Fluctuation-Response Design Rules for Nonequilibrium Flows

TL;DR

This paper introduces a scalable method for designing nonequilibrium biological networks by adjusting local transition rates to meet global dynamical goals, utilizing the fluctuation-response duality in the Caliber Force Theory.

Contribution

It develops a scalable, systematic approach to network design in nonequilibrium systems using fluctuation-response duality, applicable to complex biological flows.

Findings

Reveals transition from timing- to branching-dominated fluctuations in kinesin motor models

Provides a scalable framework for network design in stochastic nonequilibrium systems

Offers new insights into the control of biological molecular machines

Abstract

Biological machines like molecular motors and enzymes operate in dynamic cycles representable as stochastic flows on networks. Current stochastic dynamics describes such flows on fixed networks. Here, we develop a scalable approach to network design in which local transition rates can be systematically varied to achieve global dynamical objectives. It is based on the fluctuation-response duality in the recent Caliber Force Theory -- a path-entropy variational formalism for nonequilibria. This approach scales efficiently with network complexity and gives new insights, for example revealing the transition from timing- to branching-dominated fluctuations in a kinesin motor model.