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We first observe that the (co)domains of the q-deformed functions are some subsets of the (co)domains of their ordinary counterparts, thereby deeming the deformed functions to be incomplete. In order to obtain a complete definition of…

Statistical Mechanics · Physics 2015-05-13 Thomas Oikonomou , G. Baris Bagci

It is currently a widely used practice to write the constraints in terms of escort averages when the generalized entropies are employed in the maximization scheme. We show that the maximization of the nonadditive $q$-entropy with escort…

Statistical Mechanics · Physics 2019-04-02 Aruna Bidollina , Thomas Oikonomou , G. Baris Bagci

Within a framework of utmost generality, we show that the entropy maximization procedure with linear constraints uniquely leads to the Shannon-Boltzmann-Gibbs entropy. Therefore, the use of this procedure with linear constraints should not…

Statistical Mechanics · Physics 2018-05-01 Thomas Oikonomou , G. Baris Bagci

For statistical systems that violate one of the four Shannon-Khinchin axioms, entropy takes a more general form than the Boltzmann-Gibbs entropy. The framework of superstatistics allows one to formulate a maximum entropy principle with…

Classical Physics · Physics 2012-11-13 Rudolf Hanel , Stefan Thurner , Murray Gell-Mann

We discuss two families of two-parameter entropies and divergences, derived from the standard R\'enyi and Tsallis entropies and divergences. These divergences and entropies are found as divergences or entropies of escort distributions.…

Mathematical Physics · Physics 2011-09-16 J. -F. Bercher

It is well-known that the partition function can consistently be factorized from the canonical equilibrium distribution obtained through the maximization of the Shannon entropy. We show that such a normalized and factorized equilibrium…

Statistical Mechanics · Physics 2016-11-29 Thomas Oikonomou , G. Baris Bagci

The class of SPA entropies, which can be represented as an increasing continuous transformation of Shannon and R\'enyi entropies, have intensively been studied in previous decades. Although their mathematical structure has thoroughly been…

Mathematical Physics · Physics 2020-01-01 Velimir M. Ilic , Antonio Maria Scarfone , Tatsuaki Wada

We discuss the interest of escort distributions and R\'enyi entropy in the context of source coding. We first recall a source coding theorem by Campbell relating a generalized measure of length to the R\'enyi-Tsallis entropy. We show that…

Mathematical Physics · Physics 2011-09-16 J. -F. Bercher

Escort distributions have been shown to be very useful in a great variety of fields ranging from information theory, nonextensive statistical mechanics till coding theory, chaos and multifractals. In this work we give the notion and the…

Mathematical Physics · Physics 2018-12-26 D. Puertas-Centeno

We present a sampling-based trajectory optimization method derived from the maximum entropy formulation of Differential Dynamic Programming with Tsallis entropy. This method is a generalization of the legacy work with Shannon entropy, which…

Optimization and Control · Mathematics 2024-09-18 Yuichiro Aoyama , Evangelos A. Theodorou

In the world of generalized entropies---which, for example, play a role in physical systems with sub- and super-exponential phasespace growth per degree of freedom---there are two ways for implementing constraints in the maximum entropy…

Mathematical Physics · Physics 2019-02-20 Jan Korbel , Rudolf Hanel , Stefan Thurner

In this paper we remark that Shannon entropy can be expressed as a function of the self-information (i.e. the logarithm) and the inverse of the Lambert $W$ function. It means that we consider that Shannon entropy has the trace form: $-k…

Statistical Mechanics · Physics 2019-07-05 Laurent Truffet

Bento \textit{et al.} [Phys. Rev. E 91, 022105 (2015)] recently stated that the Tsallis entropy violates the third law of thermodynamics for $0 < q <1$ in the sub-additive regime. We first show that the division between the regimes $q < 1$…

Statistical Mechanics · Physics 2016-02-24 G. Baris Bagci , Thomas Oikonomou

We study expected utility maximization problem with constant relative risk aversion utility function in a complete market under the reinforcement learning framework. To induce exploration, we introduce the Tsallis entropy regularizer, which…

Machine Learning · Computer Science 2025-02-04 Chen Ziyi , Gu Jia-wen

By using the maximum entropy principle with Tsallis entropy we obtain a fragment size distribution function which undergoes a transition to scaling. This distribution function reduces to those obtained by other authors using Shannon…

Soft Condensed Matter · Physics 2015-06-24 Oscar Sotolongo-Costa , Arezky H. Rodriguez , G. J. Rodgers

We show that in the continuum limit, the average spectrum method (ASM) is equivalent to maximizing R\'enyi entropies of order $\eta$, of which Shannon entropy is the special case $\eta=1$. The order of R\'enyi entropy is determined by the…

Strongly Correlated Electrons · Physics 2023-07-24 Khaldoon Ghanem , Erik Koch

Entropies must correspond to mean values for them to be measurable. The Shannon entropy corresponds to the weighted arithmetic mean, whereas the Renyi entropy corresponds to the exponential mean. These means refer to code lengths, which are…

Statistical Mechanics · Physics 2011-10-25 B. H. Lavenda

We present an argument justifying the origin of the escort distributions used in calculations involving the Tsallis entropy. We rely on an induced hyperbolic Riemannian metric reflecting the generalized composition property of the Tsallis…

Statistical Mechanics · Physics 2012-06-25 Nikos Kalogeropoulos

In this article we provide initial findings regarding the problem of solving likelihood equations by means of a maximum entropy approach. Unlike standard procedures that require equating at zero the score function of the maximum-likelihood…

Computation · Statistics 2019-06-18 Antonio Calcagnì , Livio Finos , Gianmarco Altoè , Massimiliano Pastore

Algorithmic entropy and Shannon entropy are two conceptually different information measures, as the former is based on size of programs and the later in probability distributions. However, it is known that, for any recursive probability…

Information Theory · Computer Science 2010-06-03 Andreia Teixeira , Andre Souto , Armando Matos , Luis Antunes
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