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Quasi-Monte Carlo (QMC) methods for estimating integrals are attractive since the resulting estimators typically converge at a faster rate than pseudo-random Monte Carlo. However, they can be difficult to set up on arbitrary posterior…

Statistics Theory · Mathematics 2018-10-03 Tobias Schwedes , Ben Calderhead

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

The Quantum Monte Carlo method for spin 1/2 fermions at finite temperature is formulated for dilute systems with an s-wave interaction. The motivation and the formalism are discussed along with descriptions of the algorithm and various…

Statistical Mechanics · Physics 2009-02-05 Aurel Bulgac , Joaquin E. Drut , Piotr Magierski

The Kinetic Monte Carlo (KMC) method has become an important tool for examination of phenomena like surface diffusion and thin film growth because of its ability to carry out simulations for time scales that are relevant to experiments. But…

Materials Science · Physics 2007-05-23 Talat S. Rahman , Abdelkader Kara , Altaf Karim , Oleg Trushin

Dynamical mean-field theory (DMFT) is one of the most widely used theoretical methods for electronic structure calculations, providing self-consistent solutions even in low-temperature regimes, which are exact in the limit of infinite…

Strongly Correlated Electrons · Physics 2023-09-06 Johan Carlström

Finite temperature auxiliary field-based Quantum Monte Carlo methods, including Determinant Quantum Monte Carlo (DQMC) and Auxiliary Field Quantum Monte Carlo (AFQMC), have historically assumed pivotal roles in the investigation of the…

Quantum Physics · Physics 2021-02-03 Tong Shen , Yuan Liu , Yang Yu , Brenda Rubenstein

We present a realistic study for electronic and magnetic properties in dilute magnetic semiconductor (Ga,Mn)As. A multi-orbital Haldane-Anderson model parameterized by density-functional calculations is presented and solved with the…

We introduce a Quantum Monte Carlo (QMC) method which efficiently simulates in a sign-problem-free way a broad class of frustrated $S=1/2$ models with competing antiferromagnetic interactions. Our scheme uses the basis of total spin…

Strongly Correlated Electrons · Physics 2016-11-09 Fabien Alet , Kedar Damle , Sumiran Pujari

In plasma edge simulations, the behavior of neutral particles is often described by a Boltzmann--BGK equation. Solving this kinetic equation and estimating the moments of its solution are essential tasks, typically carried out using Monte…

Numerical Analysis · Mathematics 2025-12-30 Zhirui Tang , Julian Koellermeier , Emil Løvbak , Giovanni Samaey

Simulations of extended quantum systems are typically performed by extrapolating results of a sequence of finite-system-size simulations to the thermodynamic limit. In the quantum Monte Carlo community, twist-averaging was pioneered as an…

Strongly Correlated Electrons · Physics 2022-12-14 Sergei Iskakov , Hanna Terletska , Emanuel Gull

The LDA+DMFT approach merges conventional band structure theory in the local density approximation (LDA) with a state-of-the-art many-body technique, the dynamical mean-field theory (DMFT). This new computational scheme has recently become…

Strongly Correlated Electrons · Physics 2009-10-31 K. Held , I. A. Nekrasov , N. Blümer , V. I. Anisimov , D. Vollhardt

We present a new method for extracting numerically exact imaginary-time Green functions from standard Hirsch-Fye quantum Monte Carlo (HF-QMC) simulations within dynamical mean-field theory. By analytic continuation, angular resolved spectra…

Strongly Correlated Electrons · Physics 2007-12-11 N. Blümer

Density matrix quantum Monte Carlo (DMQMC) is a recently-developed method for stochastically sampling the $N$-particle thermal density matrix to obtain exact-on-average energies for model and \emph{ab initio} systems. We report a systematic…

We explore the application of the quasi-Monte Carlo (QMC) method in deep backward dynamic programming (DBDP) (Hure et al. 2020) for numerically solving high-dimensional nonlinear partial differential equations (PDEs). Our study focuses on…

Numerical Analysis · Mathematics 2024-07-23 Du Ouyang , Jichang Xiao , Xiaoqun Wang

Quantum-mechanical methods are widely used for understanding molecular interactions throughout biology, chemistry, and materials science. Quantum diffusion Monte Carlo (DMC) and coupled cluster with single, double, and perturbative triple…

We provide a pedagogical introduction to the two main variants of real-space quantum Monte Carlo methods for electronic-structure calculations: variational Monte Carlo (VMC) and diffusion Monte Carlo (DMC). Assuming no prior knowledge on…

Chemical Physics · Physics 2015-08-13 Julien Toulouse , Roland Assaraf , C. J. Umrigar

The nearest-neighbor quantum-antiferromagnetic (AF) Heisenberg model for spin 1/2 on a two-dimensional square lattice is studied in the auxiliary-fermion representation. Expressing spin operators by canonical fermionic particles requires a…

Strongly Correlated Electrons · Physics 2009-11-10 Jan Brinckmann , Peter Woelfle

This paper introduces a novel ansatz-based technique for solution of the Hubbard model over two length scales. Short range correlations are treated exactly using a dynamical cluster approximation QMC simulation, while longer-length-scale…

Strongly Correlated Electrons · Physics 2009-11-10 J. P. Hague , Mark Jarrell , T. C. Schulthess

The small magnitude and long-range character of non-covalent interactions pose a significant challenge for computational quantum chemical and electronic-structure methods alike. State-of-the-art coupled cluster (CC) theory and…

Chemical Physics · Physics 2026-01-22 S. Lambie , P. López-Ríos , D. Kats , Ali Alavi

We study the application of a tailored quasi-Monte Carlo (QMC) method to a class of optimal control problems subject to parabolic partial differential equation (PDE) constraints under uncertainty: the state in our setting is the solution of…

Numerical Analysis · Mathematics 2024-03-28 Philipp A. Guth , Vesa Kaarnioja , Frances Y. Kuo , Claudia Schillings , Ian H. Sloan