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The unitary coupled cluster (UCC) approximation is one of the more promising wave-function ans\"atze for electronic structure calculations on quantum computers via the variational quantum eigensolver algorithm. However, for large systems…

Quantum Physics · Physics 2021-09-30 Jia Chen , Hai-Ping Cheng , James K. Freericks

We present evidence in favor of the possibility of treating an out-of-equilibrium supercooled simple liquid as a system in quasi-equilibrium. Two different temperatures, one controlled by the external bath and one internally selected by the…

Soft Condensed Matter · Physics 2009-10-31 Francesco Sciortino , Piero Tartaglia

The fractal dimensions and the percolation exponents of the geometrical spin clusters of like sign at criticality, are obtained numerically for an Ising model with temperature-dependent annealed bond dilution, also known as the thermalized…

Statistical Mechanics · Physics 2012-04-03 S. Davatolhagh , M. Moshfeghian , A. A. Saberi

Interacting particle systems in a finite-volume in equilibrium are often described by a grand-canonical ensemble induced by the corresponding Hamiltonian, i.e. a finite-volume Gibbs measure. However, in practice, directly measuring this…

Mathematical Physics · Physics 2024-07-30 Fabio Frommer

Recently, Velazquez and Curilef have proposed a methodology to extend Monte Carlo algorithms based on canonical ensemble, which is aimed to overcome slow sampling problems associated with temperature-driven discontinuous phase transitions.…

Statistical Mechanics · Physics 2013-07-31 L. Velazquez , J. C. Castro-Palacio

It was recently shown [Phys. Rev. Lett. {\bf 110}, 227201 (2013)] that the critical behavior of the random-field Ising model in three dimensions is ruled by a single universality class. This conclusion was reached only after a proper taming…

Disordered Systems and Neural Networks · Physics 2016-06-21 Nikolaos G. Fytas , Victor Martin-Mayor

The importance-sampling Monte Carlo algorithm appears to be the universally optimal solution to the problem of sampling the state space of statistical mechanical systems according to the relative importance of configurations for the…

Statistical Mechanics · Physics 2010-06-22 Martin Weigel

We address the problem of clustering a set of points in $\mathbb{R}^d$ with axis-parallel clusters. Previous exact approaches to this problem are mostly based on integer programming formulations and can only solve to optimality instances of…

Discrete Mathematics · Computer Science 2024-10-16 Diego Delle Donne , Javier Marenco , Eduardo Moreno

We establish a general framework for developing approximation algorithms for a class of counting problems. Our framework is based on the cluster expansion of abstract polymer models formalism of Koteck\'y and Preiss. We apply our framework…

Quantum Physics · Physics 2024-01-18 Ryan L. Mann , Romy M. Minko

We study numerically the non-equilibrium critical properties of the Ising model defined on direct products of graphs, obtained from factor graphs without phase transition (Tc = 0). On this class of product graphs, the Ising model features a…

Statistical Mechanics · Physics 2010-12-20 R. Burioni , F. Corberi , A. Vezzani

We describe a generalized scheme for the probability-changing cluster (PCC) algorithm, based on the study of the finite-size scaling property of the correlation ratio, the ratio of the correlation functions with different distances. We…

Statistical Mechanics · Physics 2009-11-07 Yutaka Okabe , Yusuke Tomita , Chiaki Yamaguchi

Markov Chain Monte Carlo (MCMC) underlies both statistical physics and combinatorial optimization, but mixes slowly near critical points and in rough landscapes. Parallel Tempering (PT) improves mixing by swapping replicas across…

Machine Learning · Computer Science 2025-09-30 Saleh Bunaiyan , Corentin Delacour , Shuvro Chowdhury , Kyle Lee , Kerem Y. Camsari

We present here two novel algorithms for simulated tempering simulations, which break detailed balance condition (DBC) but satisfy the skewed detailed balance to ensure invariance of the target distribution. The irreversible methods we…

Statistical Mechanics · Physics 2021-02-03 Fahim Faizi , Pedro J. Buigues , George Deligiannidis , Edina Rosta

We propose to use wavefunction overlaps obtained from a quantum computer as inputs for the classical split-amplitude techniques, tailored and externally corrected coupled cluster, to achieve balanced treatment of static and dynamic…

This paper proposes Incremental Seeded Expectation Maximization, an algorithm that improves upon the traditional Expectation Maximization computational flow for clusterwise or finite mixture linear regression tasks. The proposed method…

Computation · Statistics 2025-07-08 Ye Chow Kuang , Melanie Ooi

We present a novel algorithm that allows one to obtain temperature dependent properties of quantum lattice models in the thermodynamic limit from exact diagonalization of small clusters. Our Numerical Linked Cluster (NLC) approach provides…

Strongly Correlated Electrons · Physics 2007-05-23 Marcos Rigol , Tyler Bryant , Rajiv R. P. Singh

We apply a replica inference based Potts model method to unsupervised image segmentation on multiple scales. This approach was inspired by the statistical mechanics problem of "community detection" and its phase diagram. Specifically, the…

Statistical Mechanics · Physics 2015-05-28 Dandan Hu , Peter Ronhovde , Zohar Nussinov

Employing the path integral approach, we calculate the semiclassical equilibrium density matrix of a particle moving in a nonlinear potential field for coordinates near the top of a potential barrier. As the temperature is decreased, near a…

Quantum Physics · Physics 2015-06-26 F. J. Weiper , J. Ankerhold , H. Grabert

Exponential averages that appear in integral fluctuation theorems can be recast as a sum over moments of thermodynamic observables. We use two examples to show that such moment series can exhibit non-uniform convergence in certain singular…

Statistical Mechanics · Physics 2022-05-31 Hila Katznelson , Saar Rahav

We consider an infinite-dimensional stochastic clustering model on $\mathbb{R}$. In discrete time, each point of a unit-intensity simple point process moves halfway toward either of its left or right neighbors, chosen uniformly at random.…

Probability · Mathematics 2026-03-10 Partha S. Dey , S. Rasoul Etesami , Aditya S. Gopalan
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