Article
Statistics & Probability
Jean-Marc Bardet, Paul Doukhan, Olivier Wintenberger
Summary: This paper extends the kernel-based estimation method to infinite-memory process models and proves the consistency and normality of the estimators. Experimental results demonstrate the efficiency of the estimators on both simulated and real data sets.
STOCHASTIC PROCESSES AND THEIR APPLICATIONS
(2022)
Article
Physics, Fluids & Plasmas
Jonathan Asher Pachter, Ken A. Dill
Summary: Important models in nonequilibrium statistical physics often make use of a commonly used, but frequently overlooked, near-equilibrium approximation. However, this approximation fails to hold in far-from-equilibrium systems. A more principled approach would involve deriving corrections for rate fluctuations from an underlying dynamical model, rather than assuming a particular form. Applying maximum caliber as the underlying principle, we derive such corrections for non-equilibrium processes, particularly important for heavily driven systems.
Review
Chemistry, Multidisciplinary
Marcus Muller, Volker Abetz
Summary: This passage discusses the application of porous polymer and copolymer membranes for ultrafiltration and water purification, as well as the formation of isoporous membranes using block copolymers. Understanding the spatiotemporal structure evolution and the interplay of multiple nonequilibrium processes is essential for optimizing membrane performance and fabrication processes.
Article
Chemistry, Physical
Faezeh Khodabandehlou, Christian Maes, Karel Netocny
Summary: We discuss when and why the steady nonequilibrium heat capacity vanishes with temperature using general arguments and examples. The framework of Markov jump processes on finite connected graphs is used, where the condition of local detailed balance helps identify the heat fluxes, and the discreteness enables a nondegenerate stationary distribution at absolute zero. Additionally, a dynamic condition is needed for the nonequilibrium extension of the Third Law to ensure that the low-temperature dynamical activity and accessibility of the dominant state remain sufficiently high.
JOURNAL OF CHEMICAL PHYSICS
(2023)
Article
Mathematics, Applied
Wenpo Yao, Jun Wang, Matjaz Perc, Wenli Yao, Jiafei Dai, Daqing Guo, Dezhong Yao
Summary: Through theoretical and experimental analyses, this paper emphasizes the strong similarities and close associations between time irreversibility and amplitude irreversibility measures. We clarify the connections of and the differences between the two types of permutation-based parameters for quantitative nonequilibrium, thereby bridging the concepts of amplitude irreversibility and time irreversibility, and expanding the selection of quantitative tools for studying nonequilibrium processes in complex systems.
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
(2021)
Article
Chemistry, Physical
Benjamin Lickert, Steffen Wolf, Gerhard Stock
Summary: This study establishes a Markovian Langevin model to reproduce the time evolution of nonstationary data from molecular dynamics simulations, discussing the sampling of free energy landscapes at equilibrium and the association of nonequilibrium processes with biased energy landscapes. The data-driven Langevin equation (dLE) approach is extended to modeling nonequilibrium processes efficiently, correctly accounting for various scenarios such as dissociation of sodium chloride in water, pressure-jump induced nucleation of hard sphere liquid, and sampling of helical peptides from nonstationary short trajectories.
JOURNAL OF PHYSICAL CHEMISTRY B
(2021)
Review
Physics, Multidisciplinary
Karl Friston, Lancelot Da Costa, Noor Sajid, Conor Heins, Kai Ueltzhoeffer, Grigorios A. Pavliotis, Thomas Parr
Summary: This paper provides a concise description of the free energy principle, starting from a formulation of random dynamical systems in terms of a Langevin equation and ending with a Bayesian mechanics that can be read as a physics of sentience. It rehearses the key steps using standard results from statistical physics. These steps entail (i) establishing a particular partition of states based upon conditional independencies that inherit from sparsely coupled dynamics, (ii) unpacking the implications of this partition in terms of Bayesian inference, and (iii) describing the paths of particular states with a variational principle of least action. Teleologically, the free energy principle offers a normative account of self-organisation in terms of optimal Bayesian design and decision-making, in the sense of maximising marginal likelihood or Bayesian model evidence. In summary, starting from a description of the world in terms of random dynamical systems, we end up with a description of self-organisation as sentient behaviour that can be interpreted as self-evidencing; namely, self-assembly, autopoiesis or active inference.
PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS
(2023)
Article
Physics, Multidisciplinary
J. Klinger, R. Voituriez, O. Benichou
Summary: We derive a universal and exact asymptotic form of the splitting probability for symmetric continuous jump processes, which highlights the importance of microscopic dynamics and provides explicit predictions for characterizing the effective random process in light scattering.
PHYSICAL REVIEW LETTERS
(2022)
Article
Statistics & Probability
Arnaud Poinas, Frederic Lavancier
Summary: This paper investigates a new approximation method for continuous determinantal point processes (DPPs) by examining the asymptotic behavior of the likelihood function as the observation window grows. This method is not limited to rectangular windows, is faster to compute than previous approaches, and does not require any tuning parameter. The paper provides theoretical justifications and an explicit formula for estimating the asymptotic variance of the associated estimator. The performance of the method is evaluated through simulation studies and compared to alternative estimation methods for continuous DPPs, showing favorable results.
SCANDINAVIAN JOURNAL OF STATISTICS
(2023)
Article
Multidisciplinary Sciences
Romuald Menuet, Raphael Meudec, Jerome Dockes, Gael Varoquaux, Bertrand Thirion
Summary: By statistically analyzing a large amount of brain activity data, we were able to successfully decode mental processes using machine learning models. This demonstrates the feasibility of image-based meta-analyses on a large scale with minimal manual data curation.
SCIENTIFIC REPORTS
(2022)
Article
Chemistry, Physical
Hong Gong, Yao Wang, Xiao Zheng, Rui-Xue Xu, YiJing Yan
Summary: In this work, we develop a method based on the dissipaton-equation-of-motion theory to evaluate the work distributions in quantum impurity system-bath mixing processes with non-Markovian and strong couplings. Our results accurately reproduce the Jarzynski equality and Crooks relation and provide rich information on large deviation.
JOURNAL OF CHEMICAL PHYSICS
(2022)
Article
Physics, Multidisciplinary
Paul C. Bressloff
Summary: A characteristic feature of stochastic processes under resetting is the convergence of probability density to a non-equilibrium stationary state, with a dynamical phase transition resembling a traveling front. In diffusion-based morphogenesis, an NESS is generated by a mechanism involving localized current sources and degradation, leading to protein concentration gradients. The calculation of accumulation time is a common method for characterizing relaxation processes in these systems.
JOURNAL OF PHYSICS A-MATHEMATICAL AND THEORETICAL
(2021)
Article
Biochemistry & Molecular Biology
Ambrosio Torres, Pablo A. Goloboff, Santiago A. Catalano
Summary: The study compared the results of three concatenated phylogenetic methods in 157 empirical datasets and found that the resulting trees were largely similar, with differences mostly in nodes of lower support. Most studies reached similar conclusions for the three methods, with discordance involving nodes considered challenging in systematics. The differences between methods were more prominent in datasets analyzing relationships at higher taxonomic levels, independent of the number of characters included in the datasets.
MOLECULAR PHYLOGENETICS AND EVOLUTION
(2021)
Article
Physics, Multidisciplinary
Taylor Firman, Jonathan Huihui, Austin R. Clark, Kingshuk Ghosh
Summary: Researchers have found that inference based on the Maximum Caliber principle is more efficient in extracting hidden information from single-cell stochastic gene expression time trajectories, compared to traditional modeling methods, demonstrating greater accuracy and computational efficiency.
Article
Biochemistry & Molecular Biology
Eric Johnson
Summary: Different models of protein folding have different mechanisms. The Foldon Hypothesis proposes a defined pathway, while the Max Cal method suggests a more heterogeneous process. Applying the Max Cal method to cytochrome c folding data, it was found that the folding process likely involves multiple pathways.
PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
(2022)