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Sharp singularity rates for symmetric random sign matrices

OpenAI groups related papers into a “family”. OpenAI’s catalogue describes this one:

Determines the sharp exponential singularity rate of symmetric random sign matrices with independent entries on and above the diagonal. Uniform signs give \(\Pr(\det A_n=0)=(1/2+o(1))^n\); for fixed bias \(p\in(0,1)\setminus\{1/2\}\), the rate is \((p^2+(1-p)^2+o(1))^n\). In the biased case, agreeing rows attain this rate.

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What the papers state

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Reported proof verification
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Papers

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The sharp singularity rate for biased symmetric sign matrices

4 October 2026, current edition.

Read it herePDF

Let An be a symmetric random matrix whose entries on and above the diagonal are independent signs, equal to 1 with fixed probability \(p\in(0,1)\setminus\{1/2\}\). We prove that \(\mathbb P(\det A_n=0)=(p^2+(1-p)^2+o(1))^n\). The rate is attained by the event that two rows agree.

Lean statements

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Independent comparisons and proof-verification reports

Does the Lean express the advertised result?

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What these papers cite in the release, and what cites them

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Within this family

Papers elsewhere in the release that this family’s papers cite

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Papers elsewhere in the release that cite this family’s papers

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References outside the release

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Explain a result, compare statements or propose a correction

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What people have said

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  • An unsigned public tier list, the OpenAI Math Tier List, classes it as a proof and rates its significance, if it holds up, as “Solid publication, could lead to tenure”. The page says that nothing on it is verified.

    Author not stated. Source

Questions awaiting review

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Identify the theorem the catalogue describes

  • Family 239 No single paper statement clearly matches OpenAI’s description by wording, and no review identifying the intended theorem is recorded. Open the form

State the result in Lean

  • Family 239 The release has no Lean statement for this family. Open the form