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Recent theoretical and experimental studies have shown significance of quantum information scrambling (i.e. a spread of quantum information over a system degrees of freedom) for problems encountered in high-energy physics, quantum…

Quantum Physics · Physics 2019-12-11 Jan Tuziemski

We consider a basic model of a dynamical distribution network, modeled as a directed graph with storage variables corresponding to every vertex and flow inputs corresponding to every edge, subject to unknown but constant inflows and…

Optimization and Control · Mathematics 2013-03-20 J. Wei , A. J. van der Schaft

Operator growth, or operator spreading, describes the process where a "simple" operator acquires increasing complexity under the Heisenberg time evolution of a chaotic dynamics, therefore has been a key concept in the study of quantum chaos…

Statistical Mechanics · Physics 2021-11-18 Laimei Nie

Fermionic (atomic nuclei) and bosonic (correlated atoms in a trap) systems are studied from an information-theoretic point of view. Shannon and Onicescu information measures are calculated for the above systems comparing correlated and…

Quantum Physics · Physics 2016-09-08 Ch. C. Moustakidis , K. Ch. Chatzisavvas , C. P. Panos

A first principles analysis of an open system thermodynamical Carnot cycle is provided, and the results are compared to those proposed by Gibbs for open systems. The Kelvin-Clausius statement concerning heat transfer for reversible cycles…

General Mathematics · Mathematics 2007-05-23 Christopher G. Jesudason

The total entropy production generated by the dynamics of an externally driven systems exchanging energy and matter with multiple reservoirs and described by a master equation is expressed as the sum of three contributions, each…

Statistical Mechanics · Physics 2010-03-01 Massimiliano Esposito , Upendra Harbola , Shaul Mukamel

Predicting the behavior of AI-driven agents is particularly challenging without a preexisting model. In our paper, we address this by treating AI agents as nonlinear dynamical systems and adopting a probabilistic perspective to predict…

Artificial Intelligence · Computer Science 2024-06-06 Shiqi Zhang , Darshan Gadginmath , Fabio Pasqualetti

We prove a random Ruelle--Perron--Frobenius theorem and the existence of relative equilibrium states for a class of random open and closed interval maps, without imposing transitivity requirements, such as mixing and covering conditions,…

Dynamical Systems · Mathematics 2023-08-23 Jason Atnip , Gary Froyland , Cecilia González-Tokman , Sandro Vaienti

We report an approach to quantum open system dynamics that leads to novel nonlinear constant relations governing information flow among the participants. Our treatment is for mixed state systems entangled in a pure state fashion with an…

Quantum Physics · Physics 2010-09-29 Xiao-Feng Qian , J. H. Eberly

We introduce the concept of a "classical observable" as an operator with vanishingly small quantum fluctuations on a set of density matrices. It is shown how to construct them for a time evolved pure state. The study of classical…

Quantum Physics · Physics 2014-04-29 Michiel Wouters

We propose a novel tensor-based formalism for inferring causal structures from time series. An information theoretical analysis of transfer entropy, shows that transfer entropy results from transmission of information over a set of…

Information Theory · Computer Science 2020-04-22 David Sigtermans

Here, we investigate the uncertainty of dynamical observables in classical systems manipulated by repeated measurements and feedback control; the precision should be enhanced in the presence of an external controller but limited by the…

Statistical Mechanics · Physics 2020-01-23 Tan Van Vu , Yoshihiko Hasegawa

Symmetry is a powerful concept in physics, and its recent application to understand nonequilibrium behavior is providing deep insights and groundbreaking exact results. Here we show how to harness symmetry to control transport and…

Statistical Mechanics · Physics 2014-09-26 Daniel Manzano , Pablo I. Hurtado

Proportional fairness is a popular service allocation mechanism to describe and analyze the performance of data networks at flow level. Recently, several authors have shown that the invariant distribution of such networks admits a product…

Probability · Mathematics 2015-06-18 Maria Vlasiou , Jiheng Zhang , Bert Zwart

A general information transmission model, under independent and identically distributed Gaussian codebook and nearest neighbor decoding rule with processed channel output, is investigated using the performance metric of generalized mutual…

Information Theory · Computer Science 2019-08-23 Wenyi Zhang , Yizhu Wang , Cong Shen , Ning Liang

In this paper, for linear time-invariant plants, where a collection of possible inputs and outputs are known a priori, we address the problem of determining the communication between outputs and inputs, i.e., information patterns, such that…

Optimization and Control · Mathematics 2015-09-09 J. Frederico Carvalho , Sergio Pequito , A. Pedro Aguiar , Soummya Kar , George J. Pappas

I introduce an algorithm to detect one-way quantum information between two interacting quantum systems, i.e. the direction and orientation of the information transfer in arbitrary quantum dynamics. I then build an information-theoretic…

Quantum Physics · Physics 2020-08-26 Davide Girolami

Entanglement fidelity quantifies how well a quantum channel preserves the correlations between a transmitted system and an inaccessible reference system. We derive closed-form expressions for the entanglement fidelity associated with…

Quantum Physics · Physics 2026-03-10 Niccolò Zanieri , Marios Kountouris

The proliferation of networked devices, systems, and applications that we depend on every day makes managing networks more important than ever. The increasing security, availability, and performance demands of these applications suggest…

Networking and Internet Architecture · Computer Science 2017-11-01 Nick Feamster , Jennifer Rexford

We propose the concept of open network as an arbitrary selection of nodes of a large unknown network. Using the hypothesis that information of the whole network structure can be extrapolated from an arbitrary set of its nodes, we use Renyi…

Disordered Systems and Neural Networks · Physics 2009-11-13 V. Gudkov , V. Montealegre
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