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A unified presentation of the perturbation and variational methods for the generalized statistical mechanics based on Tsallis entropy is given here. In the case of the variational method, the Bogoliubov inequality is generalized in a very…

Statistical Mechanics · Physics 2009-10-31 E. K. Lenzi , L. C. Malacarne , R. S. Mendes

A principled framework to generalize variational perturbation approximations (VPA's) formulated within the ambit of the nonadditive statistics of Tsallis statistics, is introduced. This is accomplished by operating on the terms constituting…

Statistical Mechanics · Physics 2015-05-14 R. C. Venkatesan , A. Plastino

Variational inference has become one of the most widely used methods in latent variable modeling. In its basic form, variational inference employs a fully factorized variational distribution and minimizes its KL divergence to the posterior.…

Machine Learning · Statistics 2020-01-29 Robert Bamler , Cheng Zhang , Manfred Opper , Stephan Mandt

Tsallis entropy is a useful one-parameter generalization of the standard von Neumann entropy in information theory. We study the variance of Tsallis entropy of bipartite quantum systems in a random pure state. The main result is an exact…

Mathematical Physics · Physics 2022-02-16 Lu Wei

A variational method is discussed, extending the Gaussian effective potential to higher orders. The single variational parameter is replaced by trial unknown two-point functions, with infinite variational parameters to be optimized by the…

High Energy Physics - Phenomenology · Physics 2013-09-30 Fabio Siringo

We propose a variational perturbation method based on the observation that eigenvalues of each parity sector of both the anharmonic and double-well oscillators are approximately equi-distanced. The generalized deformed algebra satisfied by…

High Energy Physics - Theory · Physics 2008-11-26 Hyeong-Chan Kim , Jae Hyung Yee

A new variational perturbation theory is developed based on the $q-$deformed oscillator. It is shown that the new variational perturbation method provides 200 or 10 times better accuracy for the ground state energy of anharmonic oscillator…

High Energy Physics - Theory · Physics 2007-05-23 Hyeong-Chan Kim , Jae Hyung Yee , Sang Pyo Kim

We apply a recently proposed approximation method to the evaluation of non-Gaussian integral and anharmonic oscillator. The method makes use of the truncated perturbation series by recasting it via the modified Laplace integral…

Mathematical Physics · Physics 2009-10-30 Naoki Mizutani , Hirofumi Yamada

In a recent paper [Phys. Rev. Lett. \textbf{93}, 130401 (2004)], we proposed the idea of expanding the space of variations in variational calculations of the energy by considering the approximate wave function $\psi$ to be a functional of…

Chemical Physics · Physics 2009-11-11 Xiao-Yin Pan , Viraht Sahni , Lou Massa

Using an alternative notion of entropy introduced by Datta, the max-entropy, we present a new simplified framework to study the minimizers of the specific free energy for random fields which are weakly dependent in the sense of Lewis,…

Probability · Mathematics 2021-03-30 Piet Lammers , Martin Tassy

A generalized-statistics variational principle for source separation is formulated by recourse to Tsallis' entropy subjected to the additive duality and employing constraints described by normal averages. The variational principle is…

Statistical Mechanics · Physics 2011-03-01 R. C. Venkatesan , A. Plastino

In a recent letter (EPL, 104 (2013) 60003) we suggested a way to avoid divergences inherent to the formulation of nonextensive statistical mechanics. They can be eliminated via the use of a q-Laplace transformation, which was illustrated…

Statistical Mechanics · Physics 2015-11-18 A. Plastino , M. C. Rocca

We systematically investigate different versions of variational perturbation theory by forcing not only the first or second but also higher derivatives of the approximant with respect to the variational parameter to vanish. The choice of…

Condensed Matter · Physics 2016-11-23 Bodo Hamprecht , Axel Pelster

A variational method is studied based on the minimum of energy variance. The method is tested on exactly soluble problems in quantum mechanics, and is shown to be a useful tool whenever the properties of states are more relevant than the…

High Energy Physics - Phenomenology · Physics 2009-01-07 Luca Marotta , Fabio Siringo

A nonextensive thermostatic approach to chaotic dynamical systems is developed by expressing generalized Tsallis distribution as escort distribution. We explicitly show the thermodynamic limit and also derive the Legendre Transform…

Statistical Mechanics · Physics 2009-10-31 Ramandeep S. Johal , Renuka Rai

We introduce a variational algorithm based on Matrix Product States that is trained by minimizing a generalized free energy defined using Tsallis entropy instead of the standard Gibbs entropy. As a result, our model can generate the…

Statistical Mechanics · Physics 2024-09-16 Pablo Díez-Valle , Fernando Martínez-García , Juan José García-Ripoll , Diego Porras

We show that Tsallis ensemble of power-law distributions provides a mechanical model of nonextensive equilibrium thermodynamics for small interacting Hamiltonian systems, i.e., using Boltzmann's original nomenclature, we prove that it is an…

Statistical Mechanics · Physics 2007-05-23 M. Campisi , G. B. Bagci

Tsallis' non-extensive entropy is extended to incorporate the dependence on affinities between the microstates of a system. At the core of our construction of the extended entropy ($\mathcal{H}$) is the concept of the effective number of…

Quantitative Methods · Quantitative Biology 2022-02-08 Keisuke Okamura

We derive recursively the perturbation series for the ground-state energy of the D-dimensional anharmonic oscillator and resum it using variational perturbation theory (VPT). From the exponentially fast converging approximants, we extract…

Quantum Physics · Physics 2009-12-06 Sebastian F. Brandt , Axel Pelster

Variational methods are employed in situations where exact Bayesian inference becomes intractable due to the difficulty in performing certain integrals. Typically, variational methods postulate a tractable posterior and formulate a lower…

Machine Learning · Statistics 2019-06-12 Nikolaos Gianniotis , Christoph Schnörr , Christian Molkenthin , Sanjay Singh Bora
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