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Understanding the properties of transient gravitational waves and their sources is of broad interest in physics and astronomy. Bayesian inference is the standard framework for astro-physical measurement in transient gravitational-wave…

General Relativity and Quantum Cosmology · Physics 2020-10-07 Rory Smith , Gregory Ashton , Avi Vajpeyi , Colm Talbot

The GW method is a many-body electronic structure technique capable of generating accurate quasiparticle properties for realistic systems spanning physics, chemistry, and materials science. Despite its power, GW is not routinely applied to…

Computational Physics · Physics 2020-02-19 Minjung Kim , Glenn J. Martyna , Sohrab Ismail-Beigi

We introduce a fast algorithm for Gaussian process regression in low dimensions, applicable to a widely-used family of non-stationary kernels. The non-stationarity of these kernels is induced by arbitrary spatially-varying vertical and…

Numerical Analysis · Mathematics 2025-03-28 P. Michael Kielstra , Michael Lindsey

The VB-QMC method is presented in this chapter. It consists of using in quantum Monte Carlo (QMC) approaches with a wave function expressed as a usually short expansion of classical Valence-Bond (VB) structures supplemented by a Jastrow…

Chemical Physics · Physics 2022-08-01 Slavko Radenković , Dominik Domin , Julien Toulouse , Benoît Braïda

This work brings together two powerful concepts in Gaussian processes: the variational approach to sparse approximation and the spectral representation of Gaussian processes. This gives rise to an approximation that inherits the benefits of…

Machine Learning · Statistics 2017-11-09 James Hensman , Nicolas Durrande , Arno Solin

Training and inference in Gaussian processes (GPs) require solving linear systems with $n\times n$ kernel matrices. To address the prohibitive $\mathcal{O}(n^3)$ time complexity, recent work has employed fast iterative methods, like…

Machine Learning · Computer Science 2024-03-12 Kaiwen Wu , Jonathan Wenger , Haydn Jones , Geoff Pleiss , Jacob R. Gardner

Gaussian and discrete non-Gaussian spatial datasets are common across fields like public health, ecology, geosciences, and social sciences. Bayesian spatial generalized linear mixed models (SGLMMs) are a flexible class of models for…

Methodology · Statistics 2025-01-27 Jin Hyung Lee , Ben Seiyon Lee

Quantum Monte Carlo methods have proven to predict atomic and bulk properties of light and non-light elements with high accuracy. Here we report on the first variational quantum Monte Carlo (VMC) calculations for solid surfaces. Taking the…

Materials Science · Physics 2009-10-31 R. Bahnsen , H. Eckstein , W. Schattke , N. Fitzer , R. Redmer

We present a lightweight, flexible, and high-performance framework for inferring the properties of gravitational-wave events. By combining likelihood heterodyning, automatically-differentiable and accelerator-compatible waveforms, and…

Instrumentation and Methods for Astrophysics · Physics 2023-02-13 Kaze W. K. Wong , Maximiliano Isi , Thomas D. P. Edwards

Clusters of sizes ranging from two to five are studied by variational quantum Monte Carlo techniques. The clusters consist of Ar, Ne and hypothetical lighter (``$1 \over 2$-Ne") atoms. A general form of trial function is developed for which…

chem-ph · Physics 2009-10-22 Andrei Mushinski , M. P. Nightingale

We introduce a new path integral Monte Carlo method for investigating nonadiabatic systems in thermal equilibrium and demonstrate an approach to reducing stochastic error. We derive a general path integral expression for the partition…

Chemical Physics · Physics 2019-07-11 Neil Raymond , Dmitri Iouchtchenko , Pierre-Nicholas Roy , Marcel Nooijen

Variational Monte Carlo (VMC) methods are used to sample classically from distributions corresponding to quantum states which have an efficient classical description. VMC methods are based on performing a number of steps of a Markov chain…

Quantum Physics · Physics 2023-10-27 Ashley Montanaro , Stasja Stanisic

We introduce an efficient method to construct optimal and system adaptive basis sets for use in electronic structure and quantum Monte Carlo calculations. The method is based on an embedding scheme in which a reference atom is singled out…

Strongly Correlated Electrons · Physics 2016-02-02 Sandro Sorella , Nicolas Devaux , Mario Dagrada , Guglielmo Mazzola , Michele Casula

Variational methods are a common approach for computing properties of ground states but have not yet found analogous success in finite temperature calculations. In this work we develop a new variational finite temperature algorithm (VAFT)…

Strongly Correlated Electrons · Physics 2017-05-17 Jahan Claes , Bryan K. Clark

This article proposes a Variational Quantum Algorithm to solve linear and nonlinear thermofluid dynamic transport equations. The hybrid classical-quantum framework is applied to problems governed by the heat, wave, and Burgers' equation in…

Quantum Physics · Physics 2025-11-06 Sergio Bengoechea , Paul Over , Dieter Jaksch , Thomas Rung

Effective low-energy theories represent powerful theoretical tools to reduce the complexity in modeling interacting quantum many-particle systems. However, common theoretical methods rely on perturbation theory, which limits their…

Quantum Physics · Physics 2021-11-18 Laura Gentini , Alessandro Cuccoli , Leonardo Banchi

Although the GW approximation is recognized as one of the most accurate theories for predicting materials excited states properties, scaling up conventional GW calculations for large systems remains a major challenge. We present a powerful…

Computational Physics · Physics 2018-03-28 Weiwei Gao , Weiyi Xia , Xiang Gao , Peihong Zhang

The thermodynamic and structural properties of (NH$_4$Cl)$_n$ clusters, n=3-10 are studied. Using the method of simulated annealing, the geometries of several isomers for each cluster size are examined. Jump-walking Monte Carlo simulations…

chem-ph · Physics 2009-10-28 Alexander Matro , David L. Freeman , Robert Q. Topper

We present an effective medium theory based on density functional theory that is implemented in VASP using the PAW method with a plane wave basis set. The transmission coefficient is derived through three complementary approaches: the…

Mesoscale and Nanoscale Physics · Physics 2025-09-03 Yi-Cheng Lin , Ken-Ming Lin , Yu-Chang Chen

In nuclear fusion and fission, fluctuation and dissipation arise due to the coupling of collective degrees of freedom with internal excitations. Close to the barrier, both quantum, statistical and non-Markovian effects are expected to be…

Nuclear Theory · Physics 2010-04-06 G. Hupin , D. Lacroix