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OAI.IndependentProducts.main_gaussian_24

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by wurtle · Oct 7, 2026 · Mathlib 0df444a (Lean v4.33.1)

The theorem states that, for every real t>0, a lower bound holds for the averaged asymptotic midpoint modulus of a particular L1 span, and that the bound is strictly positive. The space is built from the tree of finite sequences of positive integers: one independent coordinate is attached to each nonroot vertex, each distributed as the law of the square of a standard real Gaussian (the pushforward of N(0,1) under x ↦ x²), and the infinite product measure is taken on the resulting sample space. The path product of a vertex multiplies the coordinates along the nonroot prefixes of its path, with the root giving the empty product 1. The space is the closed real linear span, inside L1 of the product measure, of all path products, equipped with its L1 norm. The averaged midpoint modulus at t takes the infimum over unit vectors x of the supremum, over closed finite-codimension subspaces F, of the infimum over y in F with norm at least 1 of (‖x+ty‖+‖x−ty‖)/2 − 1. With g(r) denoting the probability that a standard Gaussian satisfies |Z| ≥ r, the theorem asserts that this modulus is at least g(4√2(2+√2)/t)/8, and that g(4√2(2+√2)/t)/8 is greater than 0. The statement itself does not assume the multiplier-law hypotheses; the proof is admitted rather than verified here.

Preamble
-- Generated from openai/math @ adc7f1241b42e322a6451854ab7e4b4c146bf78a
-- Source: lean/ComparatorChallenges/IndependentProducts.lean; bytes 4071..4395
-- Kind: theorem; original declaration names and bodies preserved.
-- Source groups are independent. Target: Lean 4.33.1; see compilation.json.

import Mathlib
import Definitions.Def_IndependentProducts

namespace OAI

noncomputable section

open MeasureTheory ProbabilityTheory Set Filter

open scoped ENNReal NNReal Topology

universe uX

namespace IndependentProducts

variable (X : Type uX) [NormedAddCommGroup X] [NormedSpace ℝ X]

Formal statement
theorem main_gaussian_24 (t : ℝ) (ht : 0 < t) :
    gaussianTail (4 * Real.sqrt 2 * (2 + Real.sqrt 2) / t) / 8 ≤
      averagedMidpointModulus (productSpan gaussianSquareLaw)
        (normSeminorm ℝ (productSpan gaussianSquareLaw)) t ∧
    0 < gaussianTail (4 * Real.sqrt 2 * (2 + Real.sqrt 2) / t) / 8 := by
  sorry

end IndependentProducts
end
end OAI
Source
https://github.com/openai/math/blob/adc7f1241b42e322a6451854ab7e4b4c146bf78a/lean/ComparatorChallenges/IndependentProducts.lean
Human review
  • Endorsed by Community (Bot) · Oct 7, 2026

    Confirmed by the moderator at approval.

  • Endorsed by marwahaha · Oct 7, 2026

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

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