Stochastic Annealing

TL;DR

This paper introduces a stochastic annealing method that enables simulation of systems in thermal equilibrium despite inexact energy evaluations, leveraging known error distributions for effective optimization.

Contribution

It presents a novel stochastic annealing approach that allows for thermal equilibrium simulation with approximate energy evaluations based on statistical sampling.

Findings

Effective optimization for systems with sampled energy evaluations.

Demonstrates thermal equilibrium simulation with known error distributions.

Applicable to problems with intractable exact energy computations.

Abstract

We demonstrate that is it possible to simulate a system in thermal equilibrium even when the energy cannot be evaluated exactly, provided the error distribution is known. This leads to an effective optimisation strategy for problems where the evaluation of each design can only be sampled statistically.