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We introduce new machine-learning techniques for analyzing chaotic dynamical systems. The primary objectives of the study include the development of a new and simple method for calculating the Lyapunov exponent using only two trajectory…

Chaotic Dynamics · Physics 2024-08-06 Lazare Osmanov

Two familiar notions of correlation are rediscovered as the extreme operating points for distributed synthesis of a discrete memoryless channel, in which a stochastic channel output is generated based on a compressed description of the…

Information Theory · Computer Science 2016-11-18 Paul Cuff

We study the concentration phenomenon for discrete-time random dynamical systems with an unbounded state space. We develop a heuristic approach towards obtaining exponential concentration inequalities for dynamical systems using an entirely…

Machine Learning · Statistics 2022-12-08 Muhammad Abdullah Naeem , Miroslav Pajic

We analyze the top Lyapunov exponent of the product of sequences of two by two matrices that appears in the analysis of several statistical mechanics models with disorder: for example these matrices are the transfer matrices for the nearest…

Probability · Mathematics 2022-09-01 Giambattista Giacomin , Rafael L. Greenblatt

We show that it is possible to associate univocally with each given solution of the time-dependent Schroedinger equation a particular phase flow ("quantum flow") of a non-autonomous dynamical system. This fact allows us to introduce a…

Quantum Physics · Physics 2007-05-23 P. Falsaperla , G. Fonte , G. Salesi

Shannon information entropy is a natural measure of probability (de)localization and thus (un)predictability in various procedures of data analysis for model systems. We pay particular attention to links between the Shannon entropy and the…

Statistical Mechanics · Physics 2007-05-23 Piotr Garbaczewski

We train an artificial neural network which distinguishes chaotic and regular dynamics of the two-dimensional Chirikov standard map. We use finite length trajectories and compare the performance with traditional numerical methods which need…

Machine Learning · Computer Science 2020-04-24 Woo Seok Lee , Sergej Flach

In this paper, we propose a dynamical systems perspective of the Expectation-Maximization (EM) algorithm. More precisely, we can analyze the EM algorithm as a nonlinear state-space dynamical system. The EM algorithm is widely adopted for…

Optimization and Control · Mathematics 2018-10-05 Orlando Romero , Sarthak Chatterjee , Sérgio Pequito

The presence of symmetries imposes a stringent set of constraints on a system. This constrained structure allows intelligent agents interacting with such a system to drastically improve the efficiency of learning and generalization, through…

Information Theory · Computer Science 2024-10-03 Hippolyte Charvin , Nicola Catenacci Volpi , Daniel Polani

This paper is concerned with relationships of Lyapunov exponents with sensitivity and stability for non-autonomous discrete systems. Some new concepts are introduced for non-autonomous discrete systems, including Lyapunov exponents, strong…

Dynamical Systems · Mathematics 2016-03-18 Hua Shao , Yuming Shi , Hao Zhu

An analytical expression for the maximal Lyapunov exponent $\lambda_1$ in generalized Fermi-Pasta-Ulam oscillator chains is obtained. The derivation is based on the calculation of modulational instability growth rates for some unstable…

Statistical Mechanics · Physics 2016-08-31 Thierry Dauxois , Stefano Ruffo , Alessandro Torcini

Positive Lyapunov exponents measure the asymptotic exponential divergence of nearby trajectories of a dynamical system. Not only they quantify how chaotic a dynamical system is, but since their sum is an upper bound for the entropy by the…

Chaotic Dynamics · Physics 2009-08-24 M. S. Baptista , F. Moukam Kakmeni , Gianluigi Del Magno , M. S. Hussein

Different aspects of the predictability problem in dynamical systems are reviewed. The deep relation among Lyapunov exponents, Kolmogorov-Sinai entropy, Shannon entropy and algorithmic complexity is discussed. In particular, we emphasize…

Chaotic Dynamics · Physics 2009-11-07 G. Boffetta , M. Cencini , M. Falcioni , A. Vulpiani

Dual to the usual noisy channel coding problem, where a noisy (classical or quantum) channel is used to simulate a noiseless one, reverse Shannon theorems concern the use of noiseless channels to simulate noisy ones, and more generally the…

Quantum Physics · Physics 2014-07-22 Charles H. Bennett , Igor Devetak , Aram W. Harrow , Peter W. Shor , Andreas Winter

Biological systems transduce signals from their surroundings through a myriad of pathways. In this paper, we describe signal transduction as a communication system: the signal transduction receptor acts as the receiver in this system, and…

Information Theory · Computer Science 2019-01-25 Andrew W. Eckford , Peter J. Thomas

Information theory has provided foundations for the theories of several application areas critical for modern society, including communications, computer storage, and AI. A key aspect of Shannon's 1948 theory is a sharp lower bound on the…

The necessary and sufficient conditions of optimality of the decoding of quantum signals minimizing the Bayesian risk are generalized for the Shannon mutual information criteria. It is shown that for a linear channel with Gaussian boson…

Quantum Physics · Physics 2007-05-23 V. P. Belavkin , A. G. Vantsyan

A new method based on the phenomenon of synchronization and the properties of chaos is proposed to reduce interference in the transferred chaotic signals of synchronized systems. In this paper, the interference is considered as a series of…

Mathematical Physics · Physics 2011-09-27 Yang Nan , Long Zhang-Cai , Zhao Xiang-Hui

In this work we present a theoretical and numerical study of the behaviour of the maximum Lyapunov exponent for a generic coupled-map-lattice in the weak-coupling regime. We explain the observed results by introducing a suitable…

chao-dyn · Physics 2007-05-23 F. Cecconi , A. Politi

We study the chaoticity and the predictability of a turbulent flow on the basis of high-resolution direct numerical simulations at different Reynolds numbers. We find that the Lyapunov exponent of turbulence, which measures the exponential…

Fluid Dynamics · Physics 2017-08-09 G. Boffetta , S. Musacchio
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