Bulletin of the American Physical Society
APS March Meeting 2020
Volume 65, Number 1
Monday–Friday, March 2–6, 2020; Denver, Colorado
Session A25: Thermodynamics of Biological and Artificial ComputationFocus

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Sponsoring Units: GSNP DCOMP Chair: David Wolpert, Santa Fe Inst Room: 402 
Monday, March 2, 2020 8:00AM  8:36AM 
A25.00001: Thermodynamics of Open Chemical Reaction Networks: Theory and Applications Invited Speaker: Massimiliano Esposito After formulating a nonequilibrium thermodynamics for open chemical reaction networks, the theory will be applied to assess the thermodynamics performance of a dissipative selfassembly scheme. Powerefficiency and noisedissipation tradeoffs will be discussed. 
Monday, March 2, 2020 8:36AM  8:48AM 
A25.00002: Universal thermodynamic bounds on nonequilibrium response with biochemical applications Jeremy Owen, Todd R Gingrich, Jordan Horowitz Diverse physical systems are characterized by their response to small perturbations. Near thermodynamic equilibrium, the fluctuationdissipation theorem provides a powerful theoretical and experimental tool to determine the nature of response by observing spontaneous equilibrium fluctuations. In this spirit, we derive a collection of equalities and inequalities valid arbitrarily far from equilibrium that constrain the response of nonequilibrium steady states in terms of the strength of nonequilibrium driving. Our work opens new avenues for characterizing nonequilibrium response. As illustrations, we show how our results rationalize the energetic requirements of common motifs in biochemical networks, with implications for the thermodynamics of information processing in biological systems. 
Monday, March 2, 2020 8:48AM  9:00AM 
A25.00003: TradeOffs between Error, Speed, Noise and Energy Dissipation in Biological Processes with Proofreading Joel Mallory, Anatoly Boris Kolomeisky, Oleg A Igoshin

Monday, March 2, 2020 9:00AM  9:12AM 
A25.00004: Observation of Stochastic Resonance in Transport of the DNA between Entropic Traps Shayan Lame We describe a nanofluidic system in which stochastic resonance (SR) could 
Monday, March 2, 2020 9:12AM  9:24AM 
A25.00005: Overdamped Brownian dynamics in piecewisedefined energy landscapes Ee Hou Yong, Thomas Gray We study the overdamped Brownian dynamics of particles moving in piecewisedefined potential energy landscapes U(x), where the height Q of each section is obtained from the exponential distribution p(Q) = aβ exp(−aβQ), where β is the reciprocal thermal energy, and a > 0. The averaged effective diffusion coefficient Deff is introduced to characterise the diffusive motion: <x^{2}> = 2 Deff t. A general expression for Deff in terms of U(x) and p(Q) is derived, and then applied to three types of energy landscape: flat sections, smooth maxima, and sharp maxima. All three cases display a transition between subdiffusive and diffusive behaviour at a = 1, and a reduction to free diffusion as a → ∞. The behaviour of Deff around the transition is investigated and found to depend heavily upon the shape of the maxima: energy landscapes made up of flat sections or smooth maxima display powerlaw behaviour, whilst for landscapes with sharp maxima, strongly divergent behaviour is observed. Two aspects of the subdiffusive regime are studied: the growth of the mean squared displacement with time, and the distribution of mean firstpassage times. 
Monday, March 2, 2020 9:24AM  9:36AM 
A25.00006: An EnergyAccuracy Tradeoff for Nonequilibrium Receptors Sarah Harvey, Subhaneil Lahiri, Surya Ganguli Living systems constantly collect and process information about their surroundings in order to respond to changes in the environment. In particular, single cells are capable of remarkably sensitive chemical concentration sensing using membranebound receptors. The physical limit of this sensing capability has been studied since the BergPurcell limit in 1977; however, thermodynamic constraints on the design of these sensors have remained theoretically elusive. Here we discuss two novel analytical bounds on signal estimation uncertainty in different limits of the observability of the sensing system. First, we consider estimating a signal based on a fully observable system trajectory, and second we study estimation based only on the coarsegrained occupation time of a subset of states. In the second, more biophysically plausible limit, we derive an energyaccuracy tradeoff for nonequilibrium processes using stochastic thermodynamics and large deviation theory. These lower bounds, supported by numerical simulations, reveal a theoretical limit on the estimation accuracy in terms of the energy consumption of the system and the observation time. 
Monday, March 2, 2020 9:36AM  9:48AM 
A25.00007: Functional Thermodynamics for Arbitrary Mawellian Ratchets Alexandra Jurgens, James P Crutchfield Autonomous Maxwellian demons use structured environments as a resource to generate work by randomizing ordered inputs and leveraging the increased Shannon entropy to transfer energy from a thermal reservoir to a work reservoir. To date, determining their functional thermodynamic operating regimes was restricted to information engines for which correlations among informationbearing degrees of freedom can be calculated exactly via compact analytical forms  a highly restricted set of engines. Although information engines may be represented as finite hidden Markov chains, (i) no finite expression for their Shannon entropy rate exists, (ii) the set of their predictive features is generically uncountably infinite, and (iii) their statistical complexity diverges. To solve the problems these pose, we adapt recent results from dynamical systems theory to efficiently and accurately calculate the entropy rates and the rate of statistical complexity divergence of general hidden Markov chains. The results allow for precise determination of the thermodynamic functionality of previouslystudied Maxwellian demons, as well as greatly expand the class of analyzable information engines. 
Monday, March 2, 2020 9:48AM  10:00AM 
A25.00008: TrajectoryClass Fluctuation Theorems: Work Decomposition in Metastable Information Processing Greg Wimsatt, Olli Saira, Alec Boyd, Matthew Matheny, Siyuan Han, Michael Roukes, James P Crutchfield Information processing is physical. It requires particular and precise control of the underlying thermodynamic system. While system parameters in a cyclic control protocol begin and end in the same configuration, their intermediate paths determine the evolution of the system's informational states. 
Monday, March 2, 2020 10:00AM  10:12AM 
A25.00009: Quantifying scaledependent irreversibility using persistent homology Leron Perez, Kabir Husain, Samir Chowdhury, Benjamin Schweinhart, Vahe Galstyan, Pankaj Mehta, Nikta Fakhri, Arvind Murugan Irreversibility is a measure of whether an observer can distinguish a process from its time reversed version. For physical systems, irreversibility is a fundamental property related to dissipation, breaking of detailed balance and nonequilibrium phenomena. But in any real nonequilibrium system, such as in vivo studies of oocytes or in vitro reconstituted actomyosin, irreversibility is associated with the specific timescales of the system’s nonequilibrium dynamics: an observer can be fooled into believing a process is reversible if they watch on the wrong timescales. Here, we generalize persistence homology, a scaledependent topological characterization method, to quantify irreversibility on different scales. While persistence homology is usually used to detect undirected loops, we define a similarity score inspired by statistical physics that captures information about directed circular fluxes. The resulting persistence barcode quantifies irreversibility on different timescales without any prior knowledge of what the relevant variables are. 
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