Generalized Boltzmann factors and the maximum entropy principle: Entropies for complex systems
Rudolf Hanel and
Stefan Thurner
Physica A: Statistical Mechanics and its Applications, 2007, vol. 380, issue C, 109-114
Abstract:
We generalize the usual exponential Boltzmann factor to any reasonable and potentially observable distribution function, B(E). By defining generalized logarithms Λ as inverses of these distribution functions, we are led to a generalization of the classical Boltzmann–Gibbs entropy (SBG=-∫dεω(ε)B(ε)lnB(ε)) to the expression S≡-∫dεω(ε)∫0B(ε)dxΛ(x), which contains the classical entropy as a special case. We show that this is the unique modification of entropy which is compatible with the maximum entropy principle for arbitrary, non-exponential distribution functions. We demonstrate that this entropy has two important features: first, it describes the correct thermodynamic relations of the system, and second, the observed distributions are straightforward solutions to the Jaynes maximum entropy principle with the ordinary (not escort!) constraints. Tsallis entropy is recovered as a further special case.
Date: 2007
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437107002233
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:380:y:2007:i:c:p:109-114
DOI: 10.1016/j.physa.2007.02.070
Access Statistics for this article
Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis
More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().