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Currently, 'time' does not play any essential role in quantum information theory. In this sense, quantum information theory is underdeveloped similarly to how quantum physics was underdeveloped before Erwin Schrodinger introduced his famous…

Mesoscale and Nanoscale Physics · Physics 2019-09-04 Mohammad H. Ansari , Alwin van Steensel , Yuli V. Nazarov

Inferring models, predicting the future, and estimating the entropy rate of discrete-time, discrete-event processes is well-worn ground. However, a much broader class of discrete-event processes operates in continuous-time. Here, we provide…

Statistical Mechanics · Physics 2020-05-11 S. E. Marzen , J. P. Crutchfield

In the 21st century, many of the crucial scientific and technical issues facing humanity can be understood as problems associated with understanding, modelling, and ultimately controlling complex systems: systems comprised of a large number…

Information Theory · Computer Science 2025-01-20 Thomas F. Varley

Recent research has explored the increasingly important role of social media by examining the dynamics of individual and group behavior, characterizing patterns of information diffusion, and identifying influential individuals. In this…

Social and Information Networks · Computer Science 2011-10-13 Greg Ver Steeg , Aram Galstyan

Entropy estimation is of practical importance in information theory and statistical science. Many existing entropy estimators suffer from fast growing estimation bias with respect to dimensionality, rendering them unsuitable for…

Information Theory · Computer Science 2023-08-22 Ziqiao Ao , Jinglai Li

A unified view on macroscopic thermodynamics and quantum transport is presented. Thermodynamic processes with an exchange of energy between two systems necessarily involve the flow of other balanceable quantities. These flows are first…

Mesoscale and Nanoscale Physics · Physics 2012-10-02 C. Strunk

The application of information theory approach (both in its extensive and nonextensive versions) to high energy multiparticle processes is discussed and confronted with experimental data on e+e- annihilation processes, pp and \bar{p}p…

High Energy Physics - Phenomenology · Physics 2014-11-17 F. S. Navarra , O. V. Utyuzh , G. Wilk , Z. Wlodarczyk

We show how active transport of ions can be interpreted as an entropy facilitated process. In this interpretation, the pore geometry through which substrates are transported can give rise to a driving force. This gives a direct link between…

Biomolecules · Quantitative Biology 2017-05-24 J. M. Rubi , A. Lervik , D. Bedeaux , S. Kjelstrup

Quantum mechanics, information theory, and relativity theory are the basic foundations of theoretical physics. The acquisition of information from a quantum system is the interface of classical and quantum physics. Essential tools for its…

Quantum Physics · Physics 2011-04-29 Asher Peres , Daniel R. Terno

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

Prompted by the realisation that the statistical entropy of an ideal gas in the micro-canonical ensemble should not fluctuate or change over time, the meaning of the H-theorem is re-interpreted from the perspective of information theory in…

General Physics · Physics 2013-01-09 David Sands , Jeremy Dunning-Davies

Fluctuation theorems impose fundamental bounds in the statistics of the entropy production, with the second law of thermodynamics being the most famous. Using information theory, we quantify the information of entropy production and find an…

Quantum Physics · Physics 2021-02-17 Domingos S. P. Salazar

We propose to examine the predictability and the complexity characteristics of the Standard&Poor500 dynamics behaviors in a coarse-grained way using the symbolic dynamics method and under the prism of the Information theory through the…

Statistical Finance · Quantitative Finance 2021-05-11 Geoffrey Ducournau

The content of phase information of an arbitrary phase--sensitive measurement is evaluated using the maximum likelihood estimation. The phase distribution is characterized by the relative entropy--a nonlinear functional of input quantum…

Quantum Physics · Physics 2016-08-15 Zdeněk Hradil , Robert Myška , Tomáš Opatrný , Jiří Bajer

Entropy is a quantity for counting physical degrees of freedom in a system. At a finite temperature, one can use thermal entropy to study thermodynamical properties. At zero temperature, entanglement entropy is expected to provide a…

High Energy Physics - Theory · Physics 2018-10-29 Chen-Te Ma

This paper represents an extended version of an earlier note [10]. The concept of weighted entropy takes into account values of different outcomes, i.e., makes entropy context-dependent, through the weight function. We analyse analogs of…

Probability · Mathematics 2017-10-31 Mark Kelbert , Izabella Stuhl , Yuri Suhov

We analyze the effect of varying system conditions on the single-particle entanglement entropy for an arbitrary eigenstate of a complex system that can be described by a multiparametric Gaussian ensemble. Our theoretical analysis leads to…

Quantum Physics · Physics 2025-10-14 Devanshu Shekhar , Pragya Shukla

In the last decades, it has been understood that a wide variety of phenomena in quantum field theory (QFT) can be characterised using quantum information measures, such as the entanglement entropy of a state and the relative entropy between…

High Energy Physics - Theory · Physics 2017-02-27 David Blanco

We investigate quantum information processing and manipulations in disordered systems of ultracold atoms and trapped ions. First, we demonstrate generation of entanglement and local realization of quantum gates in a quantum spin glass…

We examine a class of deep learning models with a tractable method to compute information-theoretic quantities. Our contributions are three-fold: (i) We show how entropies and mutual informations can be derived from heuristic statistical…

Machine Learning · Computer Science 2020-01-22 Marylou Gabrié , Andre Manoel , Clément Luneau , Jean Barbier , Nicolas Macris , Florent Krzakala , Lenka Zdeborová