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Flat-Minima Scaling Limits and the Riemann Hypothesis: An Exploratory Negative

This essay examines whether the non-Gaussian scaling limits of stochastic gradient descent (SGD) at flat minima, as established by Zhang, Mao, and Mukherjee, provide a structural analogy to the value distribution of the Riemann zeta function or critical multiplicative chaos.

Abstract

This essay examines whether the non-Gaussian scaling limits of stochastic gradient descent (SGD) at flat minima, as established by Zhang, Mao, and Mukherjee, provide a structural analogy to the value distribution of the Riemann zeta function or critical multiplicative chaos.


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The Source Result

The paper Scaling Limits of Constant-Stepsize SGD at Flat Minima (arXiv:2607.16384v1) studies stochastic gradient descent with a constant stepsize α near a minimizer x* where the Hessian vanishes as ‖x − x*‖^{m−2} for m ≥ 2. When m = 2 (quadratic), the invariant law scales as √α and has a Gaussian limit. For m > 2 (flat minima), the authors prove geometric convergence to an invariant law concentrating on the scale α^{1/m}, and the rescaled process converges to the stationary distribution of a nonlinear diffusion dY_t = −h_0(Y_t)dt + Σ^{1/2}dB_t. This yields generally non-Gaussian stationary limits.

The Attempted Bridge

We speculate that this anomalous diffusion might model the critical value statistics of the Riemann zeta function ζ(s), particularly the non-Gaussian fluctuations of log|ζ(1/2 + it)| and the framework of critical multiplicative chaos. The exponent m governing the flatness could correspond to the critical parameter in log-correlated Gaussian fields.

The Assessment

The analogy is rated as a suggestive metaphor at best. While both systems exhibit non-Gaussian limits governed by exponent parameters, the SGD dynamics rely on additive Markovian noise and deterministic flat geometry, whereas zeta-function statistics derive from multiplicative randomness and number-theoretic structures. The correspondence fails to produce a formal analogy because the invariant measures and scaling mechanisms are structurally incompatible.

Key Findings

This essay was produced by an automated research pipeline and has not been peer reviewed; conjectures herein are unproven.

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