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Parallel tempering (PT) methods are a popular class of Markov chain Monte Carlo schemes used to sample complex high-dimensional probability distributions. They rely on a collection of $N$ interacting auxiliary chains targeting tempered…

Computation · Statistics 2021-07-28 Saifuddin Syed , Alexandre Bouchard-Côté , George Deligiannidis , Arnaud Doucet

We revisit the question of describing critical spin systems and field theories using matrix product states, and formulate a scaling hypothesis in terms of operators, eigenvalues of the transfer matrix, and lattice spacing in the case of…

Statistical Mechanics · Physics 2019-12-25 Bram Vanhecke , Jutho Haegeman , Karel Van Acoleyen , Laurens Vanderstraeten , Frank Verstraete

The order parameter cumulants of infinite matrix product ground states are evaluated across a quantum phase transition. A scheme using the Binder cumulant, finite-entanglement scaling and scaling functions to obtain the critical point and…

Strongly Correlated Electrons · Physics 2020-01-01 Jason C. Pillay , Ian P. McCulloch

We study the Weighted Min Cut problem in the Adaptive Massively Parallel Computation (AMPC) model. In 2019, Behnezhad et al. [3] introduced the AMPC model as an extension of the Massively Parallel Computation (MPC) model. In the past…

Data Structures and Algorithms · Computer Science 2022-05-30 MohammadTaghi Hajiaghayi , Marina Knittel , Jan Olkowski , Hamed Saleh

The expectation-maximization (EM) algorithm is a well-known iterative method for computing maximum likelihood estimates from incomplete data. Despite its numerous advantages, a main drawback of the EM algorithm is its frequently observed…

Computation · Statistics 2018-08-14 Nicholas C. Henderson , Ravi Varadhan

We define geometric critical exponents for systems that undergo continuous second order classical and quantum phase transitions. These relate scalar quantities on the information theoretic parameter manifolds of such systems, near…

Statistical Mechanics · Physics 2015-06-19 Prashant Kumar , Tapobrata Sarkar

In this article we propose a novel MCMC method based on deterministic transformations T: X x D --> X where X is the state-space and D is some set which may or may not be a subset of X. We refer to our new methodology as Transformation-based…

Computation · Statistics 2013-10-21 Somak Dutta , Sourabh Bhattacharya

For a second-order phase transition the critical energy range of interest is larger than the energy range covered by a canonical Monte Carlo simulation at the critical temperature. Such an extended energy range can be covered by performing…

Statistical Mechanics · Physics 2008-11-26 Bernd A. Berg , Wolfhard Janke

Although the Bayesian paradigm offers a formal framework for estimating the entire probability distribution over uncertain parameters, its online implementation can be challenging due to high computational costs. We suggest the Adaptive…

Machine Learning · Computer Science 2023-10-23 Pedram Agand , Mo Chen , Hamid D. Taghirad

We study the non-steady relaxation of a driven one-dimensional elastic interface at the depinning transition by extensive numerical simulations concurrently implemented on graphics processing units (GPUs). We compute the time-dependent…

Statistical Mechanics · Physics 2013-06-03 Ezequiel E. Ferrero , Sebastián Bustingorry , Alejandro B. Kolton

We present extensive Monte Carlo simulations on a two-dimensional XY model with a modified form of interaction potential. Thermodynamic quantities other than energy, specific heat etc (such as magnetization, susceptibility, fourth order…

Statistical Mechanics · Physics 2013-05-24 Suman Sinha

The physics of Anderson transitions between localized and metallic phases in disordered systems is reviewed. We focus on the character of criticality as well as on underlying symmetries and topologies that are crucial for understanding…

Disordered Systems and Neural Networks · Physics 2014-11-21 A. D. Mirlin , F. Evers , I. V. Gornyi , P. M. Ostrovsky

We use the recently developed finite cluster typical medium approach to study the Anderson localization transition in three dimensions. Applying our method to the box and binary alloy disorder distributions, we find a fast convergence with…

Disordered Systems and Neural Networks · Physics 2021-04-07 H. Terletska , A. Moilanen , K. -M. Tam , Y. Zhang , Y. Wang , M. Eisenbach , N. S. Vidhyadhiraja , L. Chioncel , J. Moreno

Anderson transition in quasiperiodic potentials and the associated mobility edges have been a central focus in quantum simulation across multidisciplinary physical platforms. While these transitions have been experimentally observed in…

Quasi-Monte Carlo (QMC) methods for estimating integrals are attractive since the resulting estimators typically converge at a faster rate than pseudo-random Monte Carlo. However, they can be difficult to set up on arbitrary posterior…

Statistics Theory · Mathematics 2018-10-03 Tobias Schwedes , Ben Calderhead

In this work, we propose a generalized alternating Anderson acceleration method, a periodic scheme composed of $t$ fixed-point iteration steps, interleaved with $s$ steps of Anderson acceleration with window size $m$, to solve linear and…

Numerical Analysis · Mathematics 2026-02-02 Yunhui He , Santolo Leveque

The most efficient MC weights for the calculation of physical, canonical expectation values are not necessarily those of the canonical ensemble. The use of suitably generalized ensembles can lead to a much faster convergence of the…

Statistical Mechanics · Physics 2011-01-24 Bernd A. Berg

Linked cluster expansions are generalized from an infinite to a finite volume. They are performed to 20th order in the expansion parameter to approach the critical region from the symmetric phase. A new criterion is proposed to distinguish…

High Energy Physics - Lattice · Physics 2009-10-28 H. Meyer-Ortmanns , T. Reisz

Evaluating the statistical dimension is a common tool to determine the asymptotic phase transition in compressed sensing problems with Gaussian ensemble. Unfortunately, the exact evaluation of the statistical dimension is very difficult and…

Information Theory · Computer Science 2019-06-06 Sajad Daei , Farzan Haddadi , Arash Amini , Martin Lotz

We present numerical evidence from Monte Carlo simulations that the superfluid-insulator quantum phase transition of interacting bosons subject to strong disorder in one dimension is controlled by the strong-randomness critical point. At…

Disordered Systems and Neural Networks · Physics 2013-12-04 Susanne Pielawa , Ehud Altman
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