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An information theoretic measure is derived that quantifies the statistical coherence between systems evolving in time. The standard time delayed mutual information fails to distinguish information that is actually exchanged from shared…

Chaotic Dynamics · Physics 2009-10-31 Thomas Schreiber

Many systems involve numerous interacting parts and the whole system can have properties that the individual parts do not. I take this novelty as the defining characteristic of an emergent property. Other characteristics associated with…

History and Philosophy of Physics · Physics 2025-11-05 Ross H. McKenzie

Sampling considerations limit the experimental conditions under which information theoretic analyses of neurophysiological data yield reliable results. We develop a procedure for computing the full temporal entropy and information of…

Biological Physics · Physics 2009-11-06 Simon R. Schultz , Stefano Panzeri

The principle of maximum entropy is a broadly applicable technique for computing a distribution with the least amount of information possible while constrained to match empirically estimated feature expectations. However, in many real-world…

Machine Learning · Computer Science 2022-08-16 Kenneth Bogert , Yikang Gui , Prashant Doshi

A possible solution of the information paradox can be sought in quantum information scrambling. In this paradigm, it is postulated that all information entering a black hole is rapidly and chaotically distributed across the event horizon…

Quantum Physics · Physics 2021-01-20 Akram Touil , Sebastian Deffner

In this paper, we analyze the relationship between entropy and information in the context of the mixing process of two identical ideal gases. We will argue that entropy has a special information-based feature that is enfolded in the…

Quantum Physics · Physics 2015-06-26 Afshin Shafiee , Majid Karimi

The information entropy is here investigated in the context of early and late cosmology under the hypothesis that distinct phases of universe evolution are entangled between them. The approach is based on the \emph{entangled state ansatz},…

General Relativity and Quantum Cosmology · Physics 2018-02-28 Salvatore Capozziello , Orlando Luongo

Data-based inference of directed interactions in complex dynamical systems is a problem common to many disciplines of science. In this work, we study networks of spatially separate dynamical entities, which could represent physical systems…

Statistical Mechanics · Physics 2024-03-15 Tim Hempel , Sarah A. M. Loos

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…

We investigate a stationary process's crypticity---a measure of the difference between its hidden state information and its observed information---using the causal states of computational mechanics. Here, we motivate crypticity and cryptic…

Data Analysis, Statistics and Probability · Physics 2015-05-30 John R. Mahoney , Christopher J. Ellison , Ryan G. James , James P. Crutchfield

A unifying theory is put forward that entropy is equal to action. The crowning derivation is based on information theoretic methods and uses our hypothesis that "particles move via the discrete Bernoulli Process." While this hypothesis…

General Physics · Physics 2022-09-13 John L. Haller

This Thesis explores how tools from Statistical Physics and Information Theory can help us describe and understand complex systems. In the first part, we study the interplay between internal interactions, environmental changes, and…

Statistical Mechanics · Physics 2023-03-01 Giorgio Nicoletti

Complex systems are found in most branches of science. It is still argued how to best quantify their complexity and to what end. One prominent measure of complexity (the statistical complexity) has an operational meaning in terms of the…

Data Analysis, Statistics and Probability · Physics 2011-10-24 Karoline Wiesner , Mile Gu , Elisabeth Rieper , Vlatko Vedral

In [Haruna, T. and Nakajima, K., 2011. Physica D 240, 1370-1377], the authors introduced the duality between values (words) and orderings (permutations) as a basis to discuss the relationship between information theoretic measures for…

Chaotic Dynamics · Physics 2015-06-04 Taichi Haruna , Kohei Nakajima

We perform entanglement of spin and motional degrees of freedom of a single, ground-state trapped ion through the application of a $16$ ps laser pulse. The duration of the interaction is significantly shorter than both the motional…

Quantum Physics · Physics 2024-02-23 Randall Putnam , Adam D. West , Wesley C. Campbell , Paul Hamilton

Information shared between parties quantifies their correlation. The encoding of correlations across space and time characterises the structure, history, and interactions of systems. One of the most fundamental properties that emerges from…

In this work, we study the information scrambling and the entanglement dynamics in the complex Brownian Sachdev-Ye-Kitaev (cBSYK) models, focusing on their dependence on the charge density $n$. We first derive the effective theory for…

Strongly Correlated Electrons · Physics 2023-05-15 Pengfei Zhang

The paper introduces the recent results related to an entropy functional on trajectories of a controlled diffusion process, and the information path functional (IPF), analyzing their connections to the Kolmogorov's entropy, complexity and…

Information Theory · Computer Science 2011-07-12 Vladimir S. Lerner

Maximum entropy principle (MEP) analysis with few non-zero effective interactions successfully characterizes the distribution of dynamical states of pulse-coupled networks in many experiments, e.g., in neuroscience. To better understand the…

Biological Physics · Physics 2019-01-17 Zhi-Qin John Xu , Douglas Zhou , David Cai

Interactions between pieces of information (entities) play a substantial role in the way an individual acts on them: adoption of a product, the spread of news, strategy choice, etc. However, the underlying interaction mechanisms are often…

Machine Learning · Computer Science 2022-02-02 Gaël Poux-Médard , Julien Velcin , Sabine Loudcher