A fluctuation-sensitivity-timescale trade-off in feedback-controlled dynamics

TL;DR

This paper reveals a fundamental trade-off in feedback-controlled networks where reducing fluctuations inevitably compromises sensitivity or response speed, with bounds varying between gradient and non-gradient systems, impacting information transmission.

Contribution

It analytically derives a universal trade-off among fluctuation, sensitivity, and timescale in feedback-controlled dynamics, highlighting fundamental limits in regulatory network performance.

Findings

Feedback control cannot infinitely suppress fluctuation without reducing sensitivity or response speed.

The lower bound of the trade-off is halved in non-gradient systems compared to gradient systems.

Numerical simulations confirm the tightness of the derived trade-off in high-dimensional nonlinear systems.

Abstract

Feedback control is a renowned mechanism for attenuating intrinsic fluctuation in regulatory networks. However, its impact on the response sensitivity to external signals and the response timescale, which are also critical for signal transmission, has yet to be understood. In this letter, we study a general feedback-controlled network in which the feedback is achieved by a complex interactive module. By comparing the solution of Langevin equations with and without feedback, we analytically derive a fundamental trade-off between fluctuation, sensitivity, and timescale altered by the feedback. We show that feedback control cannot infinitely suppress fluctuation without the cost of reducing sensitivity or response speed. Furthermore, the lower bound for this trade-off can be reduced up to half in non-gradient dynamical systems compared to gradient systems. We validate this trade-off as a tight bound for high-dimensional systems in nonlinear regime through numerical simulations. These results elucidate the fundamental limitation of feedback control in enhancing the information transmission capacity of regulatory networks.