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Scalable quantum algorithms for the simulation of quantum many-body systems in thermal equilibrium are important for predicting properties of quantum matter at finite temperatures. Here we describe and benchmark a quantum computing version…

Quantum Physics · Physics 2023-09-20 João C. Getelina , Niladri Gomes , Thomas Iadecola , Peter P. Orth , Yong-Xin Yao

Using MCMC to sample from a target distribution, $\pi(x)$ on a $d$-dimensional state space can be a difficult and computationally expensive problem. Particularly when the target exhibits multimodality, then the traditional methods can fail…

Methodology · Statistics 2026-01-14 Nicholas G. Tawn , Gareth O. Roberts

Temperature of a finite-sized system fluctuates due to the thermal fluctuations. However, a systematic mathematical framework for measuring or estimating the temperature is still underdeveloped. Here, we incorporate the estimation theory in…

Statistical Mechanics · Physics 2026-03-17 Shaoyong Zhang , Zhaoyu Fei , Xiaoguang Wang

Simulation of warm dense matter requires computational methods that capture both quantum and classical behavior efficiently under high-temperature, high-density conditions. Currently, density functional theory molecular dynamics is used to…

Chemical Physics · Physics 2015-10-21 Attila Cangi , Aurora Pribram-Jones

We investigate variational problems in quantum thermodynamics at positive temperature, in which admissible states are constrained by prescribed outcomes of a finite set of measurements. We solve a problem raised by the recent work [Liu,…

Mathematical Physics · Physics 2026-03-09 Emanuele Caputo , Augusto Gerolin , Nataliia Monina , Pavlo Pelikh , Lorenzo Portinale

Sampling Boltzmann probability distributions plays a key role in machine learning and optimization, motivating the design of hardware accelerators such as Ising machines. While the Ising model can in principle encode arbitrary optimization…

Machine Learning · Computer Science 2025-08-01 Corentin Delacour , M Mahmudul Hasan Sajeeb , Joao P. Hespanha , Kerem Y. Camsari

The problem of simulating the thermal behavior of quantum systems remains a central open challenge in quantum computing. Unlike well-established quantum algorithms for unitary dynamics, \emph{provably efficient} algorithms for preparing…

Quantum Physics · Physics 2026-05-14 Dominik Hahn , Ryan Sweke , Abhinav Deshpande , Oles Shtanko

Partition functions of probability distributions are important quantities for model evaluation and comparisons. We present a new method to compute partition functions of complex and multimodal distributions. Such distributions are often…

Machine Learning · Statistics 2016-05-27 David Carlson , Patrick Stinson , Ari Pakman , Liam Paninski

We apply estimation theory to a system formed by two interacting trapped ions. By using the Fisher matrix formalism, we introduce a simple scheme for estimation of the temperature of the longitudinal vibrational modes of the ions. We use…

Quantum Physics · Physics 2022-05-26 O. P. de Sá Neto , H. A. S. Costa , G. A. Prataviera , M. C. de Oliveira

We discuss the application of techniques of quantum estimation theory and quantum metrology to thermometry. The ultimate limit to the precision at which the temperature of a system at thermal equilibrium can be determined is related to the…

Quantum Physics · Physics 2019-05-01 Antonella De Pasquale , Thomas M. Stace

Classical methods to control heating systems are often marred by suboptimal performance, inability to adapt to dynamic conditions and unreasonable assumptions e.g. existence of building models. This paper presents a novel deep reinforcement…

Applications · Statistics 2018-05-11 Adam Nagy , Hussain Kazmi , Farah Cheaib , Johan Driesen

Thermal errors in machine tools significantly impact machining precision and productivity. Traditional thermal error correction/compensation methods rely on measured temperature-deformation fields or on transfer functions. Most existing…

Machine Learning · Computer Science 2025-10-07 C. Coelho , M. Hohmann , D. Fernández , L. Penter , S. Ihlenfeldt , O. Niggemann

We present a fast adaptive method for the evaluation of heat potentials, which plays a key role in the integral equation approach for the solution of the heat equation, especially in a non-stationary domain. The algorithm utilizes a…

Numerical Analysis · Mathematics 2024-12-06 Chengyue Song , Jun Wang

We derive new results comparing the asymptotic variance of diffusions by writing them as appropriate limits of discrete-time birth-death chains which themselves satisfy Peskun orderings. We then apply our results to simulated tempering…

Probability · Mathematics 2014-01-16 Gareth O. Roberts , Jeffrey S. Rosenthal

We present a generalization of the classical Wang-Landau algorithm [Phys. Rev. Lett. 86, 2050 (2001)] to quantum systems. The algorithm proceeds by stochastically evaluating the coefficients of a high temperature series expansion or a…

Statistical Mechanics · Physics 2009-09-29 Matthias Troyer , Stefan Wessel , Fabien Alet

Metastability is a formidable challenge to Markov chain Monte Carlo methods. In this paper we present methods for algorithm design to meet this challenge. The design problem we consider is temperature selection for the infinite swapping…

Probability · Mathematics 2020-11-12 Paul Dupuis , Guo-Jhen Wu

We present an efficient sampling method for computing a partition function and accelerating configuration sampling. The method performs a random walk in the $\lambda$ space, with $\lambda$ being any thermodynamic variable that characterizes…

Computational Physics · Physics 2010-03-02 Cheng Zhang , Jianpeng Ma

We study the Schwinger model at finite-temperature regime using a quantum-classical hybrid algorithm. The preparation of thermal state on quantum circuit presents significant challenges. To address this, we adopt the Thermal Pure Quantum…

High Energy Physics - Lattice · Physics 2023-11-21 Juan W. Pedersen , Etsuko Itou , Rong-Yang Sun , Seiji Yunoki

We study the theoretical complexity of simulated tempering for sampling from mixtures of log-concave components differing only by location shifts. The main result establishes the first polynomial-time guarantee for simulated tempering…

Computation · Statistics 2025-11-04 Quan Zhou

A paradigm shift in quantum thermometry is proposed. To date, thermometry has relied on local estimation, which is useful to reduce statistical fluctuations once the temperature is very well known. In order to estimate temperatures in cases…

Quantum Physics · Physics 2021-11-04 Jesús Rubio , Janet Anders , Luis A. Correa