Article
Physics, Fluids & Plasmas
Pierpaolo Bilotto, Lorenzo Caprini, Angelo Vulpiani
Summary: This study investigates the effect of coarse graining on the thermodynamic properties of a system by considering a one-dimensional colloidal particle in a sinusoidal potential driven out of equilibrium. Different levels of coarse graining were evaluated, revealing the impact of friction values on entropy production and the influence of inertia on jump statistics and average jump rate. The periodic shape of the potential allowed for the approximation of continuous dynamics via a Markov chain after introducing suitable time and space discretization.
Article
Quantum Science & Technology
Xiang Zhou
Summary: This paper presents a superposition measure with respect to coarse-grained measurement. The initial state used is a special kind of mixed state called the generalized n-qubit Werner state. By applying an appropriate coarse-graining to the initial state, it is found that the observational entropy and the von Neumann entropy are equal for any n. Furthermore, the difference between observational entropy and von Neumann entropy is studied for another coarse-graining, and it is found to satisfy the condition of superposition measure, indicating it can be regarded as a superposition measure with respect to a coarse-grained measurement. The characterizations of this superposition measure are investigated.
QUANTUM INFORMATION PROCESSING
(2023)
Article
Physics, Multidisciplinary
Tobias Denzler, Eric Lutz
Summary: The efficiency of small thermal machines is typically a fluctuating quantity. We analytically computed the joint characteristic functions for heat and work of two exemplary quantum heat engines, and found that work and heat are perfectly anticorrelated for generic scale-invariant quantum heat engines under adiabatic driving.
NEW JOURNAL OF PHYSICS
(2021)
Article
Physics, Multidisciplinary
Nikolaos Kalogeropoulos
Summary: We discuss aspects of coarse-graining in classical Statistical Physics in light of the symplectic non-squeezing theorem. We provide comments on the implications of this theorem for the BBGKY hierarchy. Furthermore, we demonstrate that the appearance of cubic cells in coarse-graining is a direct consequence of the uniqueness of Hofer's metric on the group of Hamiltonian diffeomorphisms of the phase space.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2022)
Article
Mathematics, Applied
Michel Moreau, Bernard Gaveau
Summary: This article investigates the relationship between the evolution of mesoscopic systems and entropy, finding that under certain conditions, mesoscopic systems can be approximated by Markov processes and introduces the concept of Kolmogorov entropy. It demonstrates the connection between Kolmogorov entropy and basic aspects of time, such as irreversibility.
Article
Physics, Multidisciplinary
Ashish Kumar, Anindya S. Chakrabarti, Anirban Chakraborti, Tushar Nandi
Summary: Distress propagation occurs in connected networks, with its rate and extent depending on network topology. Economic production networks exhibit different dynamical properties at different levels, with vulnerable modules leading to destabilization.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2021)
Article
Mathematics, Interdisciplinary Applications
Daria Stepanova, Helen M. Byrne, Philip K. Maini, Tomas Alarcon
Summary: Hybrid multiscale modeling is a useful framework for simulating complex biological phenomena. However, accounting for stochasticity in the internal dynamics of agents can lead to computationally expensive models. In this study, large deviation theory is used to reduce the computational cost of a spatially extended multiagent stochastic system with multistability by coarse-graining it to a continuous time Markov chain. The results show that the coarse-grained system exhibits the lowest computational cost while preserving the rich dynamics of the stochastic system.
MULTISCALE MODELING & SIMULATION
(2022)
Article
Thermodynamics
Hans Christian Oettinger, Mark A. Peletier, Alberto Montefusco
Summary: Understanding the fluctuations in phenomenological evolution equations with thermodynamic structure is crucial for a general framework of nonequilibrium statistical mechanics. These fluctuations provide an idealized representation of microscopic details and help evaluate dynamic material properties characterized by force-flux constitutive laws through statistical mechanics. Markov processes can be conveniently characterized by stochastic differential equations, leading to Green-Kubo-type formulas for dynamic material properties.
JOURNAL OF NON-EQUILIBRIUM THERMODYNAMICS
(2021)
Article
Physics, Fluids & Plasmas
William D. Pineros, Tsvi Tlusty
Summary: The paper demonstrates how to design complex nonequilibrium steady-state density distributions and flux field flows using the large-deviation behavior of a Brownian particle. The method is validated by replicating analytical results and showing the capacity to yield complex prescribed targets. This approach is considered a first step towards designing more complex NESS where general frameworks are lacking.
Article
Chemistry, Physical
Michael Bley, Joachim Dzubiella
Summary: The study focused on the non-equilibrium behavior during fast diffusion-influenced polymerization, examining the impact of excess free energy on the system properties through computer simulations and statistical mechanics concepts.
JOURNAL OF CHEMICAL PHYSICS
(2022)
Article
Computer Science, Interdisciplinary Applications
Joseph Bakarji, Daniel M. Tartakovsky
Summary: Statistical (machine learning) tools for equation discovery require large amounts of data, typically computer generated rather than experimentally observed. Learning on simulated data in areas such as multiscale modeling and stochastic simulations can lead to discovery. Our machine-learning strategy based on sparse regression replaces human discovery of models and can be executed in two modes.
JOURNAL OF COMPUTATIONAL PHYSICS
(2021)
Article
Chemistry, Physical
Marvin P. Bernhardt, Martin Hanke, Nico F. A. van der Vegt
Summary: In this paper, new Newton and Gauss-Newton methods for iterative coarse-graining based on integral equation theory are evaluated and extended, showing promising results in coarse-graining molecules to single beads and in systems with coarse-grained bonded interactions. The Gauss-Newton method with constraints is utilized to derive a model for single bead methanol in implicit water matching the osmotic pressure of the atomistic reference. All new methods are implemented in the open-source VOTCA package.
JOURNAL OF CHEMICAL PHYSICS
(2021)
Article
Physics, Fluids & Plasmas
Trevor GrandPre, Katherine Klymko, Kranthi K. Mandadapu, David T. Limmer
Summary: The study establishes a general lower bound on entropy production in interacting active matter systems, revealing a relationship between entropy and phase transitions in active matter models. It also explores factors affecting collective fluctuations and long-ranged correlations, shedding light on the dynamics of enhanced fluctuations and control mechanisms within the system.
Article
Physics, Fluids & Plasmas
Domingos S. P. Salazar
Summary: The detailed fluctuation theorem (DFT) provides a statement about the asymmetry in the statistics of entropy production. It has been found that the DFT imposes a negative tight lower bound for the skewness of entropy production as a function of the mean.
Article
Mechanics
Taiki Haga, Shin-ich Sasa
Summary: This study investigates the emergence of classical chaos from the microscopic description of quantum mechanics. By designing a quantum lattice system and taking an appropriate continuum limit, known as the 'Hamiltonian equation limit', the researchers simulate classical chaos in a quantum framework. A key concept in their analysis is the measurement of entanglement entropy between microscopic degrees of freedom within each block and the macroscopic degrees of freedom that define the large-scale structure of the wave function. Numerical simulations show that chaos only emerges in the Hamiltonian equation limit when the long-time average of the interscale entanglement entropy (IEE) becomes positive, and the initial growth rate of entropy is proportional to that of the coarse-grained Gibbs entropy in the corresponding classical system.
JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT
(2022)
Article
Chemistry, Physical
Nils E. Strand, Hadrien Vroylandt, Todd R. Gingrich
Summary: The study of Brownian ratchets has revealed the existence of a time-periodic steady state supported by time-periodic driving, which generates nonequilibrium transport. It is possible to rationalize the current in terms of the potential, even in systems with many interacting carriers.
JOURNAL OF CHEMICAL PHYSICS
(2022)
Article
Multidisciplinary Sciences
Marylou Gabrie, Grant M. Rotskoff, Eric Vanden-Eijnden
Summary: This article introduces an adaptive MCMC algorithm that enhances sampling from high-dimensional, multimodal probability distributions by using generative models as parameterized nonlocal transition kernels. The algorithm effectively samples across large free energy barriers and shows significant acceleration compared to traditional MCMC algorithms.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2022)
Article
Multidisciplinary Sciences
Alex Albaugh, Todd R. Gingrich
Summary: The authors simulated the movement of molecular motors under non-equilibrium conditions and developed a dynamic scheme to observe their cycles. By coarse graining the simulations, they identified inter-particle interactions that regulate the motor rates.
NATURE COMMUNICATIONS
(2022)
Article
Mathematics, Applied
G. M. Rotskoff, E. Vanden-Eijnden
Summary: This article investigates the global convergence conditions of the stochastic gradient descent (SGD) algorithm used in machine learning applications, as well as the relationship between error and network size. The study finds that, when using large-scale networks, the empirical distribution of particles descends to the global minimum at a fixed rate, resulting in a universal scaling of approximation error. The analysis also provides guidelines for the step size and batch size in training neural networks.
COMMUNICATIONS ON PURE AND APPLIED MATHEMATICS
(2022)
Article
Chemistry, Physical
Nils E. Strand, Hadrien Vroylandt, Todd R. Gingrich
Summary: We present an approach based on binary tree tensor network (BTTN) states for computing steady-state current statistics for a many-particle 1D ratchet subject to volume exclusion interactions. By combining BTTN states with the time-dependent variational principle (TDVP) algorithm, the steady-state behavior, including both typical and rare trajectories, can be obtained, which is also applicable to other interacting lattice models with time-dependent driving.
JOURNAL OF CHEMICAL PHYSICS
(2022)
Article
Chemistry, Physical
Jiawei Yan, Grant M. Rotskoff
Summary: In nonequilibrium statistical mechanics, the statistical distribution of dynamical observables provides information about the physical properties of a system driven away from equilibrium. However, for complex, interacting systems, analytical calculation is often not feasible, therefore robust numerical techniques are needed. In this article, an algorithm based on optimal control problem is proposed, and the optimal control forces are solved using neural network ansatz tailored to the physical systems, which leads to transferable and accurate solutions in two systems with large numbers of interacting particles.
JOURNAL OF CHEMICAL PHYSICS
(2022)
Editorial Material
Nanoscience & Nanotechnology
Todd R. Gingrich
NATURE NANOTECHNOLOGY
(2022)
Review
Chemistry, Physical
Gregory R. Bowman, Stephen J. Cox, Christoph Dellago, Kateri H. Dubay, Joel D. Eaves, Daniel A. Fletcher, Layne B. Frechette, Michael Grunwald, Katherine Klymko, JiYeon Ku, Ahmad K. Omar, Eran Rabani, David R. Reichman, Julia R. Rogers, Andreana M. Rosnik, Grant M. Rotskoff, Anna R. Schneider, Nadine Schwierz, David A. Sivak, Suriyanarayanan Vaikuntanathan, Stephen Whitelam, Asaph Widmer-Cooper
Summary: Phillip L. Geissler made significant contributions to the fields of biological polymers, heterogeneous materials, and chemical dynamics in aqueous environments. His analytical and computational methods have revealed the underlying organization of complex systems at the frontiers of biology, chemistry, and materials science.
ANNUAL REVIEW OF PHYSICAL CHEMISTRY
(2023)
Article
Chemistry, Physical
Shriram Chennakesavalu, David J. Toomer, Grant M. Rotskoff
Summary: Coarse-grained models are essential computational tools in theoretical chemistry and biophysics, providing physical insights and efficiency compared to atomistic models. Designing effective coarse-grained models is challenging, as the mapping from fine-grained to coarse-grained configurations is not optimized. In this work, we optimize both the representation and energy function, using a graph machine learning framework.
JOURNAL OF CHEMICAL PHYSICS
(2023)
Article
Chemistry, Physical
Hyun-Myung Chun, Jordan. M. M. Horowitz
Summary: We investigate the effects of logarithmic perturbations of reaction rates on chemical reaction networks driven far from equilibrium. Our findings show that the response of the average number of chemical species is limited by both number fluctuations and the maximum thermodynamic driving force. We provide evidence for these trade-offs in linear chemical reaction networks and a specific class of nonlinear chemical reaction networks with a single chemical species. Numerical results from various model systems suggest that these trade-offs hold for a wide range of chemical reaction networks, although their specific form seems to depend on the network's deficiency.
JOURNAL OF CHEMICAL PHYSICS
(2023)
Article
Physics, Multidisciplinary
Shriram Chennakesavalu, Grant M. Rotskoff
Summary: Controlling thermodynamic cycles to minimize dissipated heat is a long-standing goal in thermodynamics. This study introduces a framework for optimizing nonequilibrium control protocols that can transform a system between two distributions with minimal dissipation. The unified geometric framework is investigated in two model systems, showing robustness beyond linear response.
PHYSICAL REVIEW LETTERS
(2023)
Article
Multidisciplinary Sciences
Jeremy A. Owen, Jordan M. Horowitz
Summary: Living organisms benefit from molecular sensitivity in key processes like DNA replication and chemical sensing. A simple structural quantity, the size of perturbation support, limits the sensitivity of biological processes, whether at or away from thermodynamic equilibrium. A novel non-equilibrium binding mechanism, nested hysteresis, with exponential sensitivity relative to the number of binding sites, has been discovered.
NATURE COMMUNICATIONS
(2023)
Article
Multidisciplinary Sciences
Alex Albaugh, Geyao Gu, Todd R. Gingrich
Summary: Simulations can unravel the complex relationship between molecular structure and function. In this study, we demonstrate how slight changes in a molecular motor's structure can reverse its typical dynamic behavior using molecular simulations. These findings highlight the potential of molecular simulation in guiding the development of artificial molecular motors.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2023)
Article
Physics, Fluids & Plasmas
Rueih-Sheng Fu, Todd R. Gingrich
Summary: This study explores TUR-like bounds in overdamped and underdamped Langevin dynamics using large deviation theory, offering a new perspective and approach. It is found that current fluctuations achieved by scaling time can provide a deeper understanding of the relationship between current and dissipation in non-equilibrium systems.
Article
Physics, Fluids & Plasmas
Qi Gao, Hyun-Myung Chun, Jordan M. Horowitz
Summary: We analyze the static response to perturbations of nonequilibrium steady states modeled as one-dimensional diffusions on the circle. We demonstrate that arbitrary perturbations can be decomposed into combinations of three specific classes of perturbations that can be effectively addressed individually. For each class, we derive simple formulas that quantitatively characterize the response in terms of the strength of nonequilibrium driving, valid even far from equilibrium.
