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This article outlines how the quantum Monte Carlo directed loop update recently introduced can be applied to a wide class of quantum lattice models. Several models are considered: Spin-S XXZ models with longitudinal and transverse magnetic…

Statistical Mechanics · Physics 2009-11-07 Olav F. Syljuasen

We exactly rewrite the Z(2) lattice gauge theory with standard plaquette action as a random surface model equivalent to the untruncated set of its strong coupling graphs. By extending the worm approach applied to spin models we simulate…

High Energy Physics - Lattice · Physics 2015-06-12 Tomasz Korzec , Ulli Wolff

We propose a variant of the Simulated Annealing method for optimization in the multivariate analysis of differentiable functions. The method uses global actualizations via the Hybrid Monte Carlo algorithm in their generalized version for…

Statistical Mechanics · Physics 2009-10-30 R. Salazar , R. Toral

Estimation in generalized linear models (GLM) is complicated by the presence of constraints. One can handle constraints by maximizing a penalized log-likelihood. Penalties such as the lasso are effective in high dimensions, but often lead…

Machine Learning · Statistics 2017-11-07 Jason Xu , Eric C. Chi , Kenneth Lange

The effect of different move sets on the folding kinetics of the Monte Carlo simulations is analysed based on the conformation-network and the temperature-dependent folding kinetics. A new scheme of implementing Metropolis algorithm is…

Soft Condensed Matter · Physics 2007-05-23 Yu-Pin Luo , Ming-Chang Huang , Yen-Liang Chou , Tsong-Ming Liaw

Ising formulations are widely utilized to solve combinatorial optimization problems, and a variety of quantum or semiconductor-based hardware has recently been made available. In combinatorial optimization problems, the existence of local…

Applied Physics · Physics 2024-03-15 Yoshiki Sato , Makiko Konoshima , Hirotaka Tamura , Jun Ohkubo

Importance sampling is a rare event simulation technique used in Monte Carlo simulations to bias the sampling distribution towards the rare event of interest. By assigning appropriate weights to sampled points, importance sampling allows…

We extend to quenched disordered systems the variational scheme for real space renormalization group calculations that we recently introduced for homogeneous spin Hamiltonians. When disorder is present our approach gives access to the flow…

Statistical Mechanics · Physics 2020-11-11 Yantao Wu , Roberto Car

With the help of the replica exchange Monte Carlo method and the improved Monte Carlo renormalization-group scheme, we investigate over a wide area in the phase diagram of the Gaussian random field Ising model on the simple cubic lattice.…

Disordered Systems and Neural Networks · Physics 2009-10-31 M. Itakura

We present an adaptive multi-GPU Exchange Monte Carlo method designed for the simulation of the 3D Random Field Model. The algorithm design is based on a two-level parallelization scheme that allows the method to scale its performance in…

Computational Physics · Physics 2016-08-10 C. A. Navarro , Wei Huang , Youjin Deng

We show in this paper the results on the phase transition of the so-called fully frustrated simple cubic lattice with the Ising spin model. We use here the Monte Carlo method with the flat energy-histogram Wang-Landau technique which is…

Statistical Mechanics · Physics 2015-05-20 V. Thanh Ngo , D. Tien Hoang , Hung The Diep

Disordered lattice spin systems are crucial in both theoretical and applied physics. However, understanding their properties poses significant challenges for Monte Carlo simulations. In this work, we investigate the two-dimensional…

Statistical Mechanics · Physics 2025-03-11 Tao Chen , Erdong Guo , Wanzhou Zhang , Pan Zhang , Youjin Deng

The Poisson Generalized Linear Model (GLM) is a foundational tool for analyzing neural spike train data. However, standard implementations rely on discretizing spike times into binned count data, limiting temporal resolution and…

Neurons and Cognition · Quantitative Biology 2025-10-27 Arina Medvedeva , Edoardo Balzani , Alex H Williams , Stephen L Keeley

Working within the Stochastic Series Expansion (SSE) framework, we construct efficient quantum cluster algorithms for transverse field Ising antiferromagnets on the pyrochlore lattice and the planar pyrochlore lattice, for the fully…

Strongly Correlated Electrons · Physics 2019-07-24 Sounak Biswas , Kedar Damle

In dynamic Monte Carlo simulations, using for example the Metropolis dynamic, it is often required to simulate for long times and to simulate large systems. We present an overview of advanced algorithms to simulate for larger times and to…

Statistical Mechanics · Physics 2007-05-23 M. A. Novotny , Alice K. Kolakowska , G. Korniss

Monte Carlo simulation using a combination of Wang Landau (WL) and Transition Matrix (TM) Monte Carlo algorithms to simulate two lattice spin models with continuous energy is described. One of the models, the one dimensional Lebwohl-Lasher…

Statistical Mechanics · Physics 2009-11-13 Shyamal Bhar , Soumen Kumar Roy

We describe a number of recently developed cluster-flipping algorithms for the efficient simulation of classical spin models near their critical temperature. These include the algorithms of Wolff, Swendsen and Wang, and Niedermeyer, as well…

Condensed Matter · Physics 2007-05-23 G. T. Barkema , M. E. J. Newman

The properties of a dilute Ising magnet are studied using a two-dimensional spin-pseudospin model with charged impurities and a frustration caused by the competition of the charge and magnetic orderings. Based on the classical Monte Carlo…

Statistical Mechanics · Physics 2021-09-23 D. N. Yasinskaya , V. A. Ulitko , Yu. D. Panov

The classical Monte Carlo method is used to study the properties of the ground state and phase transitions of the spin-pseudospin model, which describes a two-dimensional Ising magnet with competing charge and spin interactions. This…

Statistical Mechanics · Physics 2021-09-23 D. N. Yasinskaya , V. A. Ulitko , Yu. D. Panov

In complex systems such as spin systems and protein systems, conventional simulations in the canonical ensemble will get trapped in states of energy local minima. We employ the generalized-ensemble algorithms in order to overcome this…

Statistical Mechanics · Physics 2009-11-07 T. Nagasima , Y. Sugita , A. Mitsutake , Y. Okamoto
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