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We introduce a unified framework for analyzing Markov dynamics by linking nonequilibrium thermodynamics with information geometry. Using the symmetrized Kullback-Leibler divergence, we reveal an intrinsic Minkowski structure in the…

Statistical Mechanics · Physics 2025-05-08 David Andrieux

We consider a finite-state, continuous-time Markov process, represented in the "linear framework" by a directed graph with labelled edges which specifies the infinitesimal generator of the process. If the graph is strongly connected, the…

Biological Physics · Physics 2023-10-17 Ugur Cetiner , Jeremy Gunawardena

To characterize the Kullback-Leibler divergence and Fisher information in general parametrized hidden Markov models, in this paper, we first show that the log likelihood and its derivatives can be represented as an additive functional of a…

Statistics Theory · Mathematics 2023-03-15 Cheng-Der Fuh , Chu-Lan Michael Kao , Tianxiao Pang

We study transient nonequilibrium dynamics in Fisher-regularized Wasserstein gradient flows and identify a sign-changing cross-dissipation mechanism generated by the coupling between transport dissipation and Fisher-information geometry.…

Statistical Mechanics · Physics 2026-05-29 Michael Farmer , Abhinav Kochar , Yugyung Lee

In macroscopic systems behavior is usually reproducible and fluctuations, which are deviations from the typically observed mean values, are small. But almost all inverse problems in the physical and biological sciences are ill-posed and…

Statistical Mechanics · Physics 2017-08-09 Peter Burgholzer

We present a statistical mechanical framework based on the Kullback-Leibler divergence (KLD) to analyze the relativistic limits of decoding time-encoded information from a moving source. By modeling the symbol durations as…

Mathematical Physics · Physics 2025-07-31 Tatsuaki Tsuruyama

In a transition between nonequilibrium steady states, the entropic cost associated with the maintenance of steady-state currents can be distinguished from that arising from the transition itself through the concepts of excess/housekeeping…

Quantum Physics · Physics 2025-09-23 Artur M. Lacerda , Laetitia P. Bettmann , John Goold

This paper illustrates novel methods for nonstationary time series modeling along with their applications to selected problems in neuroscience. These methods are semi-parametric in that inferences are derived by combining sequential…

Applications · Statistics 2010-11-03 Fabio Rigat , Jim Q. Smith

This study aims to quantify and visualize the degradation of fidelity (information degradation) that inevitably accompanies the replication of information within the framework of information thermodynamics and to propose an…

Mathematical Physics · Physics 2025-11-20 Tatsuaki Tsuruyama

We establish that entropy production, which is crucial to the characterization of thermodynamic irreversibility, is obtained through a variational principle involving the Kulback-Leibler divergence. A simple application of this…

Statistical Mechanics · Physics 2021-03-11 Naoto Shiraishi , Keiji Saito

The Kullback-Leibler divergence or relative entropy is an information-theoretic measure between statistical models that play an important role in measuring a distance between random variables. In the study of complex systems, random fields…

Information Theory · Computer Science 2022-03-25 Alexandre L. M. Levada

This study introduces the Kerimov-Alekberli model, a novel information-geometric framework that redefines AI safety by formally linking non-equilibrium thermodynamics to stochastic control for the ethical alignment of autonomous systems. By…

Artificial Intelligence · Computer Science 2026-05-06 Hikmat Karimov , Rahid Zahid Alekberli

Fluctuation-dissipation relations elucidate the response of near-equilibrium systems to environmental changes, with recent advances extending response theory to non-equilibrium steady states. However, a general response theory for systems…

Statistical Mechanics · Physics 2026-05-06 Jiming Zheng , Zhiyue Lu

We discuss the recently proposed description of Kuramoto model in terms of hyperbolic space and relate it to the information geometry. In particular the dynamical equation in Kuramoto all-to-all model is identified with the gradient flow of…

Statistical Mechanics · Physics 2023-05-03 Artem Alexandrov , Alexander Gorsky

We propose a variational framework for nonequilibrium thermodynamics built around the effective number of accessible state, a multiplicative count that ranges from for a uniform distribution to one under complete localization, and whose…

Statistical Mechanics · Physics 2025-09-12 Mesfin Taye

The Tsallis entropy and Fisher information entropy (matrix) are very important quantities expressing information measures in nonextensive systems. Stationary and dynamical properties of the information entropies have been investigated in…

Statistical Mechanics · Physics 2009-11-13 Hideo Hasegawa

In this chapter we shall discuss the recent progresses of information theoretic tools in the context of free and confined harmonic oscillator. Confined quantum systems have provided appreciable interest in areas of physics, chemistry,…

Quantum Physics · Physics 2021-05-06 Neetik Mukherjee , Amlan K. Roy

We apply the method of shortcuts to adiabaticity to nonequilibrium systems. For unitary dynamics, the system Hamiltonian is separated into two parts. One of them defines the adiabatic states for the state to follow and the nonadiabatic…

Statistical Mechanics · Physics 2017-11-27 Kazutaka Takahashi

We prove that two well-known measures of information are interrelated in interesting and useful ways when applied to nonequilibrium circumstances. A nontrivial form of the lower bound for the Fisher information measure is derived in…

Statistical Mechanics · Physics 2012-04-06 Takuya Yamano

Fisher information is a lower bound on the uncertainty in the statistical estimation of classical and quantum mechanical parameters. While some deterministic dynamical systems are not subject to random fluctuations, they do still have a…

Classical Physics · Physics 2023-10-06 Mohamed Sahbani , Swetamber Das , Jason R. Green
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