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arxiv: 1310.7071 · v2 · pith:5CY3LAUPnew · submitted 2013-10-26 · ❄️ cond-mat.stat-mech

Application of optimization method to the x⁴ model in the Tsallis nonextensive statistics

classification ❄️ cond-mat.stat-mech
keywords betaomegastatisticsexpectationfrequencymethodnonextensiveoptimization
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We study the effects of the environment described by the Tsallis nonextensive statistics on physical quantities using an optimization method in the case of small deviation from the Boltzmann-Gibbs statistics. The $x^4$ model is used and the density operator is restricted to be a gaussian form. The variational parameter is the frequency $\Omega$ of a particle in the optimization method. We obtain an approximate expression of free energy and of the expectation value of $\beta m \Omega^2 x^2 /2$, where $\beta$ is the inverse of the temperature and $m$ is the mass of a particle. Numerically, the optimized frequency is estimated and the expectation value of $\beta m \Omega^2 x^2 /2$ is calculated. The effects of the Tsallis nonextensive statistic for small deviation from the Boltzmann-Gibbs statistics are found: 1) the frequency modulation of a particle and 2) the variation of the expectation value of $\beta m \Omega^2 x^2 /2$ at high temperature.

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