Bulletin of the American Physical Society
APS March Meeting 2019
Volume 64, Number 2
Monday–Friday, March 4–8, 2019; Boston, Massachusetts
Session P57: Noisedriven Dynamics in Farfromequilibrium Systems IFocus

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Sponsoring Units: GSNP DBIO Chair: Luis Bonilla Room: BCEC 256 
Wednesday, March 6, 2019 2:30PM  3:06PM 
P57.00001: Noiseinduced dynamics in farfromequilibrium electronic transport systems Invited Speaker: Stephen Teitsworth Bistable systems occur throughout the natural sciences and when such systems are subjected to noise, one observes probabilistic transitions between coexisting metastable states. Such behavior is found in chemical reaction kinetics, driven nonlinear mechanical systems, nonlinear electronic transport systems, climate dynamical models, and pulse propagation dynamics in neurons, to name but a few. In the case of electronic transport systems, experimental studies focus on probabilistic switching transitions between distinct states of electrical current flow in tunneling structures such as semiconductor superlattices and tunnel diodes. In particular, tunnel diode circuits provide an excellent experimental platform for the precision measurement of switching time statistics over a wide dynamic range. Furthermore, the measurement of mean switching times versus system parameters such as applied voltage near bifurcation points allows the determination of scaling behavior with remarkable precision. In related work, we have experimentally and theoretically studied linear electrical networks that are driven by nonthermal noise sources with a focus on the development of novel methods to characterize violations of detailed balance. Three methods of particular interest for experiments are: 1) construction of probability current from data, 2) stochastic area measurement, and 3) construction of statistical fluctuation loops. In this talk, we highlight the advantages and limitations of each of these approaches. 
Wednesday, March 6, 2019 3:06PM  3:18PM 
P57.00002: Learning force fields from stochastic trajectories Pierre Ronceray, Anna Frishman When monitoring the dynamics of microscopic systems, disentangling deterministic forces from thermal noise is challenging. Indeed, we show that there is an informationtheoretic bound on the rate at which information about the force field can be extracted from a trajectory. We propose a practical method, Stochastic Force Inference, that optimally uses this information to approximate force fields. This technique readily permits the evaluation of outofequilibrium currents and entropy production with a limited amount of data. 
Wednesday, March 6, 2019 3:18PM  3:30PM 
P57.00003: Noisedriven ionic currents in a viscosity gradient Derek Stein, Benjamin Wiener Gradients of voltage, pressure, temperature, or salinity can transport objects in micro and nanofluidic systems by wellknown mechanisms. I will describe the discovery of an electrokinetic transport effect driven by a viscosity gradient: An imposed liquid viscosity gradient causes an ionic current to flow inside a glass nanofluidic channel. Measurements of the current and numerical simulations reveal that the counterions in the electric double layers near the nanochannel surfaces drift in the direction of decreasing viscosity. The measurements are well described by a simple model in which the couterion drift speed equals the gradient of an ion’s local diffusivity. Drift in a viscosity gradient, or viscophoresis, is a consequence of multiplicative (statedependent) noise, where the magnitude of the thermal fluctuations experienced by a particle depends on its position. 
Wednesday, March 6, 2019 3:30PM  3:42PM 
P57.00004: Turning up the noise in nanofluidic channels Shayan Lame, Derek Stein We report an experimental technique to increase and control the diffusivity of individual DNA polymers in a nanofluidic environment. We applied white electrical noise with a Gaussian distribution of voltage fluctuations across nanofluidic slits containing fluorescently labeled DNA molecules. The effective diffusivity of the molecules in the direction parallel to the applied fields increased linearly with the noise power, reaching 19 times the thermal diffusivity with an applied noise amplitude of 36 V. This technique, which can subject DNA molecules to noise levels equivalent to 5300 K, enables us to experimentally investigate noisedriven dynamical phenomena in a previously inaccessible regime. 
Wednesday, March 6, 2019 3:42PM  3:54PM 
P57.00005: Intrinsic PinkNoise Multidecadal Global Climate Dynamics Mode Sahil Agarwal, Woosok Moon, John Wettlaufer Understanding multidecadal variability is an essential goal of climate dynamics. For example, the recent phenomenon referred to as the "global warming hiatus" may reflect a coupling to an intrinsic, preindustrial, multidecadal variability process. Here, using a multifractal timeseries method, we demonstrate that 42 data sets of 79 proxies with global coverage exhibit pinknoise characteristics on multidecadal timescales [1]. To quantify the persistence of this behavior, we examine highresolution ice core and speleothem data to find pink noise in both pre and postindustrial periods. We examine the spatial structure with an empirical orthogonal function analysis of the monthly averaged surface temperature from 1901 to 2012. The first mode clearly shows the distribution of ocean heat flux sinks located in the eastern Pacific and the Southern Ocean and has pinknoise characteristics on a multidecadal timescale. We hypothesize that this pinknoise multidecadal spatial mode may resonate with externally driven greenhouse gas forcing, driving largescale climate processes. 
Wednesday, March 6, 2019 3:54PM  4:06PM 
P57.00006: Nonlinear Transport Coefficient from Large Deviation Functions Chloe Gao, David Limmer Nonlinear response occurs naturally when a strong external perturbation takes a system far from equilibrium. While linear response can be directly related to equilibrium fluctuations, nonlinear response is difficult to predict in a general and efficient way. In this talk, we illustrate a method to compute arbitrarily high order transport coefficients of stochastic systems from derivatives of a large deviation function. We explore a selection of examples ranging from a single Brownian ratchet to thermal rectification in a massgraded FermiPastaUlam chain. Our method not only derives transport coefficients with relatively small statistical error, but also can be useful in studying mechanism by which nonlinear behavior arises. 
Wednesday, March 6, 2019 4:06PM  4:18PM 
P57.00007: Metabolic coupling of thermodynamics and mesoscopic stochastic fluctuations in an ATP chemostatted system Alexandru Bacanu, James Pelletier, Junang Li, Jordan Horowitz, Todd Gingrich, Nikta Fakhri Many biological systems act as ATP chemostats, maintaining a constant ATP chemical potential across numerous and variable free energy sources and sinks. It remains unclear how much free energy cells allocate to active mechanical fluctuations of the cytoplasm among other processes. To characterize nonequilibrium cytoskeletal mechanics, we imaged shape fluctuations of singlewalled carbon nanotubes (SWNTs) embedded in an actinintact Xenopus cytoplasmic extract. Normal mode decomposition of SWNT shape fluctuations resolved the spatial structure of myosindriven forces, which were not only stochastic, but also nonstationary due to dynamic remodeling of the actomyosin network. Based on the normal mode correlation functions, we defined metrics for nonequilibrium mechanical activity. To measure how active cytoskeletal mechanics depended on the ATP chemical potential and flux, we increased the ATP chemical potential via a phosphoenolpyruvate energy mix and decreased it via apyrasecatalyzed ATP hydrolysis. These passive measurements reveal how local nonequilibrium fluctuations of the cytoplasm respond to global thermodynamics and the ATP chemical potential. 
Wednesday, March 6, 2019 4:18PM  4:30PM 
P57.00008: Mutual information driven colloidal heat engine Govind Paneru, Sandipan Dutta, Tsvi Tlusty, Hyuk Kyu Pak We report on the direct measurement of the mutual information as a function of error size for a Brownian information engine operating in nonequilibrium steady state. Each engine cycle consists of the measurement of the particle position, feedback control, resetting of the particle position and relaxation. The measurement involves a Gaussian noise of controlled width. The performance of the information engine depends on the cycle period τ and the width of the noise N. The mutual information decreases with decrease in τ and increase in N, thereby reducing the amount of work extraction. Our system operates as a cooling or a heating device depending on the noise width. The efficiency of informationtowork conversion increases as the system is allowed to relax more at the end of each cycle. The maximum efficiency is obtained at the finite value of N. The generalized Jarzynski equality was found to be valid either when the initial state of the system is in thermal equilibrium, or when noise and signal width are equal. 
Wednesday, March 6, 2019 4:30PM  4:42PM 
P57.00009: Realization of an artificial active bath with controlled activity Jintae Park, Govind Paneru, Hyuk Kyu Pak We study the motion of a Brownian particle in artificially generated active bath. The particle is confined in a time dependent optical harmonic potential generated by optical tweezers. Therefore, the particle feels an external active noise in the background of a thermal white noise. This system is assumed to mimic the motion of a Brownian particle in active bath such as a bath of swimming bacteria. In comparison to the real bacterial bath experiments in which the activity parameters cannot be controlled easily, in this experiments the activity of the artificially generated active bath can be modulated in more controlled manner. Consequently, it allows us to study the thermodynamics of the Brownian particle in the active bath of various conditions. 
Wednesday, March 6, 2019 4:42PM  4:54PM 
P57.00010: Deformation of nonequilibrium limit cycle oscillators due to stochasticity Janaki Sheth Nonequilibrium dynamics are exhibited by numerous biological systems, often modeled as nonlinear oscillations driven by an internal energyconsuming process. Thermal processes lead to stochasticity in the measurements of their variables. Thus, experiments can only access the mean limit cycle, which may be different from the underlying zerotemperature one. This can lead to discrepancies between measurements and deterministic numerical models. 
Wednesday, March 6, 2019 4:54PM  5:06PM 
P57.00011: Numerical study for controlling surface roughening in KPZ growth process Priyanka ., Uwe Claus Tauber, Michel Pleimling The KardarParisiZhang (KPZ) equation has been used to describe growth processes in a variety of systems, and the corresponding exponents have been shown to prevail in both numerical models and experiments. Our objective in this work is to control the surface roughening for the KPZ growth process in (1+1) dimensions. We aim to saturate the surface roughness to the desired value using feedback control and try to understand the effect of the feedback control on the underlying dynamics. To this end, we apply a numerical integration scheme of the KPZ equation (with and without control) using the pseudospectral method. The numerical results show that controlling only a few small wave numbers leaves the system in the KPZ universality class. However, perturbing the wave numbers beyond a certain threshold changes the underlying kinetics, depending on the specific type of implemented (linear or nonlinear) control. 
Wednesday, March 6, 2019 5:06PM  5:18PM 
P57.00012: Selforganization in robot swarms and beyond Pavel Chvykov, William C Savoie, Zachary Jackson, Akash Vardhan, Kurt A Wiesenfeld, Jeremy L England, Daniel Goldman Swarms of interacting simple robots are interesting because of their potential for adapting rapidly to the demands of different group tasks. They also provide a playground for studying the physics of emergent selforganization. We studied a closely packed ensemble of periodically deforming simple robots, and observed the group to spontaneously organize into orderly patterns of collective motion. Viewing the collective as an emergent whole, we characterized its dynamics using an analysis originally developed for understanding fruitfly behaviors. Our findings point to design principles for the controlled stabilization of ordered behaviors in interacting systems. 
Wednesday, March 6, 2019 5:18PM  5:30PM 
P57.00013: Negative differential response of chemical reaction currents Gianmaria Falasco, Tommaso Cossetto, Emanuele Penocchio, Massimiliano Esposito Reaction currents in chemical networks can decrease when increasing their driving affinities. Such negative differential response (NDR), a hallmark of nonequilibrium physics, is found in reaction schemes of major biological relevance, namely, substrate inhibition and autocatalysis. We display it by deriving the full counting statistics of two minimal representative models by large deviation methods. We explore the consequences of NDR for biochemical networks in terms of precisiondissipation tradeoff and stability against external perturbations. Furthermore, we go beyond the realm of biochemistry and examine the relevance of NDR in artificial applications, showing how it limits the performance of dissipative selfassembly. 
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