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Hamiltonian Monte Carlo (HMC) has become routinely used for sampling from posterior distributions. Its extension Riemann manifold HMC (RMHMC) modifies the proposal kernel through distortion of local distances by a Riemannian metric. The…

Computation · Statistics 2017-02-21 Akihiko Nishimura , David Dunson

The energy variance optimization algorithm over a fixed ensemble of configurations in variational Monte Carlo is formally identical to a problem of fitting data: we reexamine it from a statistical maximum-likelihood point of view. We detect…

Atomic and Molecular Clusters · Physics 2009-11-07 Dario Bressanini , Gabriele Morosi , Massimo Mella

A second-order many-body perturbation correction to the relativistic Dirac-Hartree-Fock energy is evaluated stochastically by integrating 13-dimensional products of four-component spinors and Coulomb potentials. The integration in the real…

Quantum Physics · Physics 2022-06-16 J. César Cruz , Jorge Garza , Takeshi Yanai , So Hirata

In this work, the phase function method (PFM) is employed for the first time to explicitly construct scattering wavefunctions for the $\alpha\alpha$ system using a single-term Morse potential. Unlike earlier PFM-based studies that primarily…

Nuclear Theory · Physics 2026-02-24 Anil Khachi , Shikha Awasthi , Tarachand Verma , Ranjana Joshi

Ab-initio quantum Monte Carlo (QMC) methods are a state-of-the-art computational approach to obtaining highly accurate many-body wave functions. Although QMC methods are widely used in physics and chemistry to compute ground-state energies,…

Chemical Physics · Physics 2022-01-21 Kousuke Nakano , Abhishek Raghav , Sandro Sorella

We present an extension of constrained-path auxiliary-field quantum Monte Carlo (CP-AFQMC) for the treatment of correlated electronic systems coupled to phonons. The algorithm follows the standard CP-AFQMC approach for description of the…

Strongly Correlated Electrons · Physics 2021-03-24 Joonho Lee , Shiwei Zhang , David R. Reichman

We give a brief discussion of the recently developed Constrained-Path Monte Carlo Method. This method is a quantum Monte Carlo technique that eliminates the fermion sign problem plaguing simulations of systems of interacting electrons. The…

Strongly Correlated Electrons · Physics 2009-10-31 J. E. Gubernatis , M. Guerrero

We derive and implement symmetry-projected Hartree-Fock-Bogoliubov (HFB) equations and apply them to the molecular electronic structure problem. All symmetries (particle number, spin, spatial, and complex conjugation) are deliberately…

Strongly Correlated Electrons · Physics 2012-02-15 Gustavo E. Scuseria , Carlos A. Jimenez-Hoyos , Thomas M. Henderson , Kousik Samanta , Jason K. Ellis

Quantum mechanics for many-body systems may be reduced to the evaluation of integrals in 3N dimensions using Monte-Carlo, providing the Quantum Monte Carlo ab initio methods. Here we limit ourselves to expectation values for trial…

Computational Physics · Physics 2010-11-22 John Robert Trail , Ryo Maezono

We present a new form of explicitly correlated wave function whose parameters are mainly linear, to circumvent the problem of the optimization of a large number of non-linear parameters usually encountered with basis sets of explicitly…

Atomic Physics · Physics 2009-11-06 Luca Bertini , Dario Bressanini , Massimo Mella , Gabriele Morosi

It has become increasingly important to include one or more individual flavours of dynamical fermion in lattice QCD simulations. This is due in part to the advent of QCD+QED calculations, where isospin symmetry breaking means that the up,…

High Energy Physics - Lattice · Physics 2019-03-27 Taylor Haar , Waseem Kamleh , James Zanotti , Yoshifumi Nakamura

In this work, we test a recently developed method to enhance classical auxiliary-field quantum Monte Carlo (AFQMC) calculations with quantum computers against examples from chemistry and material science, representatives of classes of…

Quantum computers have a potential for solving quantum chemistry problems with higher accuracy than classical computers. Quantum computing quantum Monte Carlo (QC-QMC) is a QMC with a trial state prepared in quantum circuit, which is…

Quantum Physics · Physics 2024-06-07 Shu Kanno , Hajime Nakamura , Takao Kobayashi , Shigeki Gocho , Miho Hatanaka , Naoki Yamamoto , Qi Gao

Quasi-Monte Carlo (QMC) methods are being adopted in statistical applications due to the increasingly challenging nature of numerical integrals that are now routinely encountered. For integrands with $d$-dimensions and derivatives of order…

Computation · Statistics 2016-04-04 Chris. J. Oates , Mark Girolami

Hamiltonian Monte Carlo (HMC) algorithms which combine numerical approximation of Hamiltonian dynamics on finite intervals with stochastic refreshment and Metropolis correction are popular sampling schemes, but it is known that they may…

Computation · Statistics 2022-08-16 Peter A. Whalley , Daniel Paulin , Benedict Leimkuhler

In this work, we propose a Model Predictive Control (MPC) formulation incorporating two distinct horizons: a prediction horizon and a constraint horizon. This approach enables a deeper understanding of how constraints influence key system…

Systems and Control · Electrical Eng. & Systems 2025-03-25 Allan Andre Do Nascimento , Han Wang , Antonis Papachristodoulou , Kostas Margellos

A paramount goal in the field of nuclear physics is to unify ab-initio treatments of bound and unbound states. The position-space quantum Monte Carlo (QMC) methods have a long history of successful bound state calculations in light systems…

Nuclear Theory · Physics 2023-08-29 Abraham R. Flores , Kenneth M. Nollett

Hamiltonian Monte Carlo (HMC) is a popular method in sampling. While there are quite a few works of studying this method on various aspects, an interesting question is how to choose its integration time to achieve acceleration. In this…

Machine Learning · Computer Science 2023-02-16 Jun-Kun Wang , Andre Wibisono

We propose an accurate variational Monte Carlo method applicable in the presence of the strong spin-orbit interaction. Our variational wave functions consist of generalized Pfaffian-Slater wave functions that involve mixtures of singlet and…

Strongly Correlated Electrons · Physics 2015-11-10 Moyuru Kurita , Youhei Yamaji , Satoshi Morita , Masatoshi Imada

Despite more than 40 years of research in condensed-matter physics, state-of-the-art approaches for simulating the radial distribution function (RDF) g(r) still rely on binning pair-separations into a histogram. Such methods suffer from…

Materials Science · Physics 2016-09-05 Thomas W. Rosch , Paul N. Patrone