\documentclass[11pt]{amsart} \IfFileExists{lmodern.sty}% {\usepackage[T1]{fontenc}\usepackage{lmodern}\usepackage{microtype}}% {\usepackage[expansion=false]{microtype}} \usepackage{amssymb,mathtools} \usepackage{booktabs,array} \usepackage{enumitem} \emergencystretch=2.5em \usepackage[colorlinks=true,linkcolor=blue,citecolor=blue,urlcolor=blue]{hyperref} % --------------------------------------------------------------------------- % Location of the Lean formalization. \newcommand{\FormalizationURL}{https://github.com/slitsey/catalan-irrationality-measure} \newcommand{\FormalizationLink}{\url{\FormalizationURL}} % --------------------------------------------------------------------------- \newtheorem{theorem}{Theorem}[section] \newtheorem{lemma}[theorem]{Lemma} \newtheorem{proposition}[theorem]{Proposition} \newtheorem{corollary}[theorem]{Corollary} \theoremstyle{definition} \newtheorem{definition}[theorem]{Definition} \theoremstyle{remark} \newtheorem{remark}[theorem]{Remark} \numberwithin{equation}{section} \newcommand{\Z}{\mathbb Z} \newcommand{\Q}{\mathbb Q} \newcommand{\R}{\mathbb R} \newcommand{\N}{\mathbb N} \newcommand{\cV}{\mathcal V} \newcommand{\cR}{\mathcal R} \newcommand{\cA}{\mathcal A} \newcommand{\cI}{\mathcal I} \newcommand{\cJ}{\mathcal J} \newcommand{\lean}[1]{\texttt{#1}} \begin{document} \title{An irrationality measure for Catalan's constant} \author{Sean Litsey} \email{sean.litsey.math@gmail.com} \date{October 15, 2026} \subjclass[2020]{Primary 11J82; Secondary 11J72, 68V20} \keywords{Catalan's constant, irrationality measure, irrationality exponent, determinants, Andr\'eief identity, formal verification, Lean} \begin{abstract} Building on OpenAI's proof that Catalan's constant $G=\sum_{j\ge0}(-1)^j/(2j+1)^2$ is irrational, we prove $|G-a/b|>b^{-878}$ for every integer $a$ and every sufficiently large integer $b$. Thus $\mu(G)\le878$. Using Chebyshev's estimates for final prime selection gives $2\,632$; denominator and content asymptotics still use PNT. We change the determinant parameters, obtaining a $20N$ matrix and a polynomial of degree at most $18N$. Uniform physical prime-column pools and sparse residue relations sharpen its common denominator. Exact energy certificates and separate treatment of free, fixed and marked populations give a uniform mixed-integrand bound. Stronger supplied energy trials, central-gap quadrature and jointly paid atom weights control the same determinant polynomial on $|x-G|\le e^{-(519037/5000)N}$. An explicit uniform residue-kernel construction supplies additional common coefficient content of quadratic logarithmic rate $16/63$. Coefficient divisibility recycles denominator prime squares; selecting the largest prime with $p^2\nmid b$ completes the improved measure criterion. We retain the earlier $48N$ construction and its $1\,981$ bound to explain the methods. Every ingredient of the new global theorem is formalized in Lean~4 with only the standard axioms and no unproved steps. \end{abstract} \maketitle \section{Introduction}\label{sec:intro} OpenAI \cite{OpenAI2026} recently proved that Catalan's constant \[ G=\sum_{j=0}^\infty\frac{(-1)^j}{(2j+1)^2}=0.91596\,55941\ldots \] is irrational, and formalized the proof in Lean. (An earlier claimed proof \cite{Sun2026} was found to contain a gap \cite{Wachs2026}.) The argument is by contradiction: under the hypothesis $G\in\Q$ an explicit determinant $\Delta_N$ of size $n=48N$ is a nonzero rational number whose denominator is controlled prime by prime, so that $\log|\Delta_N|\ge-(\mathsf A+o(1))n^2$; on the other hand a real-variable estimate gives $\log|\Delta_N|\le-(\mathsf U-o(1))n^2$ with $\mathsf U>\mathsf A$. The margin is small: $\mathsf U-\mathsf A\approx1.3\cdot10^{-4}$. As OpenAI remarks, the argument proves qualitative irrationality; an irrationality measure requires additional control of rational approximations. Recall that the \emph{irrationality exponent} $\mu(\xi)$ of a real number $\xi$ is the infimum of the $\mu$ such that $|\xi-a/b|>b^{-\mu}$ for all integers $a$ and all sufficiently large $b$. \begin{theorem}\label{thm:main} For every integer $a$ and every sufficiently large integer $b$, \[ \left|G-\frac ab\right|>b^{-878}. \] In particular $\mu(G)\le878$. Using Chebyshev's bounds for final prime selection gives the additional statement $|G-a/b|>b^{-2\,632}$. The denominator and coefficient-content asymptotics still use PNT. \end{theorem} Theorem~\ref{thm:main}, together with every result in this paper, has been verified in the Lean~4 proof assistant on top of OpenAI's formalization, with no unproved steps and only the standard axioms; see Section~\ref{sec:formal}. The formalization is available at \FormalizationLink. The use of AI in this work is disclosed at the end of the paper. \subsection{Previous results} The first finite irrationality measure for $G$ was obtained by Jha \cite{Jha2026}, who proved $\mu(G)\le10^8$, also with a Lean formalization built on OpenAI's. The present work was carried out independently; we found Jha's preprint in a literature search after our proof was complete. Both arguments have the shape that OpenAI's proof suggests: one replaces the determinant by a polynomial in the constant, clears denominators, and needs a perturbation estimate near $G$. They differ in the perturbation estimate. Jha bounds the complementary minors of OpenAI's matrix in every dimension, by an energy estimate with node padding, with a codimension loss of the form $\exp(1000\,n(n-m))$. Here the perturbation of the matrix is written, by a quadrature formula, as a combination of point evaluations of OpenAI's row polynomials. The selected parameter family first gave perturbation exponent $\rho=538/5$; the supplied trials and central-gap quadrature below sharpen it to $\rho=519037/5000$ (Section~\ref{ssec:gap878}). The improvement also uses actual local arithmetic and certified energy fields for that family. For other recent work on rational approximations to $G$ see Eskandari \cite{Eskandari2026}; for earlier work on the arithmetic of $G$ and related values see \cite{RivoalZudilin2003,Zudilin2003}; for an effective approach to linear independence of related $L$-values see Calegari, Dimitrov and Tang \cite{CDT2024}. Marcos Costa Santos Carreira \cite[Sections~2--6]{Carreira2026} studies five-parameter determinant designs and reports $\mu(G)<2715$ for the design $(96,15,6,8,5)$, using partial-population energy estimates and sharper row and column determinant bounds. His work also develops a two-measure equilibrium formulation. Our selected design is $(20,3,1,2,1)$. His general-design analysis and two-measure equilibrium formulation provide related structural viewpoints. The estimates proved here use full-interval marked polynomial atoms, coefficientwise prime-square recycling and the explicit secondary coefficient-content construction below. \subsection{Outline of the proof} Sections~\ref{sec:setup}--\ref{sec:proof} develop the $48N$ determinant and the earlier $1981$ bound. Section~\ref{sec:twenty} changes the parameters and proves the current result. The steps for the new family are: \begin{enumerate}[label=(\roman*)] \item Its determinant polynomial has degree at most $18N$. Actual prime valuations supply a common denominator of normalized growth $8795/4800+(21/200)\log2$. Multiplication by $(18N)!$ gives an integer polynomial, nonzero at $a/b$ for large prime indices $p$ with $p^2\nmid b$. \item Four certified endpoint trials and a uniform interpolation between free and fixed populations give physical real-place constant $2.256085-\tfrac12\log2$. Full-interval marked-sheet bounds and joint quadrature weights give perturbation exponent $538/5$; the arithmetic gap permits decay rate $\eta=1.7755$ after normalization. \item Coefficientwise divisibility strengthens the integer evaluation bound. The largest-good-prime refinement initially gives exponent $1091$. \item A uniform full-row residue kernel gives a secondary prime-content tent of area $16/63$. Dividing by this common coefficient content preserves recycling and increases the available normalized gap to $2.029$. With $d=18$ and $\rho=538/5$, the same criterion gives the retained $955/2864$ checkpoint. \item Supplied $40$-mode and $160$-mode trials improve the dual target to $2.2563367$. Interpolation nodes avoiding a central physical gap jointly improve the marked field and actual coefficient-functional price. With $\rho=519037/5000$ and $\eta=425979/200000$, the criterion gives $878$; final Chebyshev selection gives $2632$. The historical $3662$ statement remains available. \end{enumerate} \subsection{Notation and conventions} We use the notation of OpenAI's paper \cite{OpenAI2026} and refer to it for the constructions; we restate only what we use. Citations of the form \cite[Prop.~2.1]{OpenAI2026} point to numbered statements, sections and equations of OpenAI's paper. We write $\log$ for the natural logarithm. \section{OpenAI's construction and the facts we use}\label{sec:setup} For a positive integer $N$ put \cite[(2)]{OpenAI2026} \begin{gather*} n=48N,\qquad b=7N,\qquad q=g=4N,\qquad h=2N,\\ L=59N,\qquad C=63N,\qquad H=65N,\qquad A=19N, \end{gather*} and $D_*=n-1-2g=40N-1$. (The letter $A$ for $19N$ is OpenAI's; the constant $\mathsf A$ below is different.) The row polynomials $P_r,D_r\in\Z[t]$ ($0\le r0\}}\frac{f(t)}{t}D_r(t),\qquad \psi_k(s)=s^{b+k}(1-s)^q , \] and let $\cA_N$ be the real $n\times n$ matrix \begin{equation}\label{eq:matrix} \cA_N(r,k)=\int_{-1}^1\int_0^1 A_r(t)\,\frac{\psi_k(s)}{1-ts}\,ds\,d\mu(t) \qquad(0\le r,kP_*$ and every $z\in\Q$ whose denominator is not divisible by $p$, $v_p\bigl(\det(\cA^0_p+z\mathcal L_p)\bigr)=-96p$; in particular this determinant is nonzero. \end{enumerate} \end{proposition} Two remarks on (c) and (d). OpenAI states them under the hypothesis $G=z\in\Q$, but the proofs only use the arithmetic of the rational matrix $\cA^0_N+z\mathcal L_N$. In (d) OpenAI assumes $p>\max(P_*,\operatorname{den}z)$, but the proof only uses $p\nmid\operatorname{den}z$; this uniformity in $z$ is essential for an irrationality measure, and is how we use the result. We also use OpenAI's real-place machinery: the double integral, the two sheet estimates \cite[Props.~5.2, 5.3]{OpenAI2026}, and the certified energy dual \cite[Prop.~6.1, \S7]{OpenAI2026}. They are recalled where needed in Section~\ref{sec:perturbation}. OpenAI's irrationality proof is the inequality $\mathsf U_{\mathrm{OAI}}>\mathsf A$, and $\mathsf U_{\mathrm{OAI}}-\mathsf A=1.3031\ldots\cdot10^{-4}$. With a new certificate for one case of OpenAI's energy dual, Proposition~\ref{prop:dual} below shows that (b) holds with \[ \mathsf U=2.29180925-\tfrac12\log2 \] in place of $\mathsf U_{\mathrm{OAI}}$. We use this constant throughout. \begin{definition} $\Delta_N(X)=\det(\cA^0_N+X\mathcal L_N)\in\Q[X]$. Thus $\Delta_N(G)=\det\cA_N$, and $\Delta_N(z)$ for $z\in\Q$ is the rational determinant OpenAI studies under the hypothesis $G=z$. We write $\gamma_0=\mathsf U-\mathsf A$. \end{definition} Numerically $\mathsf U=1.9452356\ldots$, $\mathsf A=1.9442359\ldots$ and \begin{equation}\label{eq:gap} 9.996945\cdot10^{-4}<\gamma_0=9.996948\ldots\cdot10^{-4}. \end{equation} \section{Arithmetic of \texorpdfstring{$\Delta_N(X)$}{Delta\_N(X)}}\label{sec:arith} \begin{lemma}[Degree]\label{lem:degree} $\deg\Delta_N\le44N$. \end{lemma} \begin{proof} By \eqref{eq:L} row $r$ of $\mathcal L_N$ depends only on $P_r$, hence only on $|r-g|$ by \eqref{eq:rows}. So rows $r$ and $2g-r$ of $\mathcal L_N$ agree for $0\le r0$, $\log D_N\le(\mathsf A+\varepsilon)n^2$ for all large $N$. \end{proposition} \begin{proof} At an integer $z=i$ the denominator of $z$ is $1$, and OpenAI's local lower bounds for $v_\ell(\Delta_N(i))$ become independent of $i$: at odd primes they depend only on $\ell$ and $N$ (and vanish for $\ell>H$), and at $\ell=2$ they depend on $z$ only through a quantity that, over the integers, is largest at $z=0$. Let $e_\ell(N)\ge0$ be the resulting bound, and put $D_N=\prod_{\ell\le H}\ell^{e_\ell(N)}$. Then $v_\ell(D_N\Delta_N(i))\ge0$ for every prime $\ell$, and summing the bounds $e_\ell(N)\log\ell$ exactly as in OpenAI's proof of its finite-place bound \cite[Prop.~3.4]{OpenAI2026} gives $\log D_N\le(\mathsf A+o(1))n^2$. \end{proof} \begin{proposition}[Sparse prime-row dependencies]\label{prop:sparse-rows} Let $N\ge1$ and let $p$ be a sufficiently large prime such that $58N\le3p$, $p\le21N$ and $65N0$ and all sufficiently large $N$, \[ \log D_N^*\le(\mathsf A_*+\varepsilon)n^2,\qquad \mathsf A_* = \mathsf A-\frac{5}{1728}. \] \end{proposition} \begin{proof} Take the minimum of the old denominator exponent and the new bounds from Propositions~\ref{prop:sparse-rows} and~\ref{prop:early-rows} wherever each applies. This defines $D_N^*$ and proves integrality at all integer points. For large $N$ the old exponent is exactly $96N$ throughout these windows. The resulting continuous saving is \[ f(x)=3(x-18)_+-3(x-58/3)_+-3(x-59/3)_++3(x-21)_+, \] where $y_+=\max(y,0)$. It rises from zero to four on $[18,58/3]$, is constant on $[58/3,59/3]$, then decreases to zero at $21$. It is nonnegative, supported in $[18,21]$, and $\int_1^{65}f(x)\,dx=20/3$. The weighted prime number theorem gives \[ \frac{N}{n^2}\sum_{p\le65N}f(p/N)\log p\longrightarrow\frac{5}{1728}. \] Subtract this saving from Proposition~\ref{prop:denominators} to obtain the result. \end{proof} \begin{lemma}[Integer-valued polynomials]\label{lem:intvalued} If $f\in\Q[X]$ has degree at most $d$ and $f(\N)\subseteq\Z$, then $d!\,f\in\Z[X]$. \end{lemma} \begin{proof} The $d$-th forward difference of $f$ is $d!$ times its coefficient of $X^d$, and it is an integer combination of $f(0),\ldots,f(d)$. Subtract that coefficient times the integer-valued polynomial $X(X-1)\cdots(X-d+1)$ and induct on $d$. \end{proof} \begin{proposition}[Square-denominator nonvanishing]\label{prop:square-nonvanishing} For every prime $p>P_*$ and rational $z$ such that $pz$ has denominator coprime to $p$, $\Delta_p(z)\ne0$. In particular, $\Delta_p(a/b)\ne0$ if $a\in\Z$, $b\ge1$ and $p^2\nmid b$. \end{proposition} \begin{proof} The scaled residue matrix in OpenAI's nonvanishing proof is obtained from the rational matrix by multiplying each entry by $p^2$ and permuting its rows and columns. Each filtered entry is affine in $z$, so its change from the entry at zero is $p^2z\mathcal L_p(r,k)$. The central-binomial coefficients $c_l$ have denominators that are powers of $2$, and the filter coefficients are integers. Thus the denominator of $\mathcal L_p(r,k)$ is coprime to the odd prime $p$. If $pz$ also has denominator coprime to $p$, the change $p(pz)\mathcal L_p(r,k)$ has denominator coprime to $p$ and residue zero. The scaled residue matrix is therefore exactly the matrix at $z=0$. OpenAI's proof shows that this matrix has nonzero determinant for $p>P_*$, proving $\Delta_p(z)\ne0$. If $p\nmid b$, then $p(a/b)$ has denominator coprime to $p$. Otherwise write $b=pc$; $p^2\nmid b$ implies $p\nmid c$, and $p(a/b)=a/c$ again has denominator coprime to $p$. \end{proof} \begin{corollary}\label{cor:Q} $Q_N=(44N)!\,D_N^*\,\Delta_N(X)$ lies in $\Z[X]$ and has degree at most $44N$. If $p>P_*$ is prime, $a\in\Z$, $b\ge1$ and $p^2\nmid b$, then $Q_p(a/b)\ne0$ and hence $b^{44p}|Q_p(a/b)|\ge1$. \end{corollary} \begin{proof} The first claims follow from Lemmas~\ref{lem:degree} and~\ref{lem:intvalued} and Proposition~\ref{prop:sparse-denominators}. Proposition~\ref{prop:square-nonvanishing} gives $\Delta_p(a/b)\ne0$. Finally $b^{44p}Q_p(a/b)$ is a nonzero integer. \end{proof} \section{The irrationality-measure criterion}\label{sec:criterion} \begin{proposition}\label{prop:criterion} Let $\xi\in\R$, $d\in\N$ and $\eta,\rho>0$. Let $Q_p\in\Z[X]$ be defined for primes $p$ and suppose that, for all primes $p\ge P_0$: \begin{enumerate}[label=(\roman*)] \item $\deg Q_p\le dp$; \item $Q_p(a/b)\ne0$ for all $a\in\Z$ and $b\ge1$ with $p\nmid b$; \item $|Q_p(x)|\le e^{-\eta p^2}$ whenever $|x-\xi|\le e^{-\rho p}$. \end{enumerate} Put $\kappa=\max(d/\eta,4)$. Then $|\xi-a/b|>b^{-3\rho\kappa}$ for all $a\in\Z$ and all sufficiently large $b$. Assuming the prime number theorem, for every $\varepsilon>0$ and every $c>1$ the same holds with the exponent $(1+\varepsilon)\rho\max(d/\eta,c/\varepsilon)$. If (ii) holds whenever $p^2\nmid b$, this PNT exponent improves to $(1+\varepsilon)\rho\max(d/\eta,c/(2\varepsilon))$. \end{proposition} \begin{proof} Suppose $|\xi-a/b|\le b^{-3\rho\kappa}$ with $b$ large, and put $X=\kappa\log b$. If every prime in $(X,3X]$ divided $b$, then $\vartheta(3X)-\vartheta(X)\le\log b\le X/4$, where $\vartheta$ is Chebyshev's function. But Chebyshev's bounds $\vartheta(x)\le x\log4$ and $\vartheta(x)\ge(x-1)\log2-O(\sqrt x\log x)$ give $\vartheta(3X)-\vartheta(X)\ge X\log2-o(X)$. Hence for large $b$ there is a prime $p\in(X,3X]$ with $p\nmid b$, and $p\ge P_0$. Since $\rho p\le3\rho\kappa\log b$, we get $|a/b-\xi|\le e^{-\rho p}$, so by (iii) $|Q_p(a/b)|\le e^{-\eta p^2}$. By (i) and (ii), $b^{dp}Q_p(a/b)$ is a nonzero integer, so $e^{-\eta p^2}\ge b^{-dp}$, that is $p\le(d/\eta)\log b\le X$. This contradicts $p>X$. For the second statement use the window $(X,(1+\varepsilon)X]$ with $X=\max(d/\eta,c/\varepsilon)\log b$. Then $\log b\le\varepsilon X/c$, while the prime number theorem gives $\vartheta((1+\varepsilon)X)-\vartheta(X)=\varepsilon X+o(X)$, which exceeds $\varepsilon X/c$ for large $X$. For the stronger nonvanishing condition, put $X=\max(d/\eta,c/(2\varepsilon))\log b$. If every prime in $(X,(1+\varepsilon)X]$ had its square dividing $b$, their distinct prime squares would have product dividing $b$. Taking logarithms gives $2(\vartheta((1+\varepsilon)X)-\vartheta(X))\le\log b\le2\varepsilon X/c$. The PNT contradicts this for large $X$. There is therefore a prime with $p^2\nmid b$ in the window, and the polynomial argument proceeds unchanged. \end{proof} The factor $3$ in the first version, or $1+\varepsilon$ in the second, is the price of finding a prime $p\nmid b$ in a window of the right size. \section{The perturbation estimate}\label{sec:perturbation} This section proves the main new ingredient. Recall $\mathsf U=2.29180925-\frac12\log2$. \begin{theorem}[Perturbation estimate]\label{thm:perturbation} Let $\rho=366.3$. For every $\varepsilon>0$ there is $N_0$ such that for all $N\ge N_0$ and all real $x$ with $|x-G|\le e^{-\rho N}$, \[ |\Delta_N(x)-\Delta_N(G)|\le\exp\bigl(n^2(-\mathsf U+\varepsilon)\bigr). \] \end{theorem} Let $\delta=x-G$, so that $\Delta_N(x)=\det(\cA_N+\delta\mathcal L_N)$. The plan: write $\mathcal L_N=\Phi\beta$, where the columns of $\Phi$ are values of OpenAI's row functions $A_r$ at fixed nodes (\S\ref{ssec:quadrature}); expand the determinant column by column (\S\ref{ssec:expansion}); write each resulting mixed determinant as an integral (\S\ref{ssec:andreief}); and bound the integrand by OpenAI's method (\S\S\ref{ssec:vandermonde}--\ref{ssec:energy}). Throughout, $J=H=65N$. \subsection{A quadrature formula for \texorpdfstring{$\mathcal L_N$}{L\_N}}\label{ssec:quadrature} Let $x_a=\cos\bigl((2a+1)\pi/(2J)\bigr)$ for $0\le a\deg g$). Since $|c_z|\le1$, it suffices to show $|g_a(t)|\le2J\,K^N$ for $|t|=1$. We have $T_J=2^{J-1}\prod_c(X-x_c)$, so $\prod_c(t-\tau_c)=T_J(2t+1)/(2^J\,2^{J-1})$. For the denominator of $\ell_a$, $\prod_{c\ne a}|\tau_a-\tau_c|=2^{1-J}\prod_{c\ne a}|x_a-x_c|$ and $\prod_{c\ne a}(x_a-x_c)=2^{1-J}T_J'(x_a)=2^{1-J}J\,U_{J-1}(x_a)$. Since $U_{J-1}(\cos\theta)\sin\theta=\sin(J\theta)$ and $\sin(J\theta_a)=\pm1$ at $\theta_a=(2a+1)\pi/(2J)$, we get $|U_{J-1}(x_a)|\ge1$, so the denominator is at least $J\,2^{2-2J}$. Finally, for $|t|=1$, $|t-\tau_a|\ge1+\tau_a=(1+x_a)/2\ge\sin^2(\pi/(4J))\ge1/(4J^2)$. Hence \[ |\ell_a(t)|\le\frac{|T_J(2t+1)|}{2^{2J-1}}\cdot\frac{2^{2J-2}}J\cdot4J^2=2J\,|T_J(2t+1)| . \] Writing $\zeta=\cosh w$, one has $T_J(\zeta)=\cosh(Jw)$, $|\zeta-1|+|\zeta+1|=2\cosh\operatorname{Re}w$ and $|\cosh(Jw)|\le e^{J|\operatorname{Re}w|}$, so \[ |T_J(\zeta)|\le\bigl(S+\sqrt{S^2-1}\bigr)^J,\qquad S=\tfrac12\bigl(|\zeta-1|+|\zeta+1|\bigr). \] For $\zeta=2t+1$ with $|t|=1$, let $s=|t+1|\in[0,2]$. Then $|\zeta-1|=2$, $|\zeta+1|=2s$, $S=1+s$, and $|t-1|^2=4-s^2$ by the parallelogram law. With $J=65N$ and $q=4N$, \[ |g_a(t)|\le2J\,\Bigl(\bigl(1+s+\sqrt{s^2+2s}\bigr)^{65}(4-s^2)^2\Bigr)^N\le2J\,K^N, \] where the last inequality holds for all $s\in[0,2]$. (The function $(1+s+\sqrt{s^2+2s})^{65}(4-s^2)^2$ is largest near $s=1.917$, where its logarithm is $110.394\ldots$, while $\log K=110.4728\ldots$. We check it by splitting $[0,2]$ into $21$ intervals; on each, the first factor is increasing and the second decreasing in $s$, so it suffices to compare rational upper bounds at the endpoints with $K$.) \end{proof} \begin{remark} The cruder bound $\sum_i|[t^i]\ell_a|\le\prod_{c\ne a}(1-\tau_c)/\prod_{c\ne a}|\tau_a-\tau_c|\le(3+2\sqrt2)^J$, together with $\sum_v\binom qv=2^q$, gives $|\beta_{a,k}|\le2^{q+2}(3+2\sqrt2)^J$, whose logarithm is $(4\log2+65\log(3+2\sqrt2))N\approx117.35N$ instead of $\log K\cdot N\approx110.47N$. The unit circle captures the cancellation in $(t-1)^q$ between $t=1$, where $|T_J(2t+1)|$ is largest, and $t=-1$, where it is smallest. \end{remark} Let $\Phi$ be the $n\times J$ matrix $\Phi(r,a)=A_r(\tau_a)$. Then $\Delta_N(x)=\det\bigl(\cA_N+\delta\,\Phi\beta\bigr)$. \subsection{Column expansion}\label{ssec:expansion} For a map $f\colon\{0,\ldots,n-1\}\to\{\varnothing\}\cup\{0,\ldots,J-1\}$ let $M_f$ be the matrix whose column $k$ is column $k$ of $\cA_N$ if $f(k)=\varnothing$ and the column $\Phi(\cdot,f(k))$ otherwise, and let $m(f)=\#\{k:f(k)\ne\varnothing\}$. \begin{lemma}\label{lem:expansion} If $|\beta_{a,k}|\le B$ and $|\det M_f|\le M c^{m(f)}$ for every $f$, with $M,c\ge0$, then \[ \bigl|\det(\cA_N+\delta\Phi\beta)-\det\cA_N\bigr|\le M\bigl((1+J|\delta|Bc)^n-1\bigr). \] \end{lemma} \begin{proof} Column $k$ of $\cA_N+\delta\Phi\beta$ is $\cA_N(\cdot,k)+\sum_a\delta\beta_{a,k}\Phi(\cdot,a)$. Multilinearity gives $\det(\cA_N+\delta\Phi\beta)=\sum_f\prod_{k:f(k)\ne\varnothing}\delta\beta_{f(k),k}\det M_f$. The term $f\equiv\varnothing$ is $\det\cA_N$, and the others sum in absolute value to at most $M\sum_{f\not\equiv\varnothing}(|\delta|Bc)^{m(f)}=M((1+J|\delta|Bc)^n-1)$. \end{proof} \subsection{A mixed Andr\'eief identity}\label{ssec:andreief} Fix $f$, and let $p=n-m(f)$. Permuting columns (which only changes the sign of the determinant), $M_f$ has $p$ integral columns $\cA_N(\cdot,E_i)$, $0\le E_1<\cdotsD_*-m$. \end{proposition} \begin{proof} By \eqref{eq:sheet}, Cauchy's evaluation \[ \det\Bigl[\frac1{1-t_is_j}\Bigr]=\frac{V(t)V(s)}{\prod_{i,j}(1-t_is_j)} \] \cite[(63)]{OpenAI2026} and Lemma~\ref{lem:genvandermonde}, the integrand is at most \[ \Bigl(\prod_j(1+s_j)\Bigr)^m|\cR_n(z)|\prod_jw(y_j)\cdot\cJ^{(p)}(x,s). \] For a fixed node $-1\max(c_1,c_2)$. \begin{proposition}[Energy bound with missing points]\label{prop:energy} For every $d>0$ there is $N_0$ such that for all $N\ge N_0$, all $p\le n$ (with $m=n-p$) and all $x\in(-1,1)^p$, $s\in(0,1)^p$ with distinct nonzero coordinates, \[ E^{(p)}_\kappa(x,s)\le U_\kappa+d+\frac mn\,c_\kappa , \] for $\kappa=2$ unconditionally and for $\kappa=1$ under $\sum_{iD_*-m$. \end{proposition} \begin{proof} OpenAI's proof of \cite[Prop.~6.1]{OpenAI2026} regularizes the logarithmic interactions by matched damping, controls the diagonal and endpoint corrections, and completes two squares with the trial sequences. All of these steps are estimates for sums over the points, normalized by $n$, and they remain valid, with the same error terms, uniformly for any number $p\le n$ of points. The quadratic terms are bounded by $\kappa\|u\|_*^2+\frac12\|v\|_*^2$ as before. Only three places change. \begin{enumerate}[label=(\arabic*)] \item The constant term. For $p=n$ the powers of $2$ combine to $-\frac{11}{16}\log2$. For $p-1-\frac m6$, which costs $\lambda(1+m/6)/n$. \end{enumerate} The damping parameter is chosen in terms of $d$ alone, and the remaining errors are $O_d(1/n)$, uniformly in $p$ and the configuration. \end{proof} \subsection{A new certificate for the second case of the energy dual}\label{ssec:dual} For a finite list $c_1,\dots,c_K$ of reals and finitely many pairs $(z_j,r_j)$ of complex numbers with $|z_j|<1$, consider the trial sequence \begin{equation}\label{eq:trial} u_k=c_k+\operatorname{Re}\sum_j r_jz_j^k\qquad(k\ge1;\ c_k=0\text{ for }k>K). \end{equation} This is the form of OpenAI's trial sequences \cite[\S7]{OpenAI2026}. \begin{proposition}\label{prop:dual} There are trial sequences $u,v$ of the form \eqref{eq:trial}, with $K=40$, coefficients $c_k$ in $10^{-8}\Z$, twelve pairs $(z_j,r_j)$ for $u$ and fifteen for $v$, all $z_j$ and $r_j$ in $\Q+\Q i$ (they are listed in the file \lean{Dual/Data.lean} of the formalization), such that \eqref{eq:Bfields} holds for $\kappa=2$ with $B^2_x=-0.98572217$ and $B^2_s=-1.60942387$, and $\|u\|_*^2\le0.066723974$, $\|v\|_*^2\le1.292855037$. Hence \begin{align*} U_2&\le-\tfrac{11}{16}\log2+2\cdot0.066723974+\tfrac12\cdot1.292855037\\ &\qquad-0.98572217-1.60942387<-2.29180925 , \end{align*} and Proposition~\ref{prop:openai}(b) holds with $\mathsf U=2.29180925-\frac12\log2$ in place of $\mathsf U_{\mathrm{OAI}}$. \end{proposition} The sequences were found numerically, by maximizing the dual value $-U_2$ over sequences of the form \eqref{eq:trial} with prescribed bases $z_j$ (OpenAI's, together with $\pm0.9$, $\pm0.97$, $0.96$, $\pm0.99$ and a few others) by a cutting-plane method, and then rounded. At the optimum the two fields of \eqref{eq:Bfields} nearly equioscillate, with about fifty and thirty local maxima. \begin{proof} All computations below are in exact integer and rational arithmetic and are carried out by Lean's kernel. We follow the structure of OpenAI's certificate, but make each step a decidable check of general lemmas. \emph{Closed forms.} For $|x|\le1$, OpenAI's formulas give \[ T(u,x)=\sum_{k\le K}\frac{c_kT_k(x)}k-\frac12\operatorname{Re}\sum_jr_j\log(1-2xz_j+z_j^2) \] and $S(u,x)=\sum_{k\le K}c_kx^k/k-\operatorname{Re}\sum_jr_j\log(1-xz_j)$. Expanding the squares and using $\sum_{k\ge1}w^k/k=-\log(1-w)$, \begin{multline*} \|u\|_*^2=\sum_{k\le K}\frac{c_k^2+2c_kt_k}k -\frac12\operatorname{Re}\sum_{j,l}\bigl(r_jr_l\log(1-z_jz_l) +r_j\bar r_l\log(1-z_j\bar z_l)\bigr),\\ t_k=\operatorname{Re}\sum_jr_jz_j^k . \end{multline*} So the norms and the values of the fields at rational points are rational numbers plus finite sums of terms $\operatorname{Re}((c+di)\log w)$ with $c,d,w$ rational. Each such term is approximated to $10^{-12}$ by OpenAI's rational approximations of the logarithm and the arctangent \cite[\S7]{OpenAI2026}; the reduction of $w$ to the range of these approximations is computed and checked rationally. \emph{Stationary points.} The derivative of each field $F$ is a sum of rational functions with rational coefficients, hence $F'=A/Q$ with explicit $A,Q\in\Q[x]$ (of degrees $78$ and $39$ for the row field, $60$ and $21$ for the column field), where $Q$ does not vanish on the domain. The domain is cut into $154$ (respectively $94$) intervals. On $104$ (respectively $63$) of them $A$ has no root: after the substitution $x=a+(b-a)/(1+y)$, all coefficients of $(1+y)^{\deg A}A(x)$ have the same sign, so that $A$ has no root in $(a,b)$ (the case of Descartes's rule of signs without sign changes). The remaining $50$ (respectively $31$) intervals have length $2\cdot10^{-7}$ and contain the roots of $A$; a breakpoint between two intervals of the first kind is not a root of $A$. \emph{Brackets.} On a bracket $[l,l+w]$ write $A(l+wt)=\sum a_it^i$ and $Q(l+wt)=\sum q_it^i$. For $0\le t\le1$, $|F'|\le\sum|a_i|/(|q_0|-\sum_{i\ge1}|q_i|)$; since $A$ has a root in the bracket, $a_0$ and $a_1$ are small, and this gives $|F(x)-F(l)|\le10^{-8}$ on the bracket. The value $F(l)$ is computed as above. \emph{Conclusion.} The fields tend to $-\infty$ at $0$ and $1$ (the row field at $0^\pm$ and $1^-$), so their suprema are attained at stationary points or at $x=-1$, and every stationary point lies in a bracket. Comparing the certified values with $B^2_x$ and $B^2_s$ proves \eqref{eq:Bfields}. The bound for $U_2$ follows, with $\log2>0.6931471803$. OpenAI's proof of \cite[Prop.~7.1]{OpenAI2026} applies to any trial sequences in its two cases and gives $\limsup_N\log|\det\cA_N|/n^2\le\max(U_1,U_2)+\frac12\log2$, and $U_1<-2.296789875$. \end{proof} For efficient replay, the implementation clears polynomial denominators once and performs the root-cover and bracket substitutions over $\Z$, retaining rational arithmetic for the final scalar ratio and field approximations. Lean proves the coefficient conversions and the soundness of both substitutions. This changes the computation of the certificates, while preserving their trial sequences, covers and certified bounds. \begin{remark} OpenAI's own certificate for $\kappa=2$ records its bounds to five digits, as $B^2_x\le-0.98399+2.4\cdot10^{-5}$, $B^2_s\le-1.60890+2.4\cdot10^{-5}$ and a norm term at most $0.77844$, while its computations show that the largest bracket values of its two fields are $-0.98403338\ldots$ and $-1.60894641\ldots$ and its norm term is at most $0.778423472$. Read to seven digits, OpenAI's certificate already gives $U_2<-2.2910468$, and hence the exponent $34\,000$ by the argument of Section~\ref{sec:proof}. This is also formalized (\lean{SharpBarrier}). \end{remark} \subsection{A weighted endpoint certificate}\label{ssec:weighted} For each fixed $a\in\{0,1\}$, repeat the proof of Proposition~\ref{prop:energy} with the column field $W_s+2T(v,\cdot)+a\log(1+s)$, retaining the quadratic mass correction instead of using $1-p^2/n^2\le2m/n$. Write $K_a=\kappa\|u_a\|_*^2+\frac12\|v_a\|_*^2$ and $b_a=B_{x,a}+B_{s,a}$. The resulting bound, uniform in the same configurations, is \[ E^{(p)}_{\kappa,a}\le-\tfrac{11}{16}\log2+K_a+(1-t)b_a +(\tfrac\kappa2+1)(2t-t^2)\log2+\lambda_a t/6+d. \] Its error is uniform because $0\le a\le1$ and the added field is bounded and smooth at the damping endpoint. One may weaken it before damping at a cost $a\log2/n$, which tends uniformly to zero. Since $E^{(p)}_{\kappa,t}=(1-t)E^{(p)}_{\kappa,0}+tE^{(p)}_{\kappa,1}$, the two fixed endpoint inequalities give \begin{equation}\label{eq:weighted-quadratic} E^{(p)}_{\kappa,t}\le V_0+tC+t^2Q+d, \end{equation} where \begin{align*} V_0&=-\tfrac{11}{16}\log2+K_0+b_0,\\ C&=K_1-K_0+b_1-2b_0+(\kappa+2)\log2+\lambda_0/6,\\ Q&=b_0-b_1-(\tfrac\kappa2+1)\log2+(\lambda_1-\lambda_0)/6. \end{align*} Thus only two fixed trials need certification; no interpolated family of norms is assumed. For $\kappa=2$, the $a=0$ endpoint is Proposition~\ref{prop:dual}. A second rational trial, listed in \lean{WeightedDualTwo/Data.lean}, certifies \begin{gather*} B_{x,1}=-0.9498627,\qquad B_{s,1}=-1.2145624,\\ \|u_1\|_*^2\le0.0713397,\qquad \|v_1\|_*^2\le1.3114478, \qquad\lambda_0=\lambda_1=0. \end{gather*} Here $B_{s,1}$ bounds the column field including $\log(1+s)$. The same exact rational checks used in Proposition~\ref{prop:dual} apply: the derivative numerators have degrees $81$ and $62$, and the covers have $159$ and $93$ pieces, including $51$ and $31$ stationary-point brackets. These caps give $C\le5.817$, $Q\le0$, and $V_0<-2.29180925$. For $\kappa=1$, keep OpenAI's original trial at both endpoints, with $K_0=K_1=0.9321$ as a common norm cap and $\lambda_0=\lambda_1=2.47405979$. The new column check is \[ W_s+2T(v^{(1)},s)+\log(1+s)\le-0.7586255. \] Its derivative is rational with numerator degree $9$ and denominator degree $3$; a cover of five pieces has one stationary-point bracket. Combined with the old caps, it gives $C\le5.913488$, $Q\le-1.70907$, and $V_0\le-2.29180925-0.004980625$. The extra constant margin absorbs the larger linear coefficient: for $t\ge0$, \[ 0.183488t-1.70907t^2\le\frac{0.183488^2}{4\cdot1.70907}<0.004980625. \] Consequently the two cases give \begin{equation}\label{eq:weighted-energy} E^{(p)}_{1,t}\le-2.29180925+d+5.73t,\qquad E^{(p)}_{2,t}\le-2.29180925+d+5.817t. \end{equation} All the new field, norm, cover and algebraic inequalities are checked by Lean's kernel. The additional case-two decay absorbs its larger energy cost: since $8\log2>48(5.817-5.73)$ and $n=48N$, its product of fixed-node and energy factors is bounded by the common factor $2^{-28Nm}\exp(nm\cdot5.73)$. This uses the two cases together and does not change their trial sequences. \subsection{Completion of the proof}\label{ssec:assembly} \begin{proof}[Proof of Theorem~\ref{thm:perturbation}] Fix $d>0$ and let $N$ be large. By \eqref{eq:detMf}, Proposition~\ref{prop:pointwise}, \eqref{eq:weighted-energy}, with $c^*=5.73$ and $-2.29180925=-\mathsf U-\frac12\log 2$, every $f$ with $m=m(f)$ satisfies \[ |\det M_f|\le2^nK_n\,2^{-28Nm}\exp\bigl(n^2(-\mathsf U+d)+nm\,c^*\bigr)=Mc^m, \] with \[ M=2^nK_n\,e^{n^2(-\mathsf U+d)},\qquad c=2^{-28N}\,e^{nc^*}. \] (The degenerate configurations, such as two fixed nodes being equal or a vanishing coordinate, have measure zero or make the determinant vanish.) By Lemma~\ref{lem:quadrature}, $|\beta_{a,k}|\le B=8J^2K^N$. Now \begin{align*} \log(nJBc)&=\log(8nJ^3)-28N\log2+N\log K+nc^*\\ &= -28N\log2+N\log K+48Nc^*+\log(8\cdot48\cdot65^3N^4), \end{align*} and $-28\log2+\log K+48c^*<366.107$; so $nJBc\le e^{366.3N}$ for $N\ge4000$. If $|\delta|\le e^{-366.3N}$ then $J|\delta|Bc\le1/n$ and $(1+J|\delta|Bc)^n-1\le e-1<2$. Lemma~\ref{lem:expansion} gives \[ |\Delta_N(x)-\Delta_N(G)|\le2M=2^{n+1}K_n\,e^{n^2(-\mathsf U+d)} . \] Since $\log K_n=O(n\log n)$, taking $d=\varepsilon/2$ proves the theorem. \end{proof} \begin{remark}[The value of $\rho$] Per unit of $N$, the quadrature weights contribute $\log K<110.475$, the fixed nodes contribute $-28\log2$, and the weighted energy contributes $48\cdot5.73=275.04$. The polynomial prefactor is absorbed by the remaining margin to $\rho=366.3$. Retaining the Vandermonde product replaces the former combined charge $48\log2+48\cdot5.3678$ by the weighted energy charge, then the separate fixed-node caps and the quadratic margin lower it to $48\cdot5.73$. \end{remark} \section{The $48N$ bound}\label{sec:proof} \begin{proof}[The earlier $1981$ bound] Let $\gamma_*=\mathsf U-\mathsf A_* = \gamma_0+5/1728$ and $\eta=8969/1000$. The certified old margin \eqref{eq:gap} implies $2304\gamma_*>2304\cdot9.996945\cdot10^{-4}+20/3>8.969$. For sufficiently small $\varepsilon>0$ and large primes $p$, the real bound and perturbation estimate give $|\Delta_p(x)|\le2e^{n^2(-\mathsf U+\varepsilon)}$ on $|x-G|\le e^{-366.3p}$. The factorial and the factor two are $e^{o(n^2)}$, while Proposition~\ref{prop:sparse-denominators} bounds $D_p^*$ by $e^{n^2(\mathsf A_*+\varepsilon)}$. Thus $Q_p=(44p)!D_p^*\Delta_p$ satisfies $|Q_p(x)|\le e^{-\eta p^2}$ for large $p$. Corollary~\ref{cor:Q} gives its degree and square-denominator nonvanishing. Apply Proposition~\ref{prop:criterion} with $d=44$, $\rho=366.3$ and $R=d/\eta=44000/8969$. Choose $c=10001/10000$ and $\varepsilon=c/(2R)=89698969/880000000$. The PNT exponent is \[ (1+\varepsilon)\rho R=366.3\left(\frac{44000}{8969}+\frac{10001}{20000}\right) =1980.157945\ldots<1981. \] With the Chebyshev window the exponent is $3\rho R=5390.968892\ldots<5391$. \end{proof} \begin{remark}[Further reductions]\label{rem:limits} The sparse-row mechanism raises the denominator gap without changing the determinant's degree or the perturbation estimate. Further improvements can come from additional residue dependencies in other prime windows, more efficient determinant parameters, or a smaller perturbation exponent. Coefficient recycling below removes the overhead of the earlier square-prime selection step. The remaining analytic and arithmetic constants still give a bound far above two; the present proof does not establish an irrationality exponent near two. \end{remark} \section{A twenty-row parameter family}\label{sec:twenty} The preceding sections explain the $48N$ construction and its $1981$ bound. We now change the determinant parameters, first derive the $1281$ checkpoint, then refine quadrature and prime selection to prove Theorem~\ref{thm:main}. This change requires new arithmetic and real-place estimates; substituting parameters into the earlier numerical constants would not suffice. \subsection{The determinant and its arithmetic} Use the same moment and contact construction with \[ \begin{gathered} n=20N,\quad b=3N,\quad q=N,\quad g=2N,\quad h=N,\\ L=24N,\quad C=26N,\quad H=27N,\quad A=8N. \end{gathered} \] In the definitions of the row polynomials, replace the previous parameter values by these values: the offset is $r-2N$, the reversal length is $26N$, and the common row factor is $(1-t)^N$. The filtered columns are $t^{3N+k}(1-t)^N$. Write $\Delta_N^{(20)}(X)$ for the resulting determinant polynomial. Row reflection gives \[ \deg\Delta_N^{(20)}\le18N. \] The three $20\times20$ base matrices corresponding to signs $0,1,-1$ are invertible. Exact inverse certificates modulo $1009$ prove their rational nonvanishing. The prime-index reduction then proves uniformly, outside a fixed finite set of primes, \[ \Delta_p^{(20)}(a/b)\ne0\qquad\text{if }p^2\nmid b. \] The finite inverse computations certify the base matrices; the deduction for all large primes is a separate theorem, not an extrapolation from those computations. For large odd primes with $27N0$, eventually \[ \log D_N^{(20)}\le \left(\frac{8795}{4800}+\frac{21}{200}\log2+\epsilon\right)(20N)^2. \] The formal construction uses a harmless eventual threshold $N\ge10^{12}$ to absorb all finite prime cutoffs. No effective threshold for the final rational denominator is asserted. \subsection{Free and fixed populations} Recompute both sheet duals for the new parameters. Four rational trial certificates cover the two sheet cases at the two endpoints of the missing population. Their global field bounds, derivatives, norms and finite diagonal corrections are checked by the kernel. The certified dual target is \[ U_{20}=\frac{2256085}{1000000}. \] The physical determinant energy retains the correction $+\tfrac12\log2$. Fixed-node fields include the common-factor cancellation in the quadrature weights; their costs are not replaced by the free-node fields. The finite population interpolation gives, uniformly in every missing mass $m$, an energy loss at most $4.3\,m/(20N)$, in addition to an arbitrarily small regularization error. Damping is chosen before taking $N$ large, so this is a uniform bound rather than a numerical cutoff near the endpoints. Use $18N$ Chebyshev nodes for the residual row polynomials, and a circle of radius $1001/1000$. The exact circle certificate gives $K\le e^{33}$. The joint common-factor and quadrature-weight bound is $54000N K^N$ per atom. Combining it with the population estimate gives the actual mixed integrand, multiplied by all its atom weights, the bound \[ S_N(54000N)^m \exp\!\left((20N)^2\left(-U_{20}+\tfrac12\log2+\delta\right)+119Nm\right), \] where \[ S_N=(3/2)^{20N}(20N)^{10N} +(1+10e^{12}(20N))^{20N},\qquad \log S_N=o(N^2). \] This estimate covers both sheets. Zero nodes and repeated nodes give zero determinants and are included separately. The mixed Andr\'eief identity can retain the product of the atom weights on both sides of the integral. The determinant column expansion then uses their joint bound, with atom cost $54000N e^{119N}$. Since \[ (20N)(18N)(54000N)e^{119N}\le e^{120N} \] eventually, for every $\epsilon>0$ the actual determinant polynomial satisfies \begin{align*} |\Delta_N^{(20)}(G)|&\le e^{(20N)^2(-U_{20}+\frac12\log2+\epsilon)},\\ |\Delta_N^{(20)}(x)-\Delta_N^{(20)}(G)|&\le e^{(20N)^2(-U_{20}+\frac12\log2+\epsilon)} \quad\text{if }|x-G|\le e^{-120N}. \end{align*} \subsection{The $1281$ checkpoint} Set \[ A_{20}=\frac{8795}{4800}+\frac{21}{200}\log2, \qquad\gamma_{20}=U_{20}-\tfrac12\log2-A_{20}. \] The certified rational budget gives $400\gamma_{20}>177/100$. The integer-valued polynomial argument supplies $Q_N^{(20)}=(18N)!D_N^{(20)}\Delta_N^{(20)}\in\Z[X]$ for all sufficiently large $N$; smaller indices can be assigned the zero polynomial. Factorial growth is $o(N^2)$, so the criterion applies with \[ d=18,\qquad\eta=177/100,\qquad\rho=120. \] Choose $\varepsilon=247/5000$ and $c=1001/1000$ in the square-denominator prime window. Its exponent is \[ (1+\varepsilon)120\max\left(\frac{18}{177/100}, \frac{1001/1000}{2(247/5000)}\right) =\frac{377784}{295}<1281. \] The Chebyshev criterion gives $216000/59<3662$. These prove the earlier $1281$ bound and the retained historical Chebyshev bound. The corresponding Lean statements are in \lean{Parametric/TwentyMain}. They have suffixes \lean{1281} and \lean{3662}. We next improve the first bound. \subsection{Full-interval marked atoms and the critical radius} Keep the same integer polynomial $Q_N^{(20)}$, and let $J=18N$. Take $\tau_1,\ldots,\tau_J$ to be all roots of $T_J$ in $(-1,1)$. Since $J$ is even none is zero. Exact coefficient quadrature now gives \begin{gather*} (\mathcal L_N)_{rk}=\sum_{a=1}^J P_r(\tau_a)\beta_{ak}, \qquad \kappa_N(t)=t^{8N}(1-t)^N,\\ |\kappa_N(\tau_a)\beta_{ak}|\le108000N e^{18N}. \end{gather*} The fixed vectors are values of the original $P_r$, including at positive nodes; they are not values of the physical amplitude $A_r$ there. For $p$ free and $m$ fixed columns, $p+m=20N$, the marked first-sheet Hadamard bound has the same prefactor $(3/2)^{20N}(20N)^{10N}$ as before. The full first-case energy certificate gives loss $(448/5)Nm$. Here its scalar budget is sharpened from $27/5$ to $269/50$: the difference is bounded above by \[ -\frac8{125}+\frac{593}{1000}a-\frac{693}{500}a^2 =-\frac{693}{500}\left(a-\frac{593}{2772}\right)^2 -\frac{3167}{5544000}<0. \] Removing the quadrature term $(9/10)a$ leaves coefficient $112/25$; multiplication by $20Nm$ gives the stated loss. In the second case expand only positive marked nodes into actual and near sheets, using the exact identity $P=-2A+3A_{\rm near}$ after removal of the common row weight. The grouped energy certificate retains separate Vandermonde factors for actual and near nodes; its loss is $89Nm$. The expansion costs at most $5^m$. Both estimates include a uniform arbitrarily small quadratic-scale error. Combining them with the joint weight bound gives \begin{equation}\label{eq:full-marked-bound} S_N(540000N)^m \exp\!\left((20N)^2\left(-U_{20}+\tfrac12\log2+\epsilon\right)+(538/5)Nm\right). \end{equation} Here $S_N$ is the same prefactor as above. In the second case the sharper $107Nm$ can be increased to $(538/5)Nm$. The mixed Andr\'eief bound allows arbitrary fixed column vectors. Formally, modify the integrated row functions at finitely many distinct auxiliary points; the atomless measure makes this change invisible to the integrals. Repeated fixed atoms give identical columns and determinant zero. Free/free and free/fixed collisions are excluded on null sets. No equality of a positive marked $P$ column and an actual free column is assumed. These arguments also cover $p=0$ and $m=0$. After integration, put \[ M_N=2^{20N}S_N e^{(20N)^2(-U_{20}+\frac12\log2+\epsilon)},\qquad c_N=540000N e^{(538/5)N}. \] The exact joint column expansion gives \[ |\Delta_N^{(20)}(G+\delta)-\Delta_N^{(20)}(G)| \le M_N\bigl((1+J|\delta|c_N)^{20N}-1\bigr). \] If $|\delta|\le e^{-(538/5)N}$ the binomial factor is at most $(1+9720000N^2)^{20N}=e^{O(N\log N)}$. Its logarithm is $o(N^2)$; there is no need to bound the factor by an absolute constant. Absorb it and the factorial normalization into the regularization error. For all sufficiently large $N$, \begin{equation}\label{eq:rho1076} |Q_N^{(20)}(x)|\le e^{-(177/100)N^2} \quad\text{whenever }|x-G|\le e^{-(538/5)N}. \end{equation} \subsection{Coefficient recycling and the final prime choice} Write $Q_N=Q_N^{(20)}=\sum_j c_{Nj}X^j$ and $D=18N$. For every sufficiently large $N$ and every prime $N\frac{17755}{10000}. \] Indeed the already verified bound $\log2<0.693147181$ suffices. The interval estimate \eqref{eq:rho1076}, including normalization, therefore holds with every $\eta<400\gamma_{20}$, in particular this sharper choice. Set $\eta=17755/10000$, $d=18$, $\rho=538/5$, $k=5455/538$ and $\delta_0=1/1000000$. For large $b$, put $L_b=\log b$, $U=kL_b$, $V=(k-1)L_b$. The prime number theorem supplies, simultaneously for every sufficiently large real $t$, \[ (1-\delta_0)t\le\theta(t)\le(1+\delta_0)t. \] If every prime in $(V,U]$ had its square dividing $b$, then $2(\theta(U)-\theta(V))\le L_b$. The displayed PNT bounds contradict this, since $2(1-\delta_0(2k-1))>1$. Choose the \emph{largest} prime $p\in(V,U]$ for which $p^2\nmid b$. Every prime $q\in(p,U]$ has $q^2\mid b$, and $U<2V<2p$. Take $B$ to be the product of their squares and put $T=\theta(U)-\theta(p)$, so $\log B=2T$. Suppose $|G-a/b|\le b^{-1091}$. Since $\rho p\le\rho U=1091L_b$, \eqref{eq:rho1076} applies at $a/b$. Prime-index nonvanishing and \eqref{eq:recycled-integer-lower} give \[ \eta p\le d(L_b-2T). \] But the PNT bounds imply $T\ge U-p-2\delta_0U$. Using $p\le U$ and $2d-\eta>0$ now yields \[ \eta k\le d+4d\delta_0 k, \qquad \eta k-d-4d\delta_0k=\frac{47987}{26900000}>0, \] a contradiction. This proves the retained $1091$ bound. The combined Lean theorem in namespace \lean{CatalanMeasure.Parametric} is \lean{catalan\_irrationalityMeasure\_1091}. It is proved in \lean{Parametric/}\allowbreak\lean{TwentyCostMain}. Its public series version is in \lean{Solution.lean}. The earlier $1095$ theorem remains in \lean{Parametric/}\allowbreak\lean{TwentySharperMain}; the $1099$ theorem remains in \lean{Parametric/}\allowbreak\lean{TwentyRecycledMain}. The sharper gap and marked-column cost give the limiting exponent $3873600/3551\approx1090.848$; the strong eventual statement above uses the integer exponent $1091$. The following arithmetic refinement gives the $955$ checkpoint; Section~\ref{ssec:gap878} then sharpens its real estimate to the current statement of Theorem~\ref{thm:main}. \subsection{A uniform secondary coefficient-content tent}\label{ssec:secondary-tent} Write $\mathcal A_{N,p}$ for the reduction of $p^2$ times the actual filtered base matrix. For all sufficiently large $N$ and primes $52N/90$, allow $\deg I_B<4\delta$; for $p+d=6N$, set $I_B=0$. The remaining constraint costs are \[ \begin{array}{c|c|c} &p=6N+\delta&p+d=6N\\\hline \text{parameter dimension}&N+2g+3N+4\delta&N+2g+3N\\ \text{small beta flag}&3N&g\\ \text{two }H_U\text{ branch flags}&N+n&N+n\\ \text{shared top cap}&8N-p+1&8N-p+1\\ \text{extra endpoint/response flags}&0&4d+4d \end{array} \] For the beta flag use $Q_i(1)=\beta_i$ and $(x-1)^p\mid Q_i^p-Q_i(1)$; its small polynomial vanishes after the indicated number of coefficient constraints. Since $N+n\le p-N$, this pays the entire $H_V$ branch flag. On the upper side the boundary input degree pays the lower endpoint $z^{24N-2p}\mid K$. On the lower side it is paid by the first $4d$ coefficients after the automatic $z^{2p}$ factor; impose another $4d$ literal raw-response conditions on the available $J=4$ columns. The $E$ response is confined to the unavailable $J=0$, $e<3N$ block. On the upper side the $B$ response is confined to unavailable $J=3$ columns, because every available such column has $e0. \] This proves the retained $955$ checkpoint. Its Lean theorem is \begin{center} \lean{catalan\_irrationalityMeasure\_955} \end{center} in \lean{Parametric/}\allowbreak\lean{SecondaryTentMain}. The limiting exponent using the full tent area is $244036800/255713\approx954.339$. Alternatively, apply the Chebyshev final prime-selection criterion of Proposition~\ref{prop:criterion} to the same $\widetilde Q_N$. Its degree is still at most $18N$. Since $p\nmid b$ implies $p^2\nmid b$, the same rational nonvanishing theorem applies. The exact criterion exponent is \[ 3\frac{538}{5}\max\left(\frac{18}{2029/1000},4\right) =\frac{5810400}{2029}<2864. \] For $b\ge2$, weakening the exponent gives $b^{-2864}<|G-a/b|$. This proves the retained $2864$ checkpoint, formalized as \lean{catalan\_}\allowbreak\lean{irrationality}\allowbreak\lean{Measure\_2864} in \lean{Parametric/}\allowbreak\lean{SecondaryTentChebyshev}. Only final prime selection uses Chebyshev here: the denominator asymptotics and the secondary coefficient-content rate remain PNT-backed, as the denominator asymptotics already were for the historical $3662$ theorem. \subsection{Supplied trials and central-gap interpolation}\label{ssec:gap878} We now retain the same canonical determinant polynomial, degree bound, integer normalization, own-prime nonvanishing and coefficient-content divisor, and improve its real estimates. This changes neither the local arithmetic nor the polynomial's rational zeros. The preceding $955/2864$ proofs remain available as separate checkpoints. \paragraph{The supplied trial contracts.} Set \[ \begin{gathered} U_* =2.2563367,\quad c_1=4.21,\quad c_2=4.29472,\\ g=\frac{401}{2500},\quad a=\frac{2g}{1+g^2}=\frac{2005000}{6410801}. \end{gathered} \] The first-population trial has $40$ finite modes and its saved geometric tails. The second has $160$ finite modes and its saved real and complex tails. Their coefficients are exact rationals in \lean{FirstStrongTrial/Data} and \lean{StrongTrial/Data}; the certificate generation records fix their input hashes. The effective first sequence is $p=2P$, so its norm contribution is $4\|P\|^2+\|V\|^2/2$; the second uses $2\|P\|^2+\|V\|^2/2$. These conventions are part of the supplied-field contracts, rather than an identification of the two trial norms. The certified caps are \[ \begin{array}{c|ccc} &\text{weighted norm}&\text{row plus column cap}&\lambda\\ \hline \text{first}&.67761&-2.47913&1.68493357\\ \text{second}&.77424975&-2.54538346&0 . \end{array} \] The second sequence also satisfies $p_1\ge .18$. Its marked residual satisfies the stronger, restricted bound \begin{equation}\label{eq:gap878-residual} -\frac9{10}\log(1+x^2)-2T(P,x)\le -.0524 \quad(g\le |x|\le1). \end{equation} The near-field bound remains global: for $0g$. This property survives the second-sheet grouping because its marked coordinates are selections of these points. Polynomial interpolation is exact at these nodes, so the same residual coefficient functional and common-factor cancellation apply. At a root, the Chebyshev derivative identity gives \[ |P_N'(t_{j,\pm})|\ge\frac{36Na}{1-a^2}. \] Fix $r=1001/1000$ and write $s=|\operatorname{Re}z|$ on $|z|=r$. For $w=(2z^2-(1+a^2))/(1-a^2)$, its exact ellipse half-sum is \[ H(s)=\frac{\sqrt{(r^2+1)^2-4s^2} +\sqrt{(r^2+a^2)^2-4a^2s^2}}{1-a^2}. \] It decreases with $s$, whereas $|1-z|^2\le r^2+1+2s$ increases. A contiguous cover of $[0,r]$ by $55$ rational intervals, with upward square-root bounds and certified logarithms, proves \[ 9\log\bigl(H(s)+\sqrt{H(s)^2-1}\bigr) +\log(r^2+1+2s)<17.913. \] Since $|z-t_{j,\pm}|\ge1/1000$ and $(1-a^2)/(36a)\le1$, the same coefficient-functional argument as before yields the actual joint bound \[ \bigl|\Phi_{N,k}(C_N L_{j,\pm})\bigr| \le108000N\exp(17.913N). \] Here $L_{j,\pm}$ is the cardinal polynomial of the new nodes and $C_N$ is the existing common factor. The residual cap and this increased nodal price are paid together. A smaller field cap without its changed weights would not give this conclusion. \paragraph{The completed ledger.} The larger marked row price is $20c_2=85.8944$. Adding the actual weight price gives \[ \rho=20c_2+17.913=\frac{519037}{5000}=103.8074. \] The exact unperturbed gap is $400U_*-8795/12-242\log2>375279/200000$; dividing by the unchanged content divisor adds $507/2000$. Thus the integer polynomial has the same degree bound $dN=18N$, with usable decay \[ \eta=\frac{375279}{200000}+\frac{507}{2000} =\frac{425979}{200000}=2.129895. \] Apply the largest-good-prime criterion with \[ k=\frac{4390000}{519037},\qquad \delta_0=10^{-7}. \] Its window and integer-payment margins are respectively \[ \frac{2595176739037}{2595185000000}>0, \qquad \eta k-18-72\delta_0k=\frac{3770721}{259518500}>0. \] Since $\rho k=878$, this proves the first statement of Theorem~\ref{thm:main}. The limiting exponent of this paid ledger is \[ \frac{18\rho}{\eta}=\frac{41522960}{47331} =877.288880\ldots<878. \] For final Chebyshev selection the same integer polynomial and its nonvanishing theorem give \[ 3\rho\max\left(\frac{18}{\eta},4\right) =\frac{41522960}{15777}<2632. \] Weakening this exponent for $b\ge2$ proves the second statement. Denominator growth and secondary content still use PNT in both results. The two new main theorems are \lean{catalan\_irrationalityMeasure\_878} and \lean{catalan\_irrationalityMeasure\_2632} in \lean{Parametric/GapMain}. \section{Formalization}\label{sec:formal} \raggedbottom All results of this paper are formalized in Lean~4 \cite{Lean4} with Mathlib \cite{Mathlib}, on top of OpenAI's Lean formalization of the irrationality of $G$ \cite{OpenAI2026}. The development is available at \begin{center} \FormalizationLink \end{center} and combines analytic and arithmetic proofs with generated rational data and kernel checks for Proposition~\ref{prop:dual} and Section~\ref{ssec:weighted}. The uniform sparse and combined prime-row dependencies and the weighted-PNT denominator saving are also proved in Lean; numerical rank scans alone are not used as proof. The historical sharpened OpenAI certificate is retained separately. It uses OpenAI's definitions directly: Catalan's constant is \lean{catalan}, defined as the series $\sum_j(-1)^j/(2j+1)^2$; the matrix \eqref{eq:matrix} and its rational form are OpenAI's \lean{determinant} and \lean{determinantRat}. The current main statements are in \lean{CatalanMeasure.Parametric}; the listed historical lemmas remain in \lean{OAI.InternalCatalan}: \begin{itemize} \item \lean{catalan\_irrationalityMeasure\_878}: for all sufficiently large $b\in\N$ and all $a\in\Z$, $b^{-878}<|G-a/b|$ (Theorem~\ref{thm:main}); \item \lean{catalan\_irrationalityMeasure\_2632}: the same with exponent $2\,632$, using Chebyshev for final prime selection; \item \lean{catalan\_irrationalityMeasure\_955}: the retained $955$ checkpoint; \item \lean{catalan\_irrationalityMeasure\_2864}: the same with exponent $2\,864$, using Chebyshev for final prime selection; \item \lean{catalan\_irrationalityMeasure\_3662}: the retained historical statement with exponent $3\,662$; \item \lean{eventually\_realDeterminant\_abs\_upper\_dual}: Proposition~\ref{prop:dual}; \item \lean{separate\_perturbation}: Theorem~\ref{thm:perturbation}, with $\rho=366.3$; \item \lean{catalan\_irrationalityMeasure} and\\ \lean{catalan\_irrationalityMeasure\_pnt}: the general exponents of Proposition~\ref{prop:criterion}. \end{itemize} The solution has no \lean{sorry}, and the command \lean{\#print axioms} reports only the three standard axioms \lean{propext}, \lean{Classical.choice} and \lean{Quot.sound}. The prime number theorem enters the denominator asymptotics and secondary prime-content sum, and also the final prime selection for $878$. The $2632$ corollary uses Chebyshev only in that final selection step. The $955/2864$ checkpoint has the same PNT scope. The formal source for PNT is the PNT+ project \cite{PNTPlus}, through OpenAI's workspace and compatibility additions. \begingroup \noindent The following file groups implement the indicated parts of the proof.\par\medskip \noindent \lean{DeltaPoly}, \lean{Degree}\par $\Delta_N(X)$; Lemma~\ref{lem:degree}.\par\medskip \noindent \lean{Denominators}, \lean{IntegerValued}, \lean{Integrality}\par Proposition~\ref{prop:denominators}; Lemma~\ref{lem:intvalued}; Corollary~\ref{cor:Q}.\par\medskip \noindent \lean{SparseDenominators}, \lean{DenseDenominators}, \lean{DenseGainPNT}, \lean{DenseMain}\par Propositions~\ref{prop:sparse-rows}--\ref{prop:sparse-denominators}; the earlier $1981$ bound.\par\medskip \noindent \lean{Nonvanishing}\par Proposition~\ref{prop:openai}(d) for $p\nmid\operatorname{den}z$.\par\medskip \noindent \lean{PrimeWindow}, \lean{Criterion}, \lean{PNTWindow}, \lean{Main}\par Proposition~\ref{prop:criterion} and the reduction to Theorem~\ref{thm:perturbation}.\par\medskip \noindent \lean{Quadrature}, \lean{ChebyshevNodes}, \lean{QuadCircle}\par Lemma~\ref{lem:quadrature}.\par\medskip \noindent \lean{DetExpansion}\par Lemma~\ref{lem:expansion}.\par\medskip \noindent \lean{MixedAndreief}\par Lemma~\ref{lem:andreief}.\par\medskip \noindent \lean{VandermondeProduct}\par Lemma~\ref{lem:genvandermonde}.\par\medskip \noindent \lean{PinMajorant}, \lean{FixedNodes}, \lean{FixedNodeMajorant}\par Proposition~\ref{prop:pointwise}, \eqref{eq:fixed-node}, and \eqref{eq:energy-identity}.\par\medskip \noindent \lean{PinDampedDual}, \lean{PinSupDual}\par Proposition~\ref{prop:energy}.\par\medskip \noindent \lean{Cert/ListPoly}, \lean{Cert/LogApprox}, \lean{Cert/FieldEval}, \lean{Cert/FieldDeriv}, \lean{Cert/Cover}, \lean{Cert/Norm}\par the general lemmas behind the checks of Proposition~\ref{prop:dual}.\par\medskip \noindent \lean{Dual/*}, \lean{DualTwo}\par the certificate data, the kernel checks, Proposition~\ref{prop:dual}.\par\medskip \noindent \lean{SharpBarrier}\par the remark after Proposition~\ref{prop:dual}.\par\medskip \noindent \lean{WeightedEnergy}, \lean{WeightedBounds}\par Section~\ref{ssec:weighted}.\par\medskip \noindent \lean{SeparateFixedNodes}, \lean{SeparateBounds}, \lean{SeparateLemma6}\par Theorem~\ref{thm:perturbation}.\par\medskip \noindent \lean{SquareNonvanishing}, \lean{SquarePNTWindow}, \lean{SquareMain}\par Proposition~\ref{prop:square-nonvanishing}, strengthened Proposition~\ref{prop:criterion}.\par\medskip \noindent \lean{Parametric/GapMain}, \lean{GapFinalTransfer}\par Section~\ref{ssec:gap878}; current $878/2632$ bounds.\par\medskip \noindent \lean{FirstStrongTrial/*}, \lean{StrongTrial/*}\par Supplied exact trials, point values and root-coverage certificates.\par\medskip \noindent \lean{GapNodal}, \lean{GapCircle/*}, \lean{GapWeights}\par Central-gap quadrature and actual joint weight bounds.\par\medskip \noindent \lean{Cert/DescartesBudget}, \lean{Cert/IntegerHorner}\par Distinct-root budgets and checked bracket endpoints.\par\medskip \noindent \lean{SecondaryTentMain}, \lean{SecondaryTent}\allowbreak\lean{MeasureTransfer}\par Section~\ref{ssec:secondary-tent}; retained $955$ bound.\par\medskip \noindent \lean{SecondaryTentChebyshev}\par Alternate final prime selection; $2864$ bound.\par\medskip \noindent \lean{SecondaryTent}\allowbreak\lean{Parameters*}, \lean{SecondaryTentRow*}, \lean{SecondaryTentSource*}\par Actual uniform row kernel, source compatibility and prime-content tent.\par\medskip \noindent \lean{TwentyCostMain}, \lean{TwentySharperMain}, \lean{TwentyIntegerPolynomial}\par Retained $1091/3662$ bounds and canonical integer polynomial.\par\medskip \noindent \lean{TwentyDenominators}, \lean{TwentyTwoAdicNorm}, \lean{TwentyCombinedOddLoss}\par Actual local arithmetic and common-denominator growth.\par\medskip \noindent \lean{TwentyTrial/*}, \lean{TwentyFirstCost}, \lean{TwentyCostPerturbation}\par Certified population and marked fields, mixed integration and $\rho=538/5$.\par\medskip \endgroup The current proofs were checked with Lean \texttt{v4.35.0-rc2} and the matching Mathlib release. OpenAI's original repository at commit \texttt{fd4aeeb} pins Lean \texttt{v4.34.1} and Mathlib commit \texttt{d13f23b}. The parts of that formalization used here were converted to Lean's module system and ported to the current toolchain; the repository's README and provenance documents describe the changes. \section*{Disclosure of AI use} The original development was produced by the AI system Claude Opus~5.5 (Anthropic): the mathematics, including the perturbation estimate and all proofs; the Lean formalization; the numerical computations and the certificate generator; the literature search; and the text of this paper. Claude worked in a series of conversations at the request of the author, who posed the problem, directed the work, and is responsible for this submission. The separate fixed-node decay bounds and weighted Vandermonde refinement, endpoint certificates, quadratic case refinement, dependency refactor, integer certificate computations and their soundness proofs, square-denominator nonvanishing, the prime-window refinement, uniform sparse and combined prime-row dependencies and denominator saving, the twenty-row parameter family, certified free and fixed population fields, joint atom integration, and corresponding revisions to this paper were developed by OpenAI Codex running GPT-6.1 Sol (OpenAI) at the author's request. The full-interval marked-sheet assembly, critical-radius perturbation, coefficient recycling, largest-good-prime criterion and the uniform secondary coefficient-content tent with its complete source and row formalization were developed with Codex at the author's request. The subsequent supplied-trial refinements, central-gap interpolation, actual circle weights, reusable root-count coverage certificates and the $878/2632$ assembly were also developed with Codex at the author's request. The underlying irrationality proof and its formalization are OpenAI's \cite{OpenAI2026}. The formal verification in Lean is intended as an independent check of every step of the argument above. \begin{thebibliography}{99} \bibitem{CDT2024} F.~Calegari, V.~Dimitrov and Y.~Tang, \emph{The linear independence of $1$, $\zeta(2)$, and $L(2,\chi_{-3})$}, preprint, \href{https://arxiv.org/abs/2408.15403}{arXiv:2408.15403}. \bibitem{Carreira2026} Marcos Costa Santos Carreira, \emph{General designs and an irrationality exponent for Catalan's constant}, preprint v1 (October 9, 2026), \href{https://doi.org/10.5281/zenodo.23326325}{doi:10.5281/zenodo.23326325}; sources at \url{https://github.com/MarcosCarreira/catalan-designs}. \bibitem{Eskandari2026} P.~Eskandari, \emph{Improved rational approximations to Catalan's constant}, preprint (2026), \href{https://arxiv.org/abs/2609.26354}{arXiv:2609.26354}. \bibitem{Forrester2018Andreief} P.~J.~Forrester, \emph{Meet Andr\'eief, Bordeaux 1886, and Andreev, Kharkov 1882--83}, preprint (2018), \href{https://arxiv.org/abs/1806.10411}{arXiv:1806.10411}. \bibitem{Jha2026} R.~K.~Jha, \emph{A finite irrationality measure for Catalan's constant}, preprint v1, October 8, 2026, \href{https://doi.org/10.5281/zenodo.23237269}{doi:10.5281/zenodo.23237269}; Lean sources at \url{https://github.com/rohitkrjha/catalan-measure}. \bibitem{Mathlib} The mathlib Community, \emph{The Lean mathematical library}, in: Proceedings of the 9th ACM SIGPLAN International Conference on Certified Programs and Proofs (CPP 2020), 367--381. \bibitem{Lean4} L.~de~Moura and S.~Ullrich, \emph{The Lean~4 theorem prover and programming language}, in: Automated Deduction -- CADE 28, Lecture Notes in Computer Science 12699, Springer, 2021, 625--635. \bibitem{OpenAI2026} OpenAI, \emph{Catalan's constant is irrational}, preprint (September 24, 2026), with a Lean formalization, available at \href{https://github.com/openai/math/blob/fd4aeeb2ee4fc729c18d98444fed42fd0529eeeb/preprints/Catalans-constant-is-irrational-September-24-2026/paper.pdf}{the original paper PDF} and \href{https://github.com/openai/math/tree/fd4aeeb2ee4fc729c18d98444fed42fd0529eeeb/lean/OAI/NumberTheory/Catalan}{the Lean formalization} (repository commit \texttt{fd4aeeb}, October 7, 2026). \bibitem{RivoalZudilin2003} T.~Rivoal and W.~Zudilin, \emph{Diophantine properties of numbers related to Catalan's constant}, Math. 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