2005
DOI: 10.1103/physreve.72.036108
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Statistical mechanics in the context of special relativity. II.

Abstract: The special relativity laws emerge as one-parameter (light speed) generalizations of the corresponding laws of classical physics. These generalizations, imposed by the Lorentz transformations, affect both the definition of the various physical observables (e.g., momentum, energy, etc.), as well as the mathematical apparatus of the theory. Here, following the general lines of [Phys. Rev. E 66, 056125 (2002)], we show that the Lorentz transformations impose also a proper one-parameter generalization of the class… Show more

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Cited by 300 publications
(223 citation statements)
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“…For the above relativistic gas in the presence of an external electromagnetic field, it can be written [26,27] as…”
Section: The Physical Interpretation For Q-parametermentioning
confidence: 99%
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“…For the above relativistic gas in the presence of an external electromagnetic field, it can be written [26,27] as…”
Section: The Physical Interpretation For Q-parametermentioning
confidence: 99%
“…The states of this gas can be characterized by a Lorentz invariant one-particle distribution function, f q (x, p). Thus at each time t, f q (x, p)d 3 xd 3 p gives the number of particles in the volume element d 3 xd 3 p around the space position x and momentum p. The evolution equation of the relativistic distribution function is assumed to be the relativistic generalized Boltzmann equation in the qkinetic theory [26]: …”
Section: The Physical Interpretation For Q-parametermentioning
confidence: 99%
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“…Kaniadakis (2002Kaniadakis ( , 2005, based on the same concept of maximum entropy, developed a power-law statistics, where the distribution function is given by:…”
Section: Appendix A: Distribution Of Projected Anglesmentioning
confidence: 99%
“…They obtained a much better fit when the assumption of Gibbs entropy in standard statistical mechanics is released and distribution functions from nonextensive statistical mechanics are applied to the sample. Specifically, they used the Tsallis distribution (Tsallis 1998) and the Kaniadakis power-law distribution (Kaniadakis 2002(Kaniadakis , 2005, both based on the concept of maximum entropy (Gell-Mann & Tsallis 2004). These distributions are also plotted in Fig.…”
Section: Application To Main-sequence Field Starsmentioning
confidence: 99%