The sensitivity of the population of states to the value of $q$ and the legitimate range of $q$ in Tsallis statistics
Ali M. Nassimi, Gholamabbas Parsafar

TL;DR
This paper investigates how the population of states in Tsallis statistical mechanics varies with the parameter q for simple systems, revealing that differences from Boltzmann-Gibbs predictions are often experimentally indistinguishable and exploring the complex relation between rare events and q.
Contribution
It provides a detailed analysis of state populations in Tsallis statistics, examines the q-dependence of rare and frequent events, and proposes a conjecture on the convergence of the partition function in the thermodynamic limit.
Findings
Differences between Tsallis and Boltzmann-Gibbs predictions are often below experimental detection.
The relation between event rarity and q is more complex than previously thought.
Conjecture that q ≤ 1 for the convergence of the partition function in large systems.
Abstract
In the framework of the Tsallis statistical mechanics, for the spin-1/2 and the harmonic oscillator, we study the change of the population of states when the parameter is varied; the results show that the difference between predictions of the Boltzmann--Gibbs and Tsallis Statistics can be much smaller than the precision of any existing experiment. Also, the relation between the privilege of rare/frequent event and the value of is restudied. This relation is shown to be more complicated than the common belief about it. Finally, the convergence criteria of the partition function of some simple model systems, in the framework of Tsallis Statistical Mechanics, is studied; based on this study, we conjecture that , in the thermodynamic limit.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsStatistical Mechanics and Entropy · Complex Systems and Time Series Analysis · Fractional Differential Equations Solutions
