English
Related papers

Related papers: Fixed and partial-node approximations in Slater de…

200 papers

In this paper, we develop a numerical scheme for the space-time fractional parabolic equation, i.e., an equation involving a fractional time derivative and a fractional spatial operator. Both the initial value problem and the…

Numerical Analysis · Mathematics 2017-08-18 Andrea Bonito , Wenyu Lei , Joseph E. Pasciak

Optimal exploitation of supercomputing resources for the evaluation of electrostatic forces remains a challenge in molecular dynamics simulations of very large systems. The most efficient methods are currently based on particle-mesh Ewald…

Computational Physics · Physics 2025-09-23 Federica Troni , Davide Grassano , Jayashree Narayan , Benoît Roux , Sara Bonella

Slater determinants built from the single-particle wave functions of the analytically solvable Ginocchio potential are used to approximate the self-consistent Hartree-Fock solutions for the ground states of nuclei. The results indicate that…

Nuclear Theory · Physics 2011-05-12 M. V. Stoitsov , S. S. Dimitrova , S. Pittel , P. Van Isacker , A. Frank

We formulate and characterize a new constraint for Auxiliary Field Quantum Monte Carlo (AFQMC) applicable for general fermionic systems, which allows for the accumulation of phase in the random walk but disallows walkers with a magnitude of…

Chemical Physics · Physics 2023-06-16 John L. Weber , Hung Vuong , Richard A. Friesner , David R. Reichman

Quantum Monte Carlo (QMC) methods represent a powerful family of computational techniques for tackling complex quantum many-body problems and performing calculations of stationary state properties. QMC is among the most accurate and…

Materials Science · Physics 2025-01-08 Alfonso Annarelli , Dario Alfè , Andrea Zen

Using the homogeneous electron gas (HEG) as a model, we investigate the sources of error in the `initiator' adaptation to Full Configuration Interaction Quantum Monte Carlo (i-FCIQMC), with a view to accelerating convergence. In particular…

Computational Physics · Physics 2012-06-26 James J. Shepherd , George H. Booth , Ali Alavi

We present a scalable approach to performing approximate fully Bayesian inference in generic state space models. The proposed method is an alternative to particle MCMC that provides fully Bayesian inference of both the dynamic latent states…

Machine Learning · Statistics 2019-02-13 Marcel Hirt , Petros Dellaportas

Sequential Monte Carlo (SMC), or particle filtering, is a popular class of methods for sampling from an intractable target distribution using a sequence of simpler intermediate distributions. Like other importance sampling-based methods,…

Machine Learning · Computer Science 2015-11-18 Shixiang Gu , Zoubin Ghahramani , Richard E. Turner

In this work we investigate replacing standard quadrature techniques used in deterministic linear solvers with a fixed-seed Quasi-Monte Carlo calculation to obtain more accurate and efficient solutions to the neutron transport equation…

Computational Physics · Physics 2022-09-07 Sam Pasmann , Ilham Variansyah , C. T. Kelley , Ryan McClarren

Quantum-selected configuration interaction (QSCI) is an approach for quantum chemical calculations using current quantum computers. In conventional QSCI, Slater determinants used for the wave function expansion are sampled by iteratively…

Quantum Physics · Physics 2025-10-03 Kenji Sugisaki , Shu Kanno , Toshinari Itoko , Rei Sakuma , Naoki Yamamoto

We study lithium systems over a range of number of atoms, e.g., atomic anion, dimer, metallic cluster, and body-centered cubic crystal by the diffusion Monte Carlo method. The calculations include both core and valence electrons in order to…

Computational Physics · Physics 2015-07-29 Kevin Rasch , Lubos Mitas

This paper is devoted to studying the global and finite convergence of the semi-smooth Newton method for solving a piecewise linear system that arises in cone-constrained quadratic programming problems and absolute value equations. We first…

Optimization and Control · Mathematics 2023-01-24 Nicolas F. Armijo , Yunier Bello-Cruz , Gabriel Haeser

In this article we consider Bayesian parameter inference associated to partially-observed stochastic processes that start from a set B0 and are stopped or killed at the first hitting time of a known set A. Such processes occur naturally…

Computation · Statistics 2012-01-19 Ajay Jasra , Nikolas Kantas

This project investigates the applicability of quasi-Monte Carlo methods to Euclidean lattice systems in order to improve the asymptotic error scaling of observables for such theories. The error of an observable calculated by averaging over…

High Energy Physics - Lattice · Physics 2013-11-20 Andreas Ammon , Tobias Hartung , Karl Jansen , Hernan Leovey , Andreas Griewank , Micheal Müller-Preussker

In the last decade, sequential Monte-Carlo methods (SMC) emerged as a key tool in computational statistics. These algorithms approximate a sequence of distributions by a sequence of weighted empirical measures associated to a weighted…

Statistics Theory · Mathematics 2007-06-13 R. Douc , France E. Moulines

In this work, we develop a unified framework for quasidiagonal and F\o lner-type approximations of linear operators on Hilbert spaces. These approximations (originally formulated for bounded operators and operator algebras) involve…

Functional Analysis · Mathematics 2025-09-04 Eva A. Gallardo-Gutiérrez , Fernando Lledó , Laura Sáenz

We report a scalable Fortran implementation of the phaseless auxiliary-field quantum Monte Carlo (ph-AFQMC) and demonstrate its excellent performance and beneficial scaling with respect to system size. Furthermore, we investigate…

Chemical Physics · Physics 2024-02-09 Z. Sukurma , M. Schlipf , M. Humer , A. Taheridehkordi , G. Kresse

The sign problem in Full Configuration Interaction Quantum Monte Carlo (FCIQMC) without annihilation can be understood as an instability of the psi-particle population to the ground state of the matrix obtained by making all off-diagonal…

Computational Physics · Physics 2013-01-14 Michael H. Kolodrubetz , James S. Spencer , Bryan K. Clark , W. Matthew C. Foulkes

We propose the use of preconditioning in FCIQMC which, in combination with perturbative estimators, greatly increases the efficiency of the algorithm. The use of preconditioning allows a time step close to unity to be used (without…

Chemical Physics · Physics 2019-05-17 Nick S. Blunt , Alex J. W. Thom , Charles J. C. Scott