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In this paper, we study a class of multilinear Gibbs measures with Hamiltonian given by a generalized $\mathrm{U}$-statistic and with a general base measure. Expressing the asymptotic free energy as an optimization problem over a space of…

Probability · Mathematics 2026-03-31 Sohom Bhattacharya , Nabarun Deb , Sumit Mukherjee

The question of the number of thermodynamic states present in the low-temperature phase of the three-dimensional Edwards-Anderson Ising spin glass is addressed by studying spin and link overlap distributions using population annealing Monte…

Disordered Systems and Neural Networks · Physics 2017-11-22 Wenlong Wang , Jonathan Machta , Humberto Munoz-Bauza , Helmut G. Katzgraber

We give the first comprehensive analysis of the effect of boundary conditions on the mixing time of the Glauber dynamics in the so-called Bethe approximation. Specifically, we show that spectral gap and the log-Sobolev constant of the…

Probability · Mathematics 2009-11-10 Fabio Martinelli , Alistair Sinclair , Dror Weitz

Annealing is the process of gradually lowering the temperature of a system to guide it towards its lowest energy states. In an accompanying paper [Luo et al. Phys. Rev. E 108, L052105 (2023)], we derived a general bound on annealing…

Statistical Mechanics · Physics 2023-11-20 Yutong Luo , Yi-Zheng Zhen , Xiangjing Liu , Daniel Ebler , Oscar Dahlsten

We propose a new method for estimating rare event probabilities when independent samples are available. It is assumed that the underlying probability measures satisfy a large deviations principle with a scaling parameter $\varepsilon$ that…

Probability · Mathematics 2018-11-06 Paul Dupuis , Guo-Jhen Wu , Michael Snarski

The Ising model is important in statistical modeling and inference in many applications, however its normalizing constant, mean number of active vertices and mean spin interaction -- quantities needed in inference -- are computationally…

Methodology · Statistics 2024-01-23 Alejandro Murua-Sazo , Ranjan Maitra

In this paper, we consider Langevin processes with mechanical constraints. The latter are a fundamental tool in molecular dynamics simulation for sampling purposes and for the computation of free energy differences. The results of this…

Statistical Mechanics · Physics 2011-04-19 Tony Lelievre , Mathias Rousset , Gabriel Stoltz

The continuous random energy model (CREM) is a toy model of spin glasses on $\{0,1\}^N$ that, in the limit, exhibits an infinitely hierarchical correlation structure. We give two polynomial-time algorithms to approximately sample from the…

Probability · Mathematics 2025-02-20 Holden Lee , Qiang Wu

Compressed sensing allows for the recovery of sparse signals from few measurements, whose number is proportional to the sparsity of the unknown signal, up to logarithmic factors. The classical theory typically considers either random linear…

Functional Analysis · Mathematics 2025-04-02 Giovanni S. Alberti , Alessandro Felisi , Matteo Santacesaria , S. Ivan Trapasso

We consider testing for the parameters of Ferromagnetic Ising models. While testing for the presence of possibly sparse magnetizations, we provide a general lower bound of minimax separation rates which yields sharp results in high…

Statistics Theory · Mathematics 2019-06-04 Rajarshi Mukherjee , Gourab Ray

The Ising model on an alternating triangular lattice with the nearest-neighbor interaction in a magnetic field is presented. Exact solution of this model is found. The thermodynamic quantities, like free energy, specific heat a finite…

Statistical Mechanics · Physics 2014-10-08 Elías Ríos

We construct an extensive adiabatic invariant for a Klein-Gordon chain in the thermodynamic limit. In particular, given a fixed and sufficiently small value of the coupling constant $a$, the evolution of the adiabatic invariant is…

Dynamical Systems · Mathematics 2015-04-27 Antonio Giorgilli , Simone Paleari , Tiziano Penati

We study the design and implementation of numerical methods to solve the generalized Langevin equation (GLE) focusing on canonical sampling properties of numerical integrators. For this purpose, we cast the GLE in an extended phase space…

Numerical Analysis · Mathematics 2020-12-09 Benedict Leimkuhler , Matthias Sachs

Quantum Gibbs state sampling algorithms generally suffer from either scaling exponentially with system size or requiring specific knowledge of spectral properties \textit{a priori}. Also, these algorithms require a large overhead of bath or…

Quantum Physics · Physics 2020-09-02 Jeffrey Cohn , Khadijeh Sona Najafi , Forest Yang , Barbara Jones , James K. Freericks

A family of collective variables is proposed to perform exact dynamical coarse-graining even in systems without time scale separation. More precisely, it is shown that these variables are not slow in general but they satisfy an overdamped…

Statistical Mechanics · Physics 2015-06-19 Jianfeng Lu , Eric Vanden-Eijnden

The low-temperature properties and crossover phenomena of $d$-dimensional transverse Ising-like systems within the influence domain of the quantum critical point are investigated solving the appropriate one-loop renormalization group…

Statistical Mechanics · Physics 2009-11-10 A. Caramico D'Auria , L. De Cesare , I. Rabuffo

We introduce and analyze a nonlinear exchange dynamics for Ising spin systems with arbitrary interactions. The evolution is governed by a quadratic Boltzmann-type equation that conserves the mean magnetization. Collisions are encoded…

Probability · Mathematics 2025-11-10 Pietro Caputo , Mario Morellini

Infinite-range interactions are known to facilitate the production of highly entangled states with applications in quantum information and metrology. However, many experimental systems have interactions that decay with distance, and the…

Quantum Gases · Physics 2016-12-26 Michael Foss-Feig , Zhe-Xuan Gong , Alexey V. Gorshkov , Charles W. Clark

Stochastic thermostats based on the Langevin equation, in which a system is coupled to an external heat bath, are popular methods for temperature control in molecular dynamics simulations due to their ergodicity and their ease of…

Chemical Physics · Physics 2018-05-23 Mahdi Hijazi , David M. Wilkins , Michele Ceriotti

We introduce a novel approach for decomposing and learning every scale of a given multiscale objective function in $\mathbb{R}^d$, where $d\ge 1$. This approach leverages a recently demonstrated implicit bias of the optimization method of…

Numerical Analysis · Mathematics 2024-01-09 Xingjie Helen Li , Molei Tao
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