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Related papers: A Shannon-Tsallis transformation

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We show that the non-additivity relation of the Tsallis entropies in nonextensive statistical mechanics has a simple physical interpretation for systems with fluctuating temperature or fluctuating energy dissipation rate. We also show that…

Statistical Mechanics · Physics 2009-11-07 Christian Beck

Shannon entropy regularization is widely adopted in optimal control due to its ability to promote exploration and enhance robustness, e.g., maximum entropy reinforcement learning known as Soft Actor-Critic. In this paper, Tsallis entropy,…

Optimization and Control · Mathematics 2024-03-05 Yota Hashizume , Koshi Oishi , Kenji Kashima

The equilibrium distributions of probabilities providing maximality of Renyi and Tsallis entropies are rederived. New S-forms of them are found which are normalised with corresponding entropies in contrast to the usual Z-forms normalised…

Statistical Mechanics · Physics 2007-05-23 A. G. Bashkirov

We present the conclusive mathematical structure behind Tsallis statistics. We obtain mainly the following five theoretical results: (i) the one-to-one correspondence between the q-multinomial coefficient and Tsallis entropy, (ii) symmetry…

Statistical Mechanics · Physics 2007-05-23 Hiroki Suyari

Tsallis relative operator entropy is defined and then its properties are given. Shannon inequality and its reverse one in Hilbert space operators derived by T.Furuta \cite{Fu:par} are extended in terms of the parameter of the Tsallis…

Functional Analysis · Mathematics 2007-05-23 Kenjiro Yanagi , Ken Kuriyama , Shigeru Furuichi

The necessary conditions (NC) that reconcile canonical probability distributions obtained from the q-maximum entropy principle, subjected to both i) the additive duality of generalized statistics and ii) normal averages expectations with…

Statistical Mechanics · Physics 2013-03-21 R. C. Venkatesan , A. Plastino

In this work we firstly review some results in Classical Information Theory. Next, we try to generalize these results by using the Tsallis entropy. We present a preliminary result and discuss our aims in this field.

General Literature · Computer Science 2007-05-23 Gilson Antonio Giraldi

We formulate the flow of thick fluids as evolution variational and quasi-variational inequalities, with a variable threshold on the absolute value of the deformation rate tensor. In the variational case, we show the existence and uniqueness…

Analysis of PDEs · Mathematics 2026-01-22 Jos\é Francisco Rodrigues , Lisa Santos

Recent experiments have demonstrated that measurements of the entropy change associated with the addition of electrons to semiconductor- and graphene-based quantum dots accurately quantify the spin and orbital degeneracy of the states into…

The phenomenon of entropy concentration provides strong support for the maximum entropy method, MaxEnt, for inferring a probability vector from information in the form of constraints. Here we extend this phenomenon, in a discrete setting,…

Information Theory · Computer Science 2021-01-11 Kostas N. Oikonomou

It is known that many classical inequalities linked to convolutions can be obtained by looking at the monotonicity in time of convolutions of powers of solutions to the heat equation, provided that both the exponents and the coefficients of…

Mathematical Physics · Physics 2013-09-26 Giuseppe Toscani

We study the properties of Tsallis entropy and Shannon entropy from the point of view of algorithmic randomness. In algorithmic information theory, there are two equivalent ways to define the program-size complexity K(s) of a given finite…

Information Theory · Computer Science 2019-09-04 Kohtaro Tadaki

The inverse problem of the calculus of variations asks whether a given system of partial differential equations (PDEs) admits a variational formulation. We show that the existence of a presymplectic form in the variational bicomplex, when…

Mathematical Physics · Physics 2013-11-12 Igor Khavkine

We investigate the necessary conditions for the two spacetimes, which are solutions to the Einstein field equations with an anisotropic matter source, to be related to each other by means of a conformal transformation. As a result, we…

General Relativity and Quantum Cosmology · Physics 2021-06-18 Jarosław Kopiński

Although compartmental dynamical systems are used in many different areas of science, model selection based on the maximum entropy principle (MaxEnt) is challenging because of the lack of methods for quantifying the entropy for this type of…

Information Theory · Computer Science 2023-08-23 Holger Metzler , Carlos A. Sierra

Upper and lower bounds are obtained for the joint entropy of a collection of random variables in terms of an arbitrary collection of subset joint entropies. These inequalities generalize Shannon's chain rule for entropy as well as…

Information Theory · Computer Science 2024-05-07 Mokshay Madiman , Prasad Tetali

We extend the Hanel and Thurner asymptotic analysis to both extensive and non-extensive entropies on the basis of a wide class of entropic forms. The procedure is known to be capable to classify multiple entropy measures in terms of their…

Statistical Mechanics · Physics 2020-02-21 Nana Cabo Bizet , Jesus Fuentes , Octavio Obregon

Understanding cause-effect relationships is a crucial part of the scientific process. As Bell's theorem shows, within a given causal structure, classical and quantum physics impose different constraints on the correlations that are…

Quantum Physics · Physics 2021-02-09 V. Vilasini , Roger Colbeck

In ordinary statistical mechanics the Boltzmann-Shannon entropy is related to the Maxwell-Bolzmann distribution $p_i$ by means of a twofold link. The first link is differential and is offered by the Jaynes Maximum Entropy Principle. The…

Statistical Mechanics · Physics 2009-10-02 G. Kaniadakis

This work develops problem statements related to encoders and autoencoders with the goal of elucidating variational formulations and establishing clear connections to information-theoretic concepts. Specifically, four problems with varying…

Information Theory · Computer Science 2021-07-15 Karthik Duraisamy
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