2016
DOI: 10.1103/physreve.94.062113
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Ensemble-free configurational temperature for spin systems

Abstract: An estimator for the dynamical temperature in an arbitrary ensemble is derived in the framework of Bayesian statistical mechanics and the maximum entropy principle. We test this estimator numerically by a simulation of the two-dimensional XY-model in the canonical ensemble. As this model is critical in the whole region of temperatures below the Berezinski-Kosterlitz-Thouless critical temperature TBKT , we use a generalization of Wolff's uni-cluster algorithm. The numerical results allow us to confirm the robus… Show more

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Cited by 11 publications
(8 citation statements)
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“…On the other hand, applying the conjugate variables theorem [16] to the distribution P (Γ|S) = p(H(Γ)) and using the chain rule for the gradient of ln P (Γ|S), we see that [17] ∇…”
Section: The Fundamental Temperaturementioning
confidence: 99%
“…On the other hand, applying the conjugate variables theorem [16] to the distribution P (Γ|S) = p(H(Γ)) and using the chain rule for the gradient of ln P (Γ|S), we see that [17] ∇…”
Section: The Fundamental Temperaturementioning
confidence: 99%
“…1. Now the generalized Boltzmann factor ρ(E) is (12) and the fundamental inverse temperature is given by [16]…”
Section: The Generalized Boltzmann Factor and The Fundamental Temmentioning
confidence: 99%
“…A model with fundamental inverse temperature β F has a generalized equipartition theorem given by [12]…”
Section: Proof Of the Uniqueness Of The Q-canonical Formmentioning
confidence: 99%
See 1 more Smart Citation
“…We will illustrate our method by simulating the well-known XY-model defined on a square lattice of lattice size L (see ref. [15] for an accurate analysis of the configurational temperature for this model). The Hamiltonian for this model is: H = −JS 2 ∑ <i, j> cos (θ i − θ j ), being J > 0 the ferromagnetic coupling constant, θ i is the angle of the spin magnetic moment of magnitude S relative to some direction at the i-th lattice site.…”
mentioning
confidence: 99%