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The computational complexity of simulating quantum many-body systems generally scales exponentially with the number of particles. This enormous computational cost prohibits first principles simulations of many important problems throughout…

Quantum Physics · Physics 2023-05-31 Chao Yin , Andrew Lucas

While recent advances have established efficient quantum algorithms for preparing Gibbs states of finite-dimensional systems, comparable complexity results for bosonic and other infinite-dimensional models remain unexplored. We introduce…

Quantum Physics · Physics 2026-04-08 Simon Becker , Cambyse Rouzé , Robert Salzmann

Systems in thermal equilibrium at non-zero temperature are described by their Gibbs state. For classical many-body systems, the Metropolis-Hastings algorithm gives a Markov process with a local update rule that samples from the Gibbs…

Quantum Physics · Physics 2023-09-20 Daniel Zhang , Jan Lukas Bosse , Toby Cubitt

When an isolated system is brought in contact with a heat bath its final energy is random and follows the Gibbs distribution -- a cornerstone of statistical physics. The system's energy can also be changed by performing non-adiabatic work…

Statistical Mechanics · Physics 2011-12-01 Guy Bunin , Luca D'Alessio , Yariv Kafri , Anatoli Polkovnikov

A key open question in the glass transition field is whether a finite temperature thermodynamic transition to the glass state exists or not. Recent simulations of coupled replicas in atomistic models have found signatures of a static…

Statistical Mechanics · Physics 2015-06-18 Juan P. Garrahan

While gradient-based discrete samplers are effective in sampling from complex distributions, they are susceptible to getting trapped in local minima, particularly in high-dimensional, multimodal discrete distributions, owing to the…

Machine Learning · Statistics 2025-05-21 Luxu Liang , Yuhang Jia , Feng Zhou

In this work, we show how Gibbs or thermal states appear dynamically in closed quantum many-body systems, building on the program of dynamical typicality. We introduce a novel perturbation theorem for physically relevant weak system-bath…

Quantum Physics · Physics 2012-03-13 Arnau Riera , Christian Gogolin , Jens Eisert

The Gibbs sampler (a.k.a. Glauber dynamics and heat-bath algorithm) is a popular Markov Chain Monte Carlo algorithm which iteratively samples from the conditional distributions of a probability measure $\pi$ of interest. Under the…

Probability · Mathematics 2026-01-21 Filippo Ascolani , Hugo Lavenant , Giacomo Zanella

We describe the study of thermodynamics of materials using replica-exchange Wang-Landau (REWL) sampling, a generic framework for massively parallel implementations of the Wang-Landau Monte Carlo method. To evaluate the performance and…

Materials Science · Physics 2014-11-18 Dilina Perera , Ying Wai Li , Markus Eisenbach , Thomas Vogel , David P. Landau

The theory of superstatistics, originally proposed for the study of complex nonequilibrium systems, has recently been extended to studies of small systems interacting with a finite environment, because such systems display interestingly…

Statistical Mechanics · Physics 2023-04-19 Constanza Farías , Sergio Davis

A recombination reaction model for high-temperature chemical kinetics is derived from ab initio simulations data. A kinetic recombination rate model is derived using a recently developed ab initio state-specific dissociation model and the…

Chemical Physics · Physics 2020-09-15 Narendra Singh , Thomas Schwartzentruber

We present a study of the parallel tempering (replica exchange) Monte Carlo method, with special focus on the feedback-optimized parallel tempering algorithm, used for generating an optimal set of simulation temperatures. This method is…

Statistical Mechanics · Physics 2014-10-15 Krzysztof Lewandowski , Piotr Knychala , Michal Banaszak

We show that spin chains in thermal equilibrium have a correlation structure in which individual regions are strongly correlated at most with their near vicinity. We quantify this with alternative notions of the conditional mutual…

A statistical system is classically defined on a set of microstates $E$ by a global energy function $H : E \to \mathbb{R}$, yielding Gibbs probability measures (softmins) $\rho^\beta(H)$ for every inverse temperature $\beta = T^{-1}$. Gibbs…

Statistical Mechanics · Physics 2022-07-05 Olivier Peltre

We propose and use a novel, hybrid Monte Carlo algorithm that combines configurational bias particle swaps with parallel tempering. We use this new method to simulate a standard model of a glass forming binary mixture above and below the…

Soft Condensed Matter · Physics 2009-11-11 Elijah Flenner , Grzegorz Szamel

We experimentally verify the Jarzynski and W\"ojcik quantum heat exchange fluctuation relation by implementing the interferometric technique in liquid-state Nuclear Magnetic Resonance setup and study the exchange heat statistics between two…

Statistical Mechanics · Physics 2019-10-30 Soham Pal , T S Mahesh , Bijay Kumar Agarwalla

We consider the statistical mechanics of a classical particle in a one-dimensional box subjected to a random potential which constitutes a Wiener process on the coordinate axis. The distribution of the free energy and all correlation…

Condensed Matter · Physics 2009-10-28 Kurt Broderix , Reiner Kree

In this work, we investigate the heat exchange between two quantum systems whose initial equilibrium states are described by the generalized Gibbs ensemble. First, we generalize the fluctuation relations for heat exchange discovered by…

Quantum Physics · Physics 2018-09-13 Bo-Bo Wei

Under the Ansatz that the occupation times of a system with finitely many states are given by the Gibbs distribution, an effective temperature is uniquely determined (up to a choice of scale), and may be computed de novo, without any…

Statistical Mechanics · Physics 2009-04-27 Steve Huntsman

In this paper, we introduce a new and efficient data augmentation approach to the posterior inference of the models with shape parameters when the reciprocal gamma function appears in full conditional densities. Our approach is to…

Methodology · Statistics 2023-11-08 Yasuyuki Hamura , Kaoru Irie , Shonosuke Sugasawa
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