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The phaseless Auxiliary Field Quantum Monte Carlo method provides a well established approximation scheme for accurate calculations of ground state energies of many-fermions systems. Here we apply the method to the calculation of imaginary…

Strongly Correlated Electrons · Physics 2015-06-17 M. Motta , D. E. Galli , S. Moroni , E. Vitali

We present a joint implementation of dynamical-mean-field theory (DMFT) with the pseudopotential plane-wave approach, via Wannier functions, for the determination of the electronic properties of strongly correlated materials. The scheme…

Strongly Correlated Electrons · Physics 2018-08-08 G. Trimarchi , I. Leonov , N. Binggeli , Dm. Korotin , V. I. Anisimov

Heavy quark thermalization in the quark-gluon plasma (QGP) is one of the most promising phenomena for understanding the strong interaction, where their energy loss and momentum broadening at low momentum can be well described by a…

High Energy Physics - Phenomenology · Physics 2024-10-23 Wenyang Qian

Many-body perturbation theory methods, such as the $G_0W_0$ approximation, are able to accurately predict quasiparticle (QP) properties of several classes of materials. However, the calculation of the QP band structure of two-dimensional…

Materials Science · Physics 2022-06-23 Alberto Guandalini , Pino D'Amico , Andrea Ferretti , Daniele Varsano

We study signal processing tasks in which the signal is mapped via some generalized time-frequency transform to a higher dimensional time-frequency space, processed there, and synthesized to an output signal. We show how to approximate such…

Numerical Analysis · Mathematics 2021-09-07 Ron Levie , Haim Avron , Gitta Kutyniok

We report on the most recent applications of the Auxiliary Field Diffusion Monte Carlo (AFDMC) method. The equation of state (EOS) for pure neutron matter in both normal and BCS phase and the superfluid gap in the low--density regime are…

Making and using polaritonic states (i.e., hybrid electron-photon states) for chemical applications have recently become one of the most prominent and active fields that connects the communities of chemistry and quantum optics. Modeling of…

Chemical Physics · Physics 2023-09-06 Braden M. Weight , Sergei Tretiak , Yu Zhang

The quantum Monte Carlo (QMC) is one of the most promising many-body electronic structure approaches. It employs stochastic techniques for solving the stationary Schr\" odinger equation and for evaluation of expectation values. The key…

Other Condensed Matter · Physics 2007-12-20 Michal Bajdich

Nuclear many-body systems, ranging from nuclei to neutron stars, are some of the most interesting physical phenomena in our universe, and Quantum Monte Carlo (QMC) approaches are among the most accurate many-body methods currently available…

Nuclear Theory · Physics 2025-01-03 Ryan Curry , Rahul Somasundaram , Stefano Gandolfi , Alexandros Gezerlis , Ingo Tews

Monte Carlo methods are widely used for approximating complicated, multidimensional integrals for Bayesian inference. Population Monte Carlo (PMC) is an important class of Monte Carlo methods, which utilizes a population of proposals to…

Methodology · Statistics 2022-08-30 Chaofan Huang , V. Roshan Joseph , Simon Mak

Quantum Monte Carlo (QMC) is commonly used in simulations for Quantum Annealing (QA), but QMC as a heuristic approach has great difficulty in that it takes much time to find minimum energy. It mainly depends on the existence of a trotter…

Quantum Physics · Physics 2024-03-13 Kiyotaka Murashima

This work describes methodologies to successfully implement the Implicit Monte Carlo (IMC) scheme for thermal radiative transfer in reduced-precision floating-point arithmetic. The methods used can be broadly categorized into scaling…

Computational Physics · Physics 2025-10-27 Simon Butson , Mathew Cleveland , Alex Long , Todd Palmer

We address the computation of ground-state properties of chemical systems and realistic materials within the auxiliary-field quantum Monte Carlo method. The phase constraint to control the fermion phase problem requires the random walks in…

Strongly Correlated Electrons · Physics 2017-11-28 Mario Motta , Shiwei Zhang

Neural-network quantum states (NQS) offer a versatile and expressive alternative to traditional variational ans\"atze for simulating physical systems. Energy-based frameworks, like Hopfield networks and Restricted Boltzmann Machines,…

Quantum Physics · Physics 2024-12-18 Manas Sajjan , Vinit Singh , Sabre Kais

We describe an algorithm to reduce the cost of auxiliary-field quantum Monte Carlo (AFQMC) calculations for the electronic structure problem. The technique uses a nested low-rank factorization of the electron repulsion integral (ERI). While…

Computational Physics · Physics 2019-07-02 Mario Motta , James Shee , Shiwei Zhang , Garnet Kin-Lic Chan

Sampling from posterior distributions using Markov chain Monte Carlo (MCMC) methods can require an exhaustive number of iterations, particularly when the posterior is multi-modal as the MCMC sampler can become trapped in a local mode for a…

Methodology · Statistics 2019-10-30 Christopher Nemeth , Fredrik Lindsten , Maurizio Filippone , James Hensman

We present an accurate numerical study of the equation of state of nuclear matter based on realistic nucleon--nucleon interactions by means of Auxiliary Field Diffusion Monte Carlo (AFDMC) calculations. The AFDMC method samples the spin and…

Nuclear Theory · Physics 2007-05-23 S. Gandolfi , F. Pederiva , S. Fantoni , K. E. Schmidt

Phonon Monte Carlo (PMC) is a versatile stochasic technique for solving the Boltzmann transport equation for phonons. It is particularly well suited for analyzing thermal transport in structures that have real-space roughness or are too…

Mesoscale and Nanoscale Physics · Physics 2016-02-26 L. N. Maurer , S. Mei , I. Knezevic

The purpose of this text is to give a self-contained description of the basic theory of the projector augmented-wave (PAW) method, as well as most of the details required to make the method work in practice. These two topics are covered in…

Materials Science · Physics 2009-10-13 Carsten Rostgaard

Monte Carlo (MC) and Quasi-Monte Carlo (QMC) methods are classical approaches for the numerical integration of functions $f$ over $[0,1]^d$. While QMC methods can achieve faster convergence rates than MC in moderate dimensions, their…

Numerical Analysis · Mathematics 2025-08-27 Jiaheng Chen , Haotian Jiang , Nathan Kirk
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