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We present a systematic and comprehensive study of finite-size effects in diffusion quantum Monte Carlo calculations of metals. Several previously introduced schemes for correcting finite-size errors are compared for accuracy and efficiency…

Materials Science · Physics 2016-08-23 Sam Azadi , Matthew Foulkes

We present a detailed derivation and numerical tests of a new mixed quantum-classical scheme to deal with non-adiabatic processes. The method is presented as the zero-th order approximation to the exact coupled dynamics of electrons and…

Chemical Physics · Physics 2015-06-22 Federica Agostini , Ali Abedi , E. K. U. Gross

Monte Carlo techniques based on indivisible energy packets are described for computing light curves and spectra for 3-D supernovae. The radiative transfer is time-dependent and includes all effects of O(v/c). Monte Carlo quantization is…

Astrophysics · Physics 2009-11-10 L. B. Lucy

We present unbiased, finite--variance estimators of energy derivatives for real--space diffusion Monte Carlo calculations within the fixed--node approximation. The derivative $d_\lambda E$ is fully consistent with the dependence…

Materials Science · Physics 2021-05-20 Jesse van Rhijn , Claudia Filippi , Stefania De Palo , Saverio Moroni

Diffusion Monte Carlo (DMC) calculations are performed on the monocyclic and bicyclic forms of m-benzyne, which are the equilibrium structures at the CCSD(T) and CCSD levels of coupled cluster theory. We employed multi-configuration…

Chemical Physics · Physics 2009-11-13 W. A. Al-Saidi , C. J. Umrigar

All-electron variational and diffusion quantum Monte Carlo calculations of the ground state energies of the first row atoms (Li to Ne) are reported. We use trial wavefunctions of four types: single determinant Slater-Jastrow wavefunctions;…

Materials Science · Physics 2010-11-22 Matthew Brown , John Robert Trail , Pablo Lopez Rios , Richard Needs

This paper develops and analyzes an efficient numerical method for solving elliptic partial differential equations, where the diffusion coefficients are random perturbations of deterministic diffusion coefficients. The method is based upon…

Numerical Analysis · Mathematics 2016-03-30 X. Feng , J. Lin. , C. Lorton

We explore the use in quantum Monte Carlo (QMC) of trial wave functions consisting of a Jastrow factor multiplied by a truncated configuration-interaction (CI) expansion in Slater determinants obtained from a CI perturbatively selected…

Chemical Physics · Physics 2016-01-25 Emmanuel Giner , Roland Assaraf , Julien Toulouse

The construction of trial wave functions based on neural networks combined with the variational Monte Carlo method is discussed. The mathematical formulation for representing quantum states as artificial neural networks is introduced. The…

Computational Physics · Physics 2026-05-19 William Freitas

We present a numerically exact steady-state inchworm Monte Carlo method for nonequilibrium quantum impurity models. Rather than propagating an initial state to long times, the method is directly formulated in the steady-state. This…

Strongly Correlated Electrons · Physics 2023-05-17 André Erpenbeck , Emanuel Gull , Guy Cohen

The Dynamic Monte Carlo (DMC) method is an established molecular simulation technique for the analysis of the dynamics in colloidal suspensions. An excellent alternative to Brownian Dynamics or Molecular Dynamics simulation, DMC is…

Soft Condensed Matter · Physics 2020-07-15 Fabián A. García Daza , Alejandro Cuetos , Alessandro Patti

The quantum Monte Carlo algorithm is arguably one of the most powerful computational many-body methods, enabling accurate calculation of many properties in interacting quantum systems. In the presence of the so-called sign problem, the…

Strongly Correlated Electrons · Physics 2018-02-23 Chia-Chen Chang , Miguel A. Morales

Experiments using intermediate- to high-energy radioactive nuclear beams present numerous findings. Extracting important properties of physical observables relies on a firm theoretical analysis. Though Glauber theory is believed to work…

Nuclear Theory · Physics 2026-04-23 W. Horiuchi , Y. Suzuki , R. B. Wiringa

We propose a new Monte Carlo scheme to study the late-time dynamics of a 2-dim hard sphere fluid, modeled by a tethered network of hard spheres. Fluidity is simulated by breaking and reattaching the flexible tethers. We study the diffusion…

Condensed Matter · Physics 2007-05-23 P. B. Sunil Kumar , Madan Rao

Diffusion Monte Carlo (DMC) simulations for fermions are becoming the standard to provide high quality reference data in systems that are too large to be investigated via quantum chemical approaches. DMC with the fixed-node approximation…

Chemical Physics · Physics 2016-07-06 Andrea Zen , Sandro Sorella , Michael J. Gillan , Angelos Michaelides , Dario Alfè

The diffusion Monte Carlo (DMC), auxiliary field quantum Monte Carlo (AFQMC), and equation-of-motion coupled cluster (EOM-CC) methods are used to calculate the electron binding energy (EBE) of the non-valence anion state of a model…

Chemical Physics · Physics 2021-02-03 Shiv Upadhyay , Amanda Dumi , James Shee , Kenneth D. Jordan

Incorporating nuclear quantum effects into nonadiabatic dynamics remains a significant challenge. Herein we introduce new nonadiabatic dynamics approaches based on the recently developed constrained nuclear-electronic orbital (CNEO) theory.…

Chemical Physics · Physics 2025-04-15 Zhe Liu , Zehua Chen , Yang Yang

The correlation energy of the homogeneous three-dimensional interacting electron gas is calculated using the variational and fixed-node diffusion Monte Carlo methods, with trial functions that include backflow and three-body correlations.…

Strongly Correlated Electrons · Physics 2009-10-31 Yongkyung Kwon , D. M. Ceperley , Richard M. Martin

We introduce a powerful Monte Carlo (MC) algorithm for the atomistic simulation of bulk models of oligo- and poly-thiophenes by redesigning MC moves originally developed for considerably simpler polymer structures and architectures, such as…

Soft Condensed Matter · Physics 2019-03-06 Flora D. Tsourtou , Stavros D. Peroukidis , Loukas D. Peristeras , Vlasis G. Mavrantzas

Monte Carlo simulations of diffusion processes often introduce bias in the final result, due to time discretization. Using an auxiliary Poisson process, it is possible to run simulations which are unbiased. In this article, we propose such…

Computational Finance · Quantitative Finance 2016-05-09 Louis Paulot