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	<id>https://openai-aftermath.mathnt.net/index.php?action=history&amp;feed=atom&amp;title=Equality_of_microstates_and_nonmicrostates_free_entropy</id>
	<title>Equality of microstates and nonmicrostates free entropy - Revision history</title>
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	<updated>2026-10-23T23:08:30Z</updated>
	<subtitle>Revision history for this page on the wiki</subtitle>
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		<id>https://openai-aftermath.mathnt.net/index.php?title=Equality_of_microstates_and_nonmicrostates_free_entropy&amp;diff=708&amp;oldid=prev</id>
		<title>Aftermath bot: New pages on the generalized Mukai conjecture and on free entropy</title>
		<link rel="alternate" type="text/html" href="https://openai-aftermath.mathnt.net/index.php?title=Equality_of_microstates_and_nonmicrostates_free_entropy&amp;diff=708&amp;oldid=prev"/>
		<updated>2026-10-21T07:08:52Z</updated>

		<summary type="html">&lt;p&gt;New pages on the generalized Mukai conjecture and on free entropy&lt;/p&gt;
&lt;p&gt;&lt;b&gt;New page&lt;/b&gt;&lt;/p&gt;&lt;div&gt;Voiculescu defined two &amp;#039;&amp;#039;&amp;#039;free entropies&amp;#039;&amp;#039;&amp;#039; for a tuple of self-adjoint operators in a tracial von Neumann algebra: the microstates entropy χ, from the volumes of matrix tuples approximating the joint moments, and the nonmicrostates entropy χ*, from free Fisher information along the addition of free semicircular noise. Whether χ = χ* whenever χ is finite was part of his unification problem. A manuscript dated 25 September 2026 in OpenAI&amp;#039;s public mathematics collection ([https://github.com/openai/math github.com/openai/math]) claims a tuple for which both are finite and differ, with a Lean formalization of the main theorem. This page summarizes the published claim and lists publicly available follow-up work. Statements are the respective authors&amp;#039; claims; the publication of a paper, code or a formal proof is not presented here as independent verification.&lt;br /&gt;
&lt;br /&gt;
== Background ==&lt;br /&gt;
* As recounted in the introduction of the manuscript:&lt;br /&gt;
** The two entropies agree for a single variable, and their agreement for general tuples was one of the questions in Voiculescu&amp;#039;s unification problem. Guionnet stated the finite-entropy formulation as a conjecture; Jekel and Pi discussed nonapproximable laws with χ = −∞ &amp;amp;lt; χ*.&lt;br /&gt;
** Biane, Capitaine and Guionnet proved χ ≤ χ* in general, and Jekel and Pi gave an elementary proof through classical entropy and Fisher information. Equality is known in regular convex settings, by Dabrowski for a class of strictly convex potentials and by Jekel for convex matrix potentials with suitable regularity.&lt;br /&gt;
&lt;br /&gt;
== The original result ==&lt;br /&gt;
* &amp;#039;&amp;#039;&amp;#039;Claim.&amp;#039;&amp;#039;&amp;#039; Theorem 1.1 of &amp;#039;&amp;#039;A finite-entropy separation of microstates and nonmicrostates free entropy&amp;#039;&amp;#039; states that there are an integer &amp;#039;&amp;#039;n&amp;#039;&amp;#039; ≥ 2 and a bounded self-adjoint tuple &amp;#039;&amp;#039;X&amp;#039;&amp;#039; in a von Neumann algebra with faithful normal tracial state such that −∞ &amp;amp;lt; χ(&amp;#039;&amp;#039;X&amp;#039;&amp;#039;) ≤ χ*(&amp;#039;&amp;#039;X&amp;#039;&amp;#039;) − 1/2 &amp;amp;lt; ∞, where χ uses an operator-norm cutoff and a limsup over matrix sizes. The number of variables is large but fixed; the manuscript does not address smaller prescribed numbers of variables.&lt;br /&gt;
* &amp;#039;&amp;#039;Method, as described:&amp;#039;&amp;#039; the tuple is a small free semicircular perturbation of free semicircular variables together with a commuting variable uniformly distributed on equally spaced points. After further noise, a cumulant estimate brings χ* close to that of a semicircular family, while matrix microstates keep a detectable block structure that independent GUE matrices lack; the classical-to-free Fisher comparison of Jekel and Pi transfers the resulting deficit between the scales.&lt;br /&gt;
* &amp;#039;&amp;#039;&amp;#039;Sources.&amp;#039;&amp;#039;&amp;#039; The manuscript [https://github.com/openai/math/tree/1581d4cbdd69a0faf34b2089614fe2a814316a6a/preprints/A-finite-entropy-separation-of-microstates-and-nonmicrostates-free-entropy-September-25-2026 A finite-entropy separation of microstates and nonmicrostates free entropy] at commit &amp;lt;code&amp;gt;1581d4c&amp;lt;/code&amp;gt;.&lt;br /&gt;
* &amp;#039;&amp;#039;&amp;#039;Formalization, as described by the repository.&amp;#039;&amp;#039;&amp;#039; The [https://github.com/openai/math/blob/1581d4cbdd69a0faf34b2089614fe2a814316a6a/lean/docs/298.md scope note] states that the formalization disproves equality of the two entropies even when both are finite, constructing a bounded self-adjoint tuple with −∞ &amp;amp;lt; χ(&amp;#039;&amp;#039;X&amp;#039;&amp;#039;) ≤ χ*(&amp;#039;&amp;#039;X&amp;#039;&amp;#039;) − 1/2 &amp;amp;lt; ∞ for a fixed finite number of variables. The Comparator statement is &amp;lt;code&amp;gt;FiniteEntropySeparation.lean&amp;lt;/code&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
== Public follow-up work ==&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
! Date !! Work !! Relation !! Public claim !! Public status (checked 21 October 2026)&lt;br /&gt;
|-&lt;br /&gt;
| 2026-10-08 || [https://github.com/mathvet/mathvet MathVet] (GitHub; review of openai/math, tables at repository commit &amp;lt;code&amp;gt;c76f1e4&amp;lt;/code&amp;gt;, 14 October 2026) || Review (fidelity of the formal statement) || Rates the family &amp;quot;full&amp;quot;; lists the hand-written definitions of the microstates entropy with cutoff, free Fisher information and the nonmicrostates entropy among the definitions to check, and records a sandboxed Comparator pass for &amp;lt;code&amp;gt;FiniteEntropySeparation&amp;lt;/code&amp;gt;. || MathVet states that it does not claim any theorem false and reports what was machine-checked as stated.&lt;br /&gt;
|-&lt;br /&gt;
| 2026-10-10 || cert-machine, openai/math lane K: run [https://github.com/carlostoledo1891/cert-machine/blob/910dddee72220b30c85da00fc414b6c987f8c954/corpus/openai-math/kernel-runs/38051470892/FiniteEntropySeparation.json 38051470892] || Verification (two kernels) || Records that Lean&amp;#039;s default kernel and the nanoda kernel accept the &amp;lt;code&amp;gt;FiniteEntropySeparation&amp;lt;/code&amp;gt; solution, in 997 s. || Repository.&lt;br /&gt;
|-&lt;br /&gt;
| 2026-10-10 to 2026-10-14 || [https://github.com/leanprover/con-leche/blob/90577d9e49ee3aed45da3d421bdf5dc780192304/DESIGN.md con-leche development journal] (task #348) || Verification (second kernel) || In its run over all Comparator challenges of the collection at commit &amp;lt;code&amp;gt;fd4aeeb&amp;lt;/code&amp;gt;, the journal&amp;#039;s table of exceptions (time-outs, memory, errors) does not list &amp;lt;code&amp;gt;FiniteEntropySeparation&amp;lt;/code&amp;gt;, so it was accepted by con-leche and by Lean&amp;#039;s official kernel. || Development journal.&lt;br /&gt;
|-&lt;br /&gt;
| 2026-10-16&lt;br /&gt;
| J. Jardine, Lattice24, referee review [https://github.com/JJardine919/openai-math-audit/blob/a06a8c6e77974d4c6021338a55a8e91b634f67f7/reviews/rank_519.json rank_519] in [https://github.com/JJardine919/openai-math-audit JJardine919/openai-math-audit] (archived at [https://doi.org/10.5281/zenodo.23422995 Zenodo 10.5281/zenodo.23422995])&lt;br /&gt;
| Review (AI-assisted audit)&lt;br /&gt;
| Reports no gap. The reviewer read all six sections and checked the normalizations of both entropies, the free-flow identity, the Wick-testing lemma, the cumulant and sparsity bounds, the explicit parameters, the finite-time flow lemma and the matrix block estimate.&lt;br /&gt;
| Part of an audit that the audit describes as complete. The reviews are published under CC BY 4.0.&lt;br /&gt;
|-&lt;br /&gt;
| 2026-10-21 (listed) || D. Jekel, &amp;#039;&amp;#039;On counterexamples to the unification of free entropy&amp;#039;&amp;#039; ([https://arxiv.org/abs/2610.27243 arXiv:2610.27243]) || Extension (exposition; Fisher information) || Describes OpenAI&amp;#039;s manuscript as the first example with −∞ &amp;amp;lt; χ &amp;amp;lt; χ*, gives a detailed presentation of a similar example, and shows explicitly the separation between free Fisher information and the large-&amp;#039;&amp;#039;n&amp;#039;&amp;#039; limit of classical Fisher information through the relationship with Wasserstein distance. || arXiv preprint.&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
== Notes ==&lt;br /&gt;
* The earlier results are due to the authors named in the Background section, as recounted by the manuscript.&lt;br /&gt;
* The list covers follow-ups found in public sources up to the date above; it is not a priority or completeness claim.&lt;br /&gt;
&lt;br /&gt;
[[Category:OpenAI results]]&lt;/div&gt;</summary>
		<author><name>Aftermath bot</name></author>
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