Inferring broken detailed balance in the absence of observable currents

Abstract

Identifying dissipation is essential for understanding the physical mechanisms underlying nonequilibrium processes. In living systems, for example, the dissipation is directly related to the hydrolysis of fuel molecules such as adenosine triphosphate (ATP). Nevertheless, detecting broken time-reversal symmetry, which is the hallmark of dissipative processes, remains a challenge in the absence of observable directed motion, flows, or fluxes. Furthermore, quantifying the entropy production in a complex system requires detailed information about its dynamics and internal degrees of freedom. Here we introduce a novel approach to detect time irreversibility and estimate the entropy production from time-series measurements, even in the absence of observable currents. We apply our technique to two different physical systems, namely, a partially hidden network and a molecular motor. Our method does not require complete information about the system dynamics and thus provides a new tool for studying nonequilibrium phenomena.

Irreversibility in dynamical phases and transitions

“…If X is already coarse-grained, multiple microscopic trajectories will be indistinguishable and Eq. ( 1 ) will underestimate the true entropy production rate due to the data processing inequality 19 , 45 , 46 .…”

How Dissipation Constrains Fluctuations in Nonequilibrium Liquids: Diffusion, Structure, and Biased Interactions

“…A direct implication is that the rate of work can now be inferred simply by measuring static density correlations, provided that the pair-wise interaction potential is known, for a given driven liquid. Importantly, such an approach does not require any invasive methods based on comparing fluctuations and response [54][55][56][57][58], and it does not rely on a detailed analysis of particle trajectories [60,61] or currents in phase space [59,62], whose experimental implementation can require elaborate techniques [3,4].…”

“…We demonstrate that this result holds both for fluids in which a fraction of the particles are driven by a fixed external drive and for fluids in which either a fraction of the liquid or the entire liquid is driven by an internal noise, analogous to the driving used in model active matter systems. This result opens the door to estimating dissipation directly from the liquid structure, in contrast with previous approaches based either on perturbing the system [54][55][56][57][58] or on analyzing trajectories and currents in phase space [3,[59][60][61][62]. We illustrate this with numerical simulations for which dissipation is quantified by the deviation from equilibrium tracer-bath correlations.…”

Learning the non-equilibrium dynamics of Brownian movies

“…In addition to thermal effects, active processes can strongly impact the stochastic dynamics of a system 8 – 12 . Recently, there has been a growing interest in quantifying and characterizing the non-equilibrium nature of the stochastic dynamics in active soft and living systems 13 – 25 . In cells, molecular-scale activity, powered for instance by ATP hydrolysis, controls mesoscale non-equilibrium processes in assemblies, such as cilia 26 , 27 , flagella 28 , chromosomes 29 , protein droplets 30 , or cytoskeletal networks 31 – 34 .…”