Bulletin of the American Physical Society
APS March Meeting 2020
Volume 65, Number 1
Monday–Friday, March 2–6, 2020; Denver, Colorado
Session G24: Noise-Driven Dynamics in Far-From-Equilibrium Systems II |
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Sponsoring Units: GSNP DBIO Chair: Jeffrey Weiss, University of Colorado, Boulder Room: 401 |
Tuesday, March 3, 2020 11:15AM - 11:27AM |
G24.00001: Minimal Model for Intermittent Dynamics and "Turbulence" in Many-Body Systems Guram Gogia, Wentao Yu, Justin Burton
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Tuesday, March 3, 2020 11:27AM - 11:39AM |
G24.00002: Stochastic transitions between phase-locked steady states in RF-irradiated graphene Josephson junctions Trevyn Larson, Lingfei Zhao, Ethan Arnault, Ming-Tso Wei, Andrew Seredinski, Hengming Li, Kenji Watanabe, Takashi Taniguchi, Francois Amet, Gleb Finkelstein We investigate the Shapiro steps in a graphene-based Josephson junction with large gap MoRe leads. A wide variety of patterns are obtained, depending on the carrier density, temperature, RF frequency, and magnetic field. A particularly interesting regime of intermediate driving power is identified, in which the zero voltage state becomes unstable even at zero bias, and the junction spontaneously develops a voltage V=±~hf/2e, which could persist for a several hours. We study the switching time between the ±~hf/2e states as a function of applied power and temperature, and find a novel non-monotonic regime, in which the switching time between these attractors demonstrates a pronounced minimum at intermediate temperatures. |
Tuesday, March 3, 2020 11:39AM - 11:51AM |
G24.00003: Understanding Stochastic Dynamics in Classical and Quantum Metastable Condensed Matter Systems Bernardo Spagnolo The noise-driven dynamics of three far-from-equilibrium systems are investigated: (i) transient dynamics in unstable potential and in Josephson junctions with Lévy noise; (ii) escape from a quantum dissipative metastable state in the presence of an external driving; (iii) the switching dynamics in a stochastic model of memristor. |
Tuesday, March 3, 2020 11:51AM - 12:03PM |
G24.00004: Anomalous Phase Dynamics of Driven Graphene Josephson Junctions Sandesh Kalantre, Fan Yu, Ming-Tso Wei, Kenji Watanabe, Takashi Taniguchi, MIguel Hernandez-Rivera, Francois Amet, James Williams
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Tuesday, March 3, 2020 12:03PM - 12:15PM |
G24.00005: A theoretical model for ionic transport in a viscosity gradient Derek Stein, Benjamin N Wiener We recently discovered that imposing a viscosity gradient across 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 fluid comprising 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. |
Tuesday, March 3, 2020 12:15PM - 12:27PM |
G24.00006: Pulling cargo increases the precision of molecular motor progress Aidan Ivar Brown, David Sivak Biomolecular motors use free energy to drive a variety of cellular tasks, including the transport of cargo, such as vesicles and organelles. We find that the widely used "constant-force" approximation for the effect of cargo on motor dynamics leads to a much larger variance of motor step number compared to explicitly modeling diffusive cargo, suggesting the constant-force approximation may be misapplied in some cases. We also find that, with cargo, motor progress is significantly more precise than suggested by a recent result. For cargo with a low relative diffusivity, the dynamics of continuous cargo motion—rather than discrete motor steps—dominate, leading to a new, more permissive bound on the precision of motor progress which is independent of the number of stages per motor cycle. |
Tuesday, March 3, 2020 12:27PM - 12:39PM |
G24.00007: Spectral method for estimating entropy production rates in spatially extended systems Daniel Seara, Benjamin B Machta, Michael Murrell Due to the lack of symmetries and variational principles, non-equilibrium systems have been difficult to treat theoretically. Recent work has focused on measuring entropy production rates as a measure of a system's distance from equilibrium, but little connection has been made between entropy production and the complex, spatiotemporal dynamics that arise at different time and length-scales in driven systems. We present a generic method for estimating entropy production rates from stochastic time series data for both random variables and fields while providing insight into the dissipative processes underlying their dynamics. Our method provides insight into the relationship between pattern formation and dissipation in mesoscopic, driven reaction-diffusion systems. Importantly, this technique does not depend at all on the underlying system and can be used with data in any number of spatial dimensions. |
Tuesday, March 3, 2020 12:39PM - 12:51PM |
G24.00008: Learning the Non-Equilibrium Dynamics of Brownian Movies Federico Gnesotto, Grzegorz Gradziuk, Pierre Ronceray, Chase Broedersz Soft living systems such as cytoskeletal networks, membranes, and tissues are driven out of thermodynamic equilibrium by internal enzymatic activity. Measuring and characterizing the non-equilibrium properties in these systems is a major challenge, owing to the large number of interacting degrees of freedom. Typically, the experimental characterizations of such systems rely on tracking the trajectories of embedded or endogenous probes. However, it is not clear how to select appropriate tracer probes and how this choice affects the resulting characterization; in general, it is unknown a priori which degrees of freedom are most informative about non-equilibrium activity in the system. In this talk, we present a new approach that does not rely on the tracking of probes in the system. Instead, we directly learn the non-equilibrium dynamics from a Brownian movie of a fluctuating soft assembly, yielding force fields and entropy production rates. Our approach is based on a principled analysis that reduces the dimensionality of the system by identifying the most dissipative components. We will discuss how this approach performs in different scenarios inspired by cytoskeletal networks. |
Tuesday, March 3, 2020 12:51PM - 1:03PM |
G24.00009: Spectral decomposition of irreversibility reveals structure of nonequilibrium activity in biological systems Alexandru Bacanu, James F Pelletier, Yoon Jung, Jordan Horowitz, Nikta Fakhri Biological systems, such as cytoskeletal networks, exhibit stochastic mechanical fluctuations on mesoscopic scales which can violate detailed balance. The spatiotemporal structure of nonequilibrium activity on these scales remains unexplored, due to a lack of methods able to reliably quantify irreversibility. To probe activity in both space and time, we image spatially extended single-walled carbon nanotubes (SWNTs) embedded in actin-intact Xenopus cytoplasmic extract. Using normal mode decomposition of filament shape fluctuations, we infer the structure of the actomyosin-driven mechanical fluctuations. Metrics for irreversibility based on normal mode correlation functions quantify the spatiotemporal extent of nonequilibrium activity. To estimate the noise floor of our analysis, we compare our results to the fluctuations of SWNTs in an equilibrium, entangled F-actin gel. By altering network architecture and generating chemostatted ATP reservoirs, we probe the response of nonequilibrium activity to distinct perturbations. Our analysis quantifies the spatiotemporal structure of irreversibility on mesoscopic scales and shows it is affected by network mechanics and its coupling to the ATP chemical reservoir. |
Tuesday, March 3, 2020 1:03PM - 1:15PM |
G24.00010: Noisy driven oscillators: Adaptive drives break the fluctuation-dissipation theorem Janaki Sheth, Alex Levine, Dolores Bozovic The steady-state dynamics of complex nonlinear systems include limit cycles in which the dynamic variables trace a closed path in phase space. Biological systems are replete with examples of such driven oscillators in a diverse range of systems including circadian rhythms, neuronal central pattern generators, and the active mechanics of hearing. These biological systems are inherently noisy, and they are typically controlled by active feedback. We explore the fluctuations and response functions of intrinsically noisy limit-cycle oscillators starting with models of stereocilium dynamics in the inner ear. We show that one can obtain a generalized fluctuations-dissipation theorem (GFDT) for the system in a reference frame comoving with the mean dynamical state moving about the limit cycle. However, in the presence of adaptive drives where there is feedback so that the energy input driving the oscillator depends on the state of the system, as in the driven stereocilium, even these generalized fluctuation theorems fail. We further explore the essential role of these feedback mechanisms in breaking GFDTs in noisy driven systems using a combination of simple computational models, analytical calculations, and stereocilium dynamics data. |
Tuesday, March 3, 2020 1:15PM - 1:27PM |
G24.00011: A generalized theory of interactions for complex multiscale stochastic systems with thermodynamic irreversibility Santiago Núñez-Corrales, Eric Jakobsson Understanding nonlinear, hierarchically structured complex systems through the discovery and application of statistical mechanics principles remains a significant challenge. Considering thermodynamic irreversibility is simultaneously essential and often intractable in these cases. Additionally, the presence and filtering of noise across scales often translates into stochastic differential equations for the dynamics, a theoretically and computationally onerous task. We present ongoing work towards a novel mathematical physics development that aims to capture statistical mechanical properties of complex multiscale stochastic systems driven by irreversible thermodynamics, a generalized theory of interactions (GToI) with a purely relational view in which interactions are fundamental entities, while objects and laws are derived. We show how these can be instantiated into concrete theories of interaction (CToIs) capable of capturing key ensemble properties. We exemplify its application to unveiling the underlying complexity of gases and discuss some aspects of its relation to differential models, including relevant computational considerations. |
Tuesday, March 3, 2020 1:27PM - 1:39PM |
G24.00012: Non-equilibrium response of a strongly coupled rotary motor Emma Lathouwers, Joseph N. E. Lucero, David Sivak Living systems at the molecular scale are complex (composed of many constituents with strong and heterogeneous interactions), far from equilibrium, and subject to strong fluctuations. This poses 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 FoF1-ATP synthase (the primary motor for ATP synthesis), we investigate the interplay between non-equilibrium driving forces, natural equilibrium fluctuations, and interactions between the strongly coupled subsystems of this ingenious rotary machine. Additionally, we consider the resulting design principles for effective free energy transduction. Most notably, while one would naively assume that tight coupling between subsystems is preferred, we find that the output power is maximized at intermediate-strength coupling, which permits lubrication by stochastic fluctuations with only minimal slippage. |
Tuesday, March 3, 2020 1:39PM - 1:51PM |
G24.00013: Stochastic Dynamics and Selection in the One Dimensional Stabilized Kuramoto-Sivashinsky Equation Saloni Saxena, John Michael Kosterlitz Many spatially extended nonlinear systems are known to exhibit coarsening - starting from an initial uniform (disordered) state, ordered structures appear, the size of which increases with time. We study coarsening dynamics in the stabilized Kuramoto-Sivashinsky (SKS) equation in one dimension, with and without noise. The SKS equation is used to describe the growth of crystal surfaces, in particular the motion of terrace edges in step-flow growth [1]. The key feature of this equation is that it displays a bifurcation from a uniform steady state to a band of periodic states, depending on the control parameter. Coarsening is studied by analyzing the time evolution of the structure function for a range of control parameter values, starting from a uniform initial state. We find that the width of the structure function decays as a power law with time during an intermediate time regime, until a narrow peak centered at a given wave number is obtained. This is consistent with the emergence of an ordered (periodic) state which grows in spatial extent. We calculate the decay exponents and discuss the influence of the noise amplitude on the values of the exponents. We also make connections with wave number selection. |
Tuesday, March 3, 2020 1:51PM - 2:03PM |
G24.00014: Maxwell's demons with finite size and response time Nathaniel Rupprecht, Dervis Vural Nearly all theoretical analyses of Maxwell’s demon focus on its energetic and entropic costs of operation. Here, we focus on its rate of operation. In our model, a demon’s rate limitation stems from its finite response time and gate area. We determine the rate limits of mass and energy transfer, as well as entropic reduction for four such demons: those that select particles according to (1) direction, (2) energy, (3) number, and (4) entropy. Last, we determine the optimal gate size for a demon with small, finite response time, and compare our predictions with molecular dynamics simulations with both ideal and nonideal gasses. |
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