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What is the most optimal diffusion?

Published 8 Oct 2025 in cond-mat.stat-mech | (2510.07571v1)

Abstract: What is the fastest possible "diffusion"? A trivial answer would be "a process that converts a Dirac delta-function into a uniform distribution infinitely fast". Below, we consider a more reasonable formulation: a process that maximizes differential entropy of a probability density function (pdf) f(x,t)f(\vec{x}, t) at every time tt, under certain restrictions. Specifically, we focus on a case when the rate of the Kullback-Leibler divergence DKLD_{\text{KL}} is fixed. If Δ(x,t,dt)=ftdt\Delta(\vec{x}, t, d{t}) = \frac{\partial f}{ \partial t} d{t} is the pdf change at a time step dtd{t}, we maximize the differential entropy H[f+Δ]H[f + \Delta] under the restriction DKL(f+Δf)=A<sup>2</sup>dt<sup>2D_{\text{KL}}(f + \Delta || f) = A<sup>2</sup> d{t}<sup>2, $A = \text{const} &gt; 0$. It leads to the following equation: ft=κf(lnfflnfdx)\frac{\partial f}{ \partial t} = - \kappa f (\ln{f} - \int f \ln{f} d{\vec{x}}), with κ=Afln<sup>2f</sup>dx(flnfdx)<sup>2</sup>\kappa = \frac{A}{\sqrt{ \int f \ln<sup>2{f}</sup> d{\vec{x}} - \left( \int f \ln{f} d{\vec{x}} \right)<sup>2</sup> } }. Notably, this is a non-local equation, so the process is different from the It^{o} diffusion and a corresponding Fokker-Planck equation. We show that the normal and exponential distributions are solutions to this equation, on (;)(-\infty; \infty) and [0;)[0; \infty), respectively, both with variancee<sup>2</sup>At\text{variance} \sim e<sup>{2</sup> A t}, i.e. diffusion is highly anomalous. We numerically demonstrate for sigmoid-like functions on a segment that the entropy change rate dHdt\frac{d H}{d t} produced by such an optimal "diffusion" is, as expected, higher than produced by the "classical" diffusion.

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