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The problems of causality, modeling, and control for chaotic, high-dimensional dynamical systems are formulated in the language of information theory. The central quantity of interest is the Shannon entropy, which measures the amount of…

Dynamical Systems · Mathematics 2022-06-01 Adrián Lozano-Durán , Gonzalo Arranz

Neural activity fluctuates over a wide range of timescales within and across brain areas. Experimental observations suggest that diverse neural timescales reflect information in dynamic environments. However, how timescales are defined and…

Neurons and Cognition · Quantitative Biology 2026-01-21 Roxana Zeraati , Anna Levina , Jakob H. Macke , Richard Gao

Intrinsic transcriptional noise induced by operator fluctuations is investigated with a simple spin like stochastic model. The effects of transcriptional fluctuations in protein synthesis is probed by coupling transcription and translation…

Other Quantitative Biology · Quantitative Biology 2007-05-23 Guilherme da C. P. Innocentini , Jose E. M. Hornos

Living systems operate far from thermal equilibrium by converting the chemical potential of ATP into mechanical work to achieve growth, replication or locomotion. Given time series observations of intra-, inter- or multicellular processes,…

Biological Physics · Physics 2021-11-03 Dominic J. Skinner , Jörn Dunkel

Fluctuating-charge models are computationally efficient methods of treating polarization and charge-transfer phenomena in molecular mechanics and classical molecular dynamics simulations. They are also theoretically appealing as they are…

Chemical Physics · Physics 2010-04-02 Jiahao Chen

This work explores entropy analysis as a tool for probing information distribution within Transformer-based architectures. By quantifying token-level uncertainty and examining entropy patterns across different stages of processing, we aim…

Computation and Language · Computer Science 2025-07-31 Amedeo Buonanno , Alessandro Rivetti , Francesco A. N. Palmieri , Giovanni Di Gennaro , Gianmarco Romano

We consider discrete stochastic processes, modeled by classical master equations, on networks. The temporal growth of the lack of information about the system is captured by its non-equilibrium entropy, defined via the transition…

Statistical Mechanics · Physics 2017-04-26 Oliver Muelken , Sarah Heinzelmann , Maxim Dolgushev

The ability to distinguish between correlation and causation of variables in molecular systems remains an interesting and open area of investigation. In this work, we probe causality in a molecular system using two independent computational…

Chemical Physics · Physics 2025-02-27 Vittorio Del Tatto , Debarshi Banerjee , Ali Hassanali , Alessandro Laio

Phase transitions abound in nature and society, and, from species extinction to stock market collapse, their prediction is of widespread importance. In earlier work we showed that Global Transfer Entropy, a general measure of information…

Statistical Mechanics · Physics 2021-04-12 Joshua Brown , Terry Bossomaier , Lionel Barnett

Neuronal dynamics are fundamentally constrained by the underlying structural network architecture, yet much of the details of this synaptic connectivity are still unknown even in neuronal cultures in vitro. Here we extend a previous…

Neurons and Cognition · Quantitative Biology 2017-02-08 Javier G. Orlandi , Olav Stetter , Jordi Soriano , Theo Geisel , Demian Battaglia

Out-of-equilibrium systems continuously generate entropy, with its rate of production being a fingerprint of non-equilibrium conditions. In small-scale dissipative systems subject to thermal noise, fluctuations of entropy production are…

Statistical Mechanics · Physics 2023-01-19 Prajwal Padmanabha , Daniel Maria Busiello , Amos Maritan , Deepak Gupta

Sagawa and Ueda established a fluctuation theorem of information exchange by revealing the role of correlations in stochastic thermodynamics and unified the non-equilibrium thermodynamics of measurement and feedback control [T. Sagawa and…

Statistical Mechanics · Physics 2019-03-26 Lee Jinwoo

A model for autonomous feedback control of particle transport through a large number of channels is introduced. Interactions among the particles can lead to a strong suppression of fluctuations in the particle number statistics. Within a…

Statistical Mechanics · Physics 2016-02-25 Tobias Brandes

We address microscopic, agent based, and macroscopic, stochastic, modeling of the financial markets combining it with the exogenous noise. The interplay between the endogenous dynamics of agents and the exogenous noise is the primary…

Statistical Finance · Quantitative Finance 2016-11-22 Vygintas Gontis

Information theory is a practical and theoretical framework developed for the study of communication over noisy channels. Its probabilistic basis and capacity to relate statistical structure to function make it ideally suited for studying…

Neurons and Cognition · Quantitative Biology 2015-01-09 Robin A. A. Ince , Simon R. Schultz , Stefano Panzeri

Making decisions freely presupposes that there is some indeterminacy in the environment and in the decision making engine. The former is reflected on the behavioral changes due to communicating: few changes indicate rigid environments;…

Artificial Intelligence · Computer Science 2020-09-23 Luis A. Pineda

The interaction between boundary layer turbulence and a porous layer is the cornerstone to the interface engineering. In this study, the spatial resolved transfer entropy is used to assess the asymmetry of the causal interaction next to a…

Fluid Dynamics · Physics 2023-12-04 Xu Chu , Wenkang Wang , Bernhard Weigand

Understanding noisy information engines is a fundamental problem of non-equilibrium physics, particularly in biomolecular systems agitated by thermal and active fluctuations in the cell. By the generalized second law of thermodynamics, the…

Statistical Mechanics · Physics 2020-09-01 Govind Paneru , Sandipan Dutta , Takahiro Sagawa , Tsvi Tlusty , Hyuk Kyu Pak

Data from social media are providing unprecedented opportunities to investigate the processes that rule the dynamics of collective social phenomena. Here, we consider an information theoretical approach to define and measure the temporal…

Energy efficiency is a big concern in industrial sectors. Finding the root cause of anomaly state of energy efficiency can help to improve energy efficiency of industrial systems and therefore save energy cost. In this research, we propose…

Machine Learning · Computer Science 2024-01-12 Jian Ma