An efficient algorithm to estimate the potential barrier height from noise-induced escape time data

TL;DR

This paper introduces an efficient iterative algorithm to estimate the potential barrier height from noise-induced escape times, optimizing experimental resource use by relating noise strength to barrier height.

Contribution

It presents a novel iterative method for estimating potential barrier heights from escape time data, optimizing noise strength control for resource-efficient experiments.

Findings

The optimal noise strength is directly related to the potential barrier height.

The proposed iterative method improves estimation accuracy with limited resources.

The algorithm is applicable in systems where noise control is feasible.

Abstract

It is a common phenomenon in nature and technology that a system under perturbations exits a regime of its usual dynamics. Often it is possible to define a potential function whereby a potential well can be associated with a usual or persistent dynamics, and a potential barrier needs to be overcome to escape the regime associated with the usual dynamics. We develop an algorithm to determine the potential barrier height experimentally, provided that we have control over the noise strength. We are concerned with the situation when the experiment requires large resources of time or computational power, and wish to find a protocol that provides the best estimate in a given amount of time. The optimal noise strength to use is found to be very simply related to the potential barrier height, and we propose an iterative method for the estimation.