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Nonlinear Response Relations and Fluctuation-Response Inequalities for Nonequilibrium Stochastic Systems
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Predicting how systems respond to external perturbations far from equilibrium remains a fundamental challenge across physics, chemistry, and biology. We present a unified response framework for stochastic Markov dynamics that integrates linear and nonlinear perturbations. Our formalism expresses nonlinear responses of observables in terms of the covariance between the observable and a nonlinear conjugate variable. The nonlinear conjugate variable is subject to the complete Bell polynomial form and is determined by the stochastic entropy production. In addition, the Fluctuation-Response Inequalities (FRIs) are also derived for nonlinear responses, unraveling the general trade-off relations between nonlinear response and systems' fluctuations far from equilibrium. The validity of our theory is verified by the numerical results from a symmetric exclusion process (SEP). By unifying and extending nonequilibrium linear response theories, our approach can provide principled design rules for sensitive, adaptive synthetic and biological networks.
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Cited by 2 Pith papers
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Mutual Linearity in and out of Stationarity for Markov Jump Processes: A Trajectory-Based Approach
A trajectory-level derivation shows mutual linearity holds for non-stationary Markov jump processes and generalizes to other systems.
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Mutual Linearity in Nonequilibrium Langevin Dynamics
Local perturbations in nonequilibrium Langevin dynamics induce linear relations between stationary densities and currents at different positions due to an underlying one-dimensional response structure.
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