As known, a method to introduce non-conventional statistics may be realized by modifying the number of possible combinations to put particles in a collection of single-particle states. In thispaper, we assume that the weight factor of the possible configurations of a system of interacting particles can be obtained by generalizing opportunely the combinatorics, according to a certain analyticalfunction f{p}(n) of the actual number of particles present in every energy level. Following this approach, the configurational Boltzmann entropy is revisited in a very general manner starting from acontinuous deformation of the multinomial coefficients depending on a set of deformation parameters {p}. It is shown that, when f{p}(n) is related to the solutions of a simple linear difference-differentialequation, the emerging entropy is a scaled version, in the occupational number representation, of the entropy of degree (k, r) known, in the framework of the information theory, as Sharma-Taneja-Mittalentropic form.

Boltzmann Configurational Entropy Revisited in the Framework of Generalized Statistical Mechanics

Antonio Maria Scarfone
2022

Abstract

As known, a method to introduce non-conventional statistics may be realized by modifying the number of possible combinations to put particles in a collection of single-particle states. In thispaper, we assume that the weight factor of the possible configurations of a system of interacting particles can be obtained by generalizing opportunely the combinatorics, according to a certain analyticalfunction f{p}(n) of the actual number of particles present in every energy level. Following this approach, the configurational Boltzmann entropy is revisited in a very general manner starting from acontinuous deformation of the multinomial coefficients depending on a set of deformation parameters {p}. It is shown that, when f{p}(n) is related to the solutions of a simple linear difference-differentialequation, the emerging entropy is a scaled version, in the occupational number representation, of the entropy of degree (k, r) known, in the framework of the information theory, as Sharma-Taneja-Mittalentropic form.
2022
Istituto dei Sistemi Complessi - ISC
configurational entropy
(k-r)-entropy
(k-r)-multinomial expansion
Sharma-Taneja- Mittal entropy
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/448323
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