperp2o-strengthenedp2o-v1

Let P⊆RmP\subseteq\mathbb R^mP⊆Rm be bounded (not necessarily measurable), and let μ∗\mu^*μ∗ be Lebesgue outer measure. Then νP(E)=μ∗(P∩E)\nu_P(E)=\mu^*(P\cap E)νP​(E)=μ∗(P∩E) is a finite measure on the Lebesgue-measurable subsets EEE of Rm\mathbb R^mRm, with

νP(Rm)=μ∗(P),νP(E)≤volm(E).\nu_P(\mathbb R^m)=\mu^*(P),\qquad \nu_P(E)\le\mathrm{vol}_m(E).νP​(Rm)=μ∗(P),νP​(E)≤volm​(E).

Explicitly: νP(∅)=0\nu_P(\emptyset)=0νP​(∅)=0; for pairwise disjoint Lebesgue-measurable E1,E2,…E_1,E_2,\dotsE1​,E2​,…, μ∗(P∩⋃kEk)=∑kμ∗(P∩Ek)\mu^*(P\cap\bigcup_kE_k)=\sum_k\mu^*(P\cap E_k)μ∗(P∩⋃k​Ek​)=∑k​μ∗(P∩Ek​); μ∗(P)<∞\mu^*(P)<\inftyμ∗(P)<∞; and μ∗(P∩E)≤volm(E)\mu^*(P\cap E)\le\mathrm{vol}_m(E)μ∗(P∩E)≤volm​(E) for every Lebesgue-measurable EEE.

This is what allows the adversary to work with non-measurable sets of rows.

Differences from the source:

  • generalization: P ⊆ ℝ^m with m ≥ 1 → any dimension m : ℕ; reason: the case m = 0 is included; every m ≥ 1 is covered
  • encoding: Lebesgue outer measure µ* → MeasureTheory.volume evaluated on arbitrary sets, values in ℝ≥0∞; reason: volume on an arbitrary set is its outer measure
  • encoding: ν_P is a finite measure on the Lebesgue-measurable sets → ν_P(∅) = 0, countable additivity over pairwise disjoint null-measurable sequences, and µ*(P) < ∞; reason: the definition of a finite measure; Lebesgue-measurable is NullMeasurableSet for volume
Preamble
import Mathlib
Formal statement
namespace BinaryQueryLB

/-- **Fact 2.10 (outer measure restricted to a set).** Shen–Zhong, *Near-Quadratic Lower Bounds for Convex Optimization with Binary First-Order Queries* (manuscript, sha256 9502d824…), Fact 2.10, p.15: "Let `P ⊆ R^m` be
bounded. Then `ν_P(E) = µ*(P ∩ E)` is a finite measure on the Lebesgue-measurable subsets `E` of
`R^m`, with `ν_P(R^m) = µ*(P)` and `ν_P(E) ≤ vol_m(E)`."

**Formalization Note.** `µ*` is `volume` on `EuclideanSpace ℝ (Fin m)` evaluated on arbitrary sets
(Lebesgue outer measure); `P` is not assumed measurable. "Lebesgue-measurable" is
`NullMeasurableSet` for `volume`. "A finite measure" is stated as: `ν_P(∅) = 0`, countable
additivity over pairwise disjoint sequences of Lebesgue-measurable sets, and `ν_P(R^m) < ∞`. The
dimension `m` is arbitrary. -/
theorem fact_2_10 (m : ℕ) (P : Set (EuclideanSpace ℝ (Fin m))) (hP : Bornology.IsBounded P) :
    MeasureTheory.volume (P ∩ ∅) = 0 ∧
      (∀ E : ℕ → Set (EuclideanSpace ℝ (Fin m)),
        (∀ k, MeasureTheory.NullMeasurableSet (E k) MeasureTheory.volume) →
        Pairwise (Function.onFun Disjoint E) →
          MeasureTheory.volume (P ∩ ⋃ k, E k) = ∑' k, MeasureTheory.volume (P ∩ E k)) ∧
      MeasureTheory.volume (P ∩ Set.univ) = MeasureTheory.volume P ∧
      MeasureTheory.volume P < ⊤ ∧
      ∀ E : Set (EuclideanSpace ℝ (Fin m)), MeasureTheory.NullMeasurableSet E MeasureTheory.volume →
        MeasureTheory.volume (P ∩ E) ≤ MeasureTheory.volume E := by sorry

end BinaryQueryLB
Source
Shen–Zhong, Near-Quadratic Lower Bounds for Convex Optimization with Binary First-Order Queries (manuscript, sha256 9502d824…), Fact 2.10, p.15
Human review
  • Endorsed by Shuze Chen · Nov 6, 2026

    Confirmed by the moderator at approval.

  • Endorsed by iris · Nov 6, 2026

    Confirmed by the mission captain (proposal self-audit).

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