Bulletin of the American Physical Society
APS March Meeting 2021
Volume 66, Number 1
Monday–Friday, March 15–19, 2021; Virtual; Time Zone: Central Daylight Time, USA
Session P08: Noise-Driven Dynamics in Far-From-Equilibrium Systems IFocus Live
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Sponsoring Units: GSNP DBIO Chair: Stephen Teitsworth, Duke University |
Wednesday, March 17, 2021 3:00PM - 3:36PM Live |
P08.00001: Unraveling the non-equilibrium dynamics of soft living matter Invited Speaker: Chase Broedersz Soft living systems such as cytoskeletal networks, membranes, and chromosomes are driven out of thermodynamic equilibrium by internal enzymatic activity. Measuring and characterizing the non-equilibrium properties in such systems is a major challenge, owing to the large number of interacting degrees of freedom. By observing the dynamics of such systems, we obtain stochastic trajectories. What can these noisy trajectories teach us about the underlying non-equilibrium physics of the system? Using several experimental examples, I will discuss how to extract information from steady-state fluctuations in active biological assemblies employing non-equilibrium measures such as phase space currents and entropy production rates. Based on a simple model, I will argue that the scaling behavior of such non-equilibrium measures can reveal physical properties of the internal driving. Finally, I will discuss a new tracking-free approach for the unsupervised analysis time-lapse microscopy data. To this end we developed Dissipative Component Analysis - a dimensional reduction scheme selecting a basis of modes based on dissipation. Subsequently, we learn the non-equilibrium dynamics in this reduced mode space, thereby estimating the entropy production rate and time-resolved force maps. we illustrate the applicability of our approach with an example inspired by active biopolymer gels. |
Wednesday, March 17, 2021 3:36PM - 3:48PM Live |
P08.00002: Bayesian Inference for Inertial Langevin Dynamics Federica Ferretti, Victor Chardès, Thierry Mora, Aleksandra Walczak, Irene Giardina Many living and complex systems exhibit second order emergent dynamics. Examples range from flocks and swarms, to bacterial propulsion, worm dynamics and cell migration experiments. A working description for these systems is given by stochastic underdamped equations. Limited experimental access to the inertial degrees of freedom poses a challenge in the quantitative reconstruction of the model, even in the case of equilibrium passive systems, as it makes the data appear to be generated by a non-Markovian process. We developed a novel analytical Bayesian approach to learn the parameters of such stochastic effective models from discrete finite-length trajectories. Naive approaches based on the estimation of derivatives through finite differences fail, yielding biased estimators regardless of the time resolution and length of the sampled trajectories. We derived, adopting a higher-order discretization, maximum-likelihood parameter estimators that provide worthy results even with moderately long trajectories. The method applies to a wide range of models, including nonlinear and nonstationary processes as well as to second-order models of collective motion, showing that reliable parameter estimators can be built also in the presence of interactions and for out-of-equilibrium systems. |
Wednesday, March 17, 2021 3:48PM - 4:00PM Live |
P08.00003: Nonequilibrium energy transduction in stochastic strongly coupled rotary motors Emma Lathouwers, Joseph Neil Lucero, David Sivak Living systems at the molecular scale are composed of many constituents with strong and heterogeneous interactions, operating far from equilibrium, and subject to strong fluctuations. These conditions pose significant challenges to efficient, precise, and rapid free energy transduction, yet nature has evolved numerous molecular machines that do just this. Using a simple model of the ingenious rotary machine FoF1-ATP synthase, we investigate the interplay between nonequilibrium driving forces, thermal fluctuations, and interactions between strongly coupled subsystems. This model reveals design principles for effective free energy transduction. Most notably, while tight coupling is intuitively appealing, we find that output power is maximized at intermediate-strength coupling, which permits lubrication by stochastic fluctuations with only minimal slippage. |
Wednesday, March 17, 2021 4:00PM - 4:12PM Live |
P08.00004: Using the fluctuation-response relations in biological limit-cycle oscillators to interrogate active feedback and control mechanisms Janaki Sheth, Dolores Bozovic, Alex Levine Biology is replete with complex, stochastic, nonlinear systems that exhibit steady-state limit-cycle dynamics driven by energy input. Many of these systems interact with various feedback and control mechanisms necessary for adaptation and/or homeostasis. We explore fluctuation dissipation relations in these noisy limit-cycle systems focusing primarily on the hair cells of the inner ear. These endogenously driven, overdamped oscillators are essential for both the sensitivity and frequency-selectivity of the auditory system. Using this model system, we demonstrate that there are two fundamental classes of noisy limit-cycle oscillators - ones in which the power input of the drive depends on the state of the system and ones where it does not. In the former case of an adaptive drive, we show that these systems violate a particular nonequilibrium fluctuation-response relation and propose that this failure is an important indicator of the presence of adaptive, control processes in biology. We also explore how one can derive a new fluctuation theorem that takes into account this feedback between the state of the noisy oscillator and its power input. This suggests that fluctuation analyses of these oscillators may provide a new window into understanding biological control and adaptation. |
Wednesday, March 17, 2021 4:12PM - 4:24PM Live |
P08.00005: Universal thermodynamic bounds on nonequilibrium response with biochemical applications Jeremy A Owen, Todd Gingrich, Jordan Horowitz Near thermodynamic equilibrium, the fluctuation-dissipation theorem provides a robust theoretical and experimental tool to determine the nature of response via spontaneous equilibrium fluctuations. Generalizations of the fluctuation-dissipation theorem for arbitrary perturbations around nonequilibrium steady states have offered fundamental theoretical insight, but often include observables that require detailed system-specific knowledge. Here, we suggest that an alternative fruitful method for characterizing nonequilibrium response is to study specific families of perturbations. For these families, we present equalities and inequalities valid arbitrarily far from equilibrium that constrain the response of nonequilibrium steady states in terms of the strength of nonequilibrium driving. As an illustration, we show how our results rationalize the energetic cost of a common biochemical switch. |
Wednesday, March 17, 2021 4:24PM - 4:36PM Live |
P08.00006: Collision of two cellular aggregates via active vertex model and topological data analysis Luis Bonilla, Ana Carpio, Carolina Trenado Yuste We have used an active vertex model for cells undergoing underdamped dynamics with active forces, Vicsek like alignment of cellular velocities and noise to study tumor invasion on epithelial tissue. Topological data analysis characterizes, tracks and compares tissue interfaces from numerical simulations and from experiments in an automatic manner. We obtain good agreement when normal cells are solid like and cancerous cells are liquid like according to their shape parameters and have appropriate junction tensions. |
Wednesday, March 17, 2021 4:36PM - 4:48PM Live |
P08.00007: Improved bounds on the entropy production rate in living systems Dominic Skinner, Jorn Dunkel Living systems maintain or increase local order, working against the second law. Thermodynamic consistency is restored as they dissipate heat, increasing the net entropy of their environment. Recently introduced estimators for the entropy production rate have provided major insights into the thermal efficiency of important cellular processes. In biological experiments, however, many degrees of freedom typically remain hidden to the observer, and in these cases, existing methods are not optimal. Here, by reformulating the problem within an optimization framework, we are able to infer improved bounds on the rate of entropy production from partial measurements of biological systems. Our approach yields provably optimal estimates given certain measurable transition statistics. In particular, it can reveal non-zero heat production rates even when non-equilibrium processes appear time symmetric and so may pretend to obey detailed balance. We demonstrate the broad applicability of this framework by providing improved bounds on the entropy production rate in a diverse range of biological systems including bacterial flagella motors, growing microtubules, and calcium oscillations within human embryonic kidney cells. |
Wednesday, March 17, 2021 4:48PM - 5:00PM Live |
P08.00008: Nonlinear dependence of desynchronization effects of coordinated reset on the number of stimulation sites and frequency Ali Khaledi Nasab, Justus Kromer, Peter A. Tass We study long-lasting desynchronization by coordinated reset (CR) stimulation in excitatory recurrent neuronal networks of integrate-and-fire neurons with spike-timing-dependent plasticity (STDP). We focus on the impact of the stimulation frequency and the number of stimulation sites on long-lasting effects. We compare theoretical predictions to simulations of plastic neuronal networks. We reveal that long-lasting effects become most pronounced when stimulation parameters are adjusted to the characteristics of STDP, rather than to neuronal frequency characteristics. This is in contrast to previous studies where the CR frequency was adjusted to the dominant neuronal rhythm. Also, we show a nonlinear dependence of long-lasting effects on the number of stimulation sites and the CR frequency. Intriguingly, optimal long-lasting desynchronization does not require larger numbers of stimulation sites. Our results indicate that tuning the spatial resolution of lead electrodes and stimulation parameters may help to exploit neuronal plasticity for long-lasting therapeutic effects. |
Wednesday, March 17, 2021 5:00PM - 5:12PM Live |
P08.00009: Mean Field Theory for Generalized Cortical Branching Model Naruepon Weerawongphrom, Jeremy Goetz, Rashid Williams-Garcia, John Beggs, Gerardo Ortiz The brain is a complex, far-from-equilibrium dynamical system consisting of diverse populations of neurons and neurotransmitters. One of the interesting behaviors observed in the mammalian brain are neuronal avalanches, which are partly explained by the Cortical Branching Model (CBM), a many-body model consisting exclusively of excitatory neurons. Here, we develop a generalized CBM (GCBM) to incorporate inhibitory neurons and their varied motifs of interaction. To gain understanding and predict behavior of this many-body system, we develop a method to generate mean-field approximations for any given motif with or without inhibition. This mean-field theory allows us to produce dynamical maps from basic interactions among excitatory and inhibitory neurons, from which it will be possible to study corresponding phase diagrams and nonequilibrium phase transition of the GCBM. |
Wednesday, March 17, 2021 5:12PM - 5:24PM Live |
P08.00010: The unreasonable effectiveness of cluster scaling Sakib Matin, Thomas Namse Tenzin, William Klein, Harvey A Gould Equilibrium statistical mechanics requires assumptions such as a Hamiltonian description and ergodicity. Nevertheless, the tools of statistical mechanics have been successfully applied to models in biology and economics. We generalize the Fisher-Stauffer cluster scaling (from percolation theory) to study the avalanches in the nearest-neighbor stochastic Olami-Feder-Christensen (OFC) model, which is believed to be a non-equilibrium system. The OFC model is a two-dimensional lattice of leaky integrate-and-fire(IF) sites. The strength of the noise determines if OFC model is effectively ergodic or non-ergodic. We show that the limit of vanishing dissipation corresponds to a critical point. The Fisher-Stauffer scaling holds when the OFC model is effectively ergodic. We derive universal scaling functions for the avalanche distributions and dynamics. However, the cluster scaling breaks down when the OFC model is non-ergodic, and the system may be characterized by a multi-fractal scaling distribution with infinitely many critical exponents. Our results raise the question whether a Hamiltonian description exists for certain stochastic IF systems. Our work indicates that effective ergodicity may be a sufficient criterion for the validity of cluster scaling methods. |
Wednesday, March 17, 2021 5:24PM - 5:36PM Live |
P08.00011: A theoretical model for viscophoresis: transport in a liquid viscosity gradient Derek Stein, Benjamin N Wiener, Shayan Lame We recently discovered that imposing a viscosity gradient within a nanofluidic channel made of glass causes ionic current to flow. The current is evidently carried by positively charged counterions in the electric double layers near the channel walls drifting toward the lower viscosity side. We present an explanation based on the Maxwell-Stefan (MS) theory of diffusion. Within the MS theory, transport of a given species is driven by a gradient in its chemical potential, and that driving force is balanced by a friction force with every other molecular species. Relating the MS theory to our nanofluidic experiments, we consider a viscous fluid, a thin fluid, and counterions. The viscous and thin components of the mixture flow in opposite directions inside the channel, and as they do, each one exerts a frictional force on the counterions. There is a net motion of those counterions in the direction of decreasing viscosity because the drag coefficient with the viscous component is larger than the coefficient with the thinner component. There is also no mystery where the energy to drive the current comes from: It comes from the free energy of mixing of the viscous and thin fluids. |
Wednesday, March 17, 2021 5:36PM - 5:48PM Live |
P08.00012: Passive colloids reveal a wet to dry crossover in active bacterial suspensions Shreyas Gokhale, Junang Li, Alexandre Solon, Jeffrey Chen Gore, Nikta Fakhri Disentangling the role of long-ranged hydrodynamics and short-ranged steric interactions in suspensions of self-propelled particles poses a significant challenge in active matter physics. Here, by analyzing the structure and dynamics of passive colloids immersed in active suspensions of motile bacteria, we reveal the existence of two distinct regimes dominated by hydrodynamic and steric interactions respectively. In dilute bacterial suspensions, dynamic correlations between colloids evolve continuously with increasing density whereas in concentrated suspensions, they are density independent. Furthermore, in concentrated bacterial suspensions, nonequilibrium depletion interactions mediated by collisions with bacteria give rise to strong effective attraction between colloids. Simulations of active and passive Brownian particles without hydrodynamics show excellent agreement with experimental data in dense suspensions but fail to capture the observed phenomenology in dilute ones. Collectively, our findings uncover a crossover from fluid-mediated to collision-mediated interactions that not only influences the dynamics of the active fluid itself, but also reveals novel nonequilibrium phenomena in passive systems that are in contact with it. |
Wednesday, March 17, 2021 5:48PM - 6:00PM Live |
P08.00013: Inverse Design of Non-equilibrium Steady-States: A Large Deviation Approach William David Piñeros, Tsvi Tlusty The design of small scale non-equilibrium steady states (NESS) is a challenging, open ended question. While similar equilibrium problems are tractable using standard thermodynamics, a generalized description for non-equilibrium systems is lacking, making the design problem particularly difficult. Here we make use of the large deviation behavior of a Brownian particle, and design a variety of geometrically complex steady-state density distributions and flux field flows. We achieve this design target from direct knowledge of the joint large deviation functional for the empirical density and flow, and a “relaxation” algorithm of the desired target states via adjustable force field parameters. We validate the method by replicating analytical results, and demonstrate its capacity to yield complex prescribed targets, such as those whose occupation and flux trace-out rose-curve or polygonal shapes. We consider this dynamical fluctuation approach a first step towards the design of more complex NESS where generalized frameworks are otherwise still lacking. |
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