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We examine Gaussian-basis Monte Carlo method (GBMC) introduced by Corney and Drummond. This method is based on an expansion of the density-matrix operator rho by means of the coherent Gaussian-type operator basis Lambda and does not suffer…

Strongly Correlated Electrons · Physics 2007-08-29 Takeshi Aimi , Masatoshi Imada

A novel sign-free Monte Carlo method for the Hubbard model has recently been proposed by Corney and Drummond. High precision measurements on small clusters show that ground state correlation functions are not correctly reproduced. We argue…

Strongly Correlated Electrons · Physics 2009-11-11 F. F. Assaad , P. Werner , P. Corboz , E. Gull , M. Troyer

For important classes of many-fermion problems, quantum Monte Carlo (QMC) methods allow exact calculations of ground-state and finite-temperature properties, without the sign problem. The list spans condensed matter, nuclear physics, and…

Computational Physics · Physics 2016-03-23 Hao Shi , Shiwei Zhang

Using quantum Monte Carlo (QMC) simulations we study the ground-state properties of the one-dimensional fermionic Hubbard model in traps with an underlying lattice. Since due to the confining potential the density is space dependent,…

Strongly Correlated Electrons · Physics 2007-05-23 Marcos Rigol , Alejandro Muramatsu

We benchmark constrained-path Monte Carlo (CPMC) on the triangular-lattice Hubbard model for several fillings and $U$ values and show that symmetry-adapted trial wave functions are essential for quantitative accuracy. Away from…

Strongly Correlated Electrons · Physics 2026-03-17 Shu Fay Ung , Ankit Mahajan , David R. Reichman

We formulate a quantum Monte Carlo (QMC) method for calculating the ground state of many-boson systems. The method is based on a field-theoretical approach, and is closely related to existing fermion auxiliary-field QMC methods which are…

Computational Physics · Physics 2009-11-10 Wirawan Purwanto , Shiwei Zhang

A unique feature of the hybrid quantum Monte Carlo (HQMC) method is the potential to simulate negative sign free lattice fermion models with subcubic scaling in system size. Here we will revisit the algorithm for various models. We will…

Strongly Correlated Electrons · Physics 2018-03-09 Stefan Beyl , Florian Goth , Fakher F. Assaad

The study of ground-state properties of the Fermi-Hubbard model is a long-lasting task in the research of strongly correlated systems. Owing to the exponentially growing complexity of the system, a quantitative analysis usually demands high…

Strongly Correlated Electrons · Physics 2023-08-15 Yue-Ran Shi , Yuan-Yao He , Ruijin Liu , Wei Zhang

We revisit the accuracy of the variational Monte Carlo (VMC) method by taking an example of ground state properties for the one-dimensional Hubbard model. We start from the variational wave functions with the Gutzwiller and long-range…

Strongly Correlated Electrons · Physics 2013-08-13 Ryui Kaneko , Satoshi Morita , Masatoshi Imada

We show how symmetry properties can be used to greatly increase the accuracy and efficiency in auxiliary-field quantum Monte Carlo (AFQMC) calculations of electronic systems. With the Hubbard model as an example, we study symmetry…

Strongly Correlated Electrons · Physics 2014-04-01 Hao Shi , Shiwei Zhang

We present clear numerical evidence for the coexistence of metallic and insulating dynamical mean field theory(DMFT) solutions in a half-filled single-band Hubbard model with bare semicircular density of states at finite temperatures.…

Strongly Correlated Electrons · Physics 2009-10-31 Jaewook Joo , Viktor Oudovenko

We propose a new quantum Monte Carlo algorithm to compute fermion ground-state properties. The ground state is projected from an initial wavefunction by a branching random walk in an over-complete basis space of Slater determinants. By…

Condensed Matter · Physics 2016-08-31 Shiwei Zhang , J. Carlson , J. E. Gubernatis

Determinant Quantum Monte Carlo (DQMC) provides numerically exact solutions for strongly correlated fermionic systems but faces significant computational challenges with increasing system size. While submatrix updates were originally…

Strongly Correlated Electrons · Physics 2025-02-19 Fanjie Sun , Xiao Yan Xu

Monte Carlo simulations are a powerful tool to investigate the thermodynamic properties of atomic systems. In practice however, sampling of the complete configuration space is often hindered by high energy barriers between different regions…

Statistical Mechanics · Physics 2020-05-04 Jonas A. Finkler , Stefan Goedecker

Building on recent solutions of the fermion sign problem for specific models we present two continuous-time quantum Monte Carlo methods for efficient simulation of mass-imbalanced Hubbard models on bipartite lattices at half-filling. For…

Strongly Correlated Electrons · Physics 2015-12-18 Ye-Hua Liu , Lei Wang

Gaussian random fields play an important role in many areas of science and engineering. In practice, they are often simulated by sampling from a high-dimensional multivariate normal distribution, which arises from the discretisation of a…

Numerical Analysis · Mathematics 2026-02-12 Yoshihito Kazashi , Eike H. Müller , Robert Scheichl

Quantum Monte Carlo (QMC) methods can very accurately compute ground state properties of quantum systems. We applied these methods to a system of boson hard spheres to get exact, infinite system size results for the ground state at several…

Computational Physics · Physics 2016-09-08 Mark Dewing

We present in detail the recently developed multi-configurational symmetrized projector quantum Monte Carlo (MSPQMC) method for excited states of the Hubbard model. We describe the implementation of the Monte Carlo method for a…

Condensed Matter · Physics 2009-10-28 Bhargavi Srinivasan , S. Ramasesha , H. R. Krishnamurthy

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

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…

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