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DY: Fachverband Dynamik und Statistische Physik

DY 21: Stochastic Thermodynamics

DY 21.5: Vortrag

Dienstag, 10. März 2026, 10:30–10:45, ZEU/0114

Nonlinear Response Theory for Nonequilibrium Biochemical Networks — Ruicheng Bao¹ and •Shiling Liang^2,3,4 — ¹University of Tokyo, Tokyo, Japan — ²MPI-PKS, Dresden, Germany — ³MPI-CBG, Dresden, Germnay — ⁴CSBD, Dresden, Germany

Living cells process information through biochemical networks operating far from equilibrium. Understanding how these systems respond to finite perturbations, such as changes in enzyme concentrations or metabolic fluxes, is essential, yet the fluctuation-dissipation theorem applies only near equilibrium.

This talk introduces a framework that fills this gap. We derive an exact identity that links nonlinear responses to linear ones through a physically meaningful scaling factor, based on a connection between steady-state responses and mean first-passage times. This provides bidirectional inference: predicting global responses from local biochemical changes, and inferring metabolic costs from measurable observables. We also establish a universal response-resolution limit, a strong-perturbation analogue of the fluctuation-dissipation theorem, which sets fundamental bounds on signal detectability.

Using transcriptional regulation as an example, we show how these parameter-independent bounds constrain the computational expressibility of gene networks. Reliable detection of transcription factor changes requires fold-changes above a universal threshold. Overall, this framework defines general physical limits on cellular information processing, with implications for metabolic control and signal transduction.

Keywords: markov chain; stochastic thermodynamics; response relation; signal processing; stochastic inference