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Related papers: Robust Parameter Selection for Parallel Tempering

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We extend the formalism of pure state thermodynamics to matrix product states. In pure state thermodynamics finite temperature properties of quantum systems are derived without the need of statistical mechanics ensembles, but instead using…

Quantum Physics · Physics 2013-10-31 Silvano Garnerone

We introduce a modification of the well-known Metropolis importance sampling algorithm by using a methodology inspired on the consideration of the reparametrization invariance of the microcanonical ensemble. The most important feature of…

Statistical Mechanics · Physics 2007-05-23 L. Velazquez , J. C. Castro Palacio

Monte Carlo computer simulations are virtually the only way to analyze the thermodynamic behavior of a system in a precise way. However, the various existing methods exhibit extreme differences in their efficiency, depending on model…

Statistical Mechanics · Physics 2011-07-05 Michael Bachmann

This paper develops a novel sequential Monte Carlo (SMC) approach for joint state and parameter estimation that can deal efficiently with abruptly changing parameters which is a common case when tracking maneuvering targets. The approach…

Computation · Statistics 2015-10-12 Christopher Nemeth , Paul Fearnhead , Lyudmila Mihaylova

We discuss the efficiency of the so-called parallel tempering method to equilibrate glassy systems also at low temperatures. The main focus is on two structural glass models, SiO_2 and a Lennard-Jones system, but we also investigate a fully…

Statistical Mechanics · Physics 2007-05-23 Walter Kob , Claudio Brangian , Torsten Stuhn , Ryoichi Yamamoto

Simultaneous estimation of multiple parameters in quantum metrological models is complicated by factors relating to the (i) existence of a single probe state allowing for optimal sensitivity for all parameters of interest, (ii) existence of…

Quantum Physics · Physics 2019-02-01 Sammy Ragy , Marcin Jarzyna , Rafal Demkowicz-Dobrzanski

We introduce two kinds of quantum algorithms to explore microcanonical and canonical properties of many-body systems. The first one is a hybrid quantum algorithm that, given an efficiently preparable state, computes expectation values in a…

Quantum Physics · Physics 2021-05-19 Sirui Lu , Mari Carmen Bañuls , J. Ignacio Cirac

Monte Carlo simulations are performed in classical phase space for a one-dimensional quantum harmonic crystal. Symmetrization effects for spinless bosons and fermions are quantified. The algorithm is tested for a range of parameters against…

Quantum Physics · Physics 2019-04-25 Phil Attard

Monte Carlo simulations of Ising models coupled to heat baths at two different temperatures are used to study a fluctuation relation for the heat exchanged between the two thermostats in a time $\tau$. Different kinetics (single--spin--flip…

Statistical Mechanics · Physics 2009-11-13 A. Piscitelli , F. Corberi , G. Gonnella

Thermal quenching has been used to find metastable materials such as hard steels and metallic glasses. More recently, quenching-based phase control has been applied to correlated electron systems that exhibit metal--insulator, magnetic or…

Materials Science · Physics 2025-04-25 Hiroshi Oike , Hidemaro Suwa , Yasunori Takahashi , Fumitaka Kagawa

Binary magnetic square lattice Ising system with nearest neighbour interactions were simulated using the Monte Carlo technique. Two types of ions were randomly distributed on the lattice sites, one type interacting ferromagnetic and the…

Statistical Mechanics · Physics 2013-01-23 Ike Q. Sikakana

Simulated tempering is popular method of allowing MCMC algorithms to move between modes of a multimodal target density {\pi}. One problem with simulated tempering for multimodal targets is that the weights of the various modes change for…

Computation · Statistics 2019-02-12 Nicholas G. Tawn , Gareth O. Roberts , Jeffrey S. Rosenthal

Density tempering (also called density annealing) is a sequential Monte Carlo approach to Bayesian inference for general state models; it is an alternative to Markov chain Monte Carlo. When applied to state space models, it moves a…

Methodology · Statistics 2022-04-05 David Gunawan , Robert Kohn , Minh Ngoc Tran

Markov chain Monte Carlo is an inherently serial algorithm. Although likelihood calculations for individual steps can sometimes be parallelized, the serial evolution of the process is widely viewed as incompatible with parallelization,…

Computation · Statistics 2013-12-31 Douglas N. VanDerwerken , Scott C. Schmidler

Algorithms for simulating complex physical systems or solving difficult optimization problems often resort to an annealing process. Rather than simulating the system at the temperature of interest, an annealing algorithm starts at a…

Computational Physics · Physics 2015-04-02 Michael Habeck

Motivation: Estimating parameters from data is a key stage of the modelling process, particularly in biological systems where many parameters need to be estimated from sparse and noisy data sets. Over the years, a variety of heuristics have…

Quantitative Methods · Quantitative Biology 2011-11-07 Mariano Beguerisse-Diaz , Baojun Wang , Radhika Desikan , Mauricio Barahona

The simulation of rare events is one of the key problems in atomistic simulations. Towards its solution a plethora of methods have been proposed. Here we combine two such methods metadynamics and inte-grated tempering sampling. In…

Chemical Physics · Physics 2018-10-29 Yi Isaac Yang , Haiyang Niu , Michele Parrinello

A recent reformulation [1] of the problem of Coulomb gases in the presence of a dynamical dielectric medium showed that finite temperature simulations of such systems can be accomplished on the basis of completely local Hamiltonians on a…

Soft Condensed Matter · Physics 2009-11-11 A. Duncan , R. D. Sedgewick

Standard methods in computer model calibration treat the calibration parameters as constant throughout the domain of control inputs. In many applications, systematic variation may cause the best values for the calibration parameters to…

Methodology · Statistics 2017-02-09 D. Andrew Brown , Sez Atamturktur

We present a massive equilibrium simulation of the three-dimensional Ising spin glass at low temperatures. The Janus special-purpose computer has allowed us to equilibrate, using parallel tempering, L=32 lattices down to T=0.64 Tc. We…