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We use an auxiliary-field Monte Carlo (AFMC) method to calculate thermodynamic properties (spin susceptibility and heat capacity) of ultra-small metallic grains in the presence of pairing correlations. This method allows us to study the…

Mesoscale and Nanoscale Physics · Physics 2007-05-23 Y. Alhassid , L. Fang , S. Schmidt

In this article, a numerical analysis of the projector augmented-wave (PAW) method is presented, restricted to the case of dimension one with Dirac potentials modeling the nuclei in a periodic setting. The PAW method is widely used in…

Numerical Analysis · Mathematics 2023-01-02 Mi-Song Dupuy

Hybrid light-matter polaritonic states have shown great promise for altering already known and enabling novel chemical reactions and controlling photophysical phenomena. This field has recently become one of the most prominent and active…

Quantum Physics · Physics 2025-05-23 Braden M. Weight , Yu Zhang

We describe a new open-source Python-based package for high accuracy correlated electron calculations using quantum Monte Carlo (QMC) in real space: PyQMC. PyQMC implements modern versions of QMC algorithms in an accessible format, enabling…

We investigate the use of optimized correlation consistent gaussian basis sets for the study of insulating solids with auxiliary-field quantum Monte Carlo (AFQMC). The exponents of the basis set are optimized through the minimization of the…

Chemical Physics · Physics 2021-02-03 Miguel A. Morales , Fionn D. Malone

We develop an all-electron quantum Monte Carlo (QMC) method for solids that does not rely on pseudopotentials, and use it to construct a primary ultra-high pressure calibration based the equation of state of cubic boron nitride(c-BN). We…

Materials Science · Physics 2015-05-14 K. P. Esler , R. E. Cohen , B. Militzer , Jeongnim Kim , R. J. Needs , M. D. Towler

Phaseless auxiliary-field quantum Monte Carlo (AFQMC) has in several cases been found to perform well on strongly correlated systems. Here, we benchmark the method for three iron-sulfur clusters ([2Fe-2S], [4Fe-4S], and the FeMo cofactor)…

Chemical Physics · Physics 2026-05-06 Eirik F. Kjønstad , Huanchen Zhai , James Shee , Sandeep Sharma , Garnet Kin-Lic Chan

In this study, we propose quantum annealing-enhanced Markov Chain Monte Carlo (QAEMCMC), where QA is integrated into the MCMC subroutine. QA efficiently explores low-energy configurations and overcomes local minima, enabling the generation…

Quantum Physics · Physics 2025-02-13 Shunta Arai , Tadashi Kadowaki

We apply diffusion quantum Monte Carlo (DMC) to a broad set of solids, benchmarking the method by comparing bulk structural properties (equilibrium volume and bulk modulus) to experiment and DFT based theories. The test set includes…

Materials Science · Physics 2015-06-17 Luke Shulenburger , Thomas R. Mattsson

In this thesis, I discuss the use of the Auxiliary Field Diffusion Monte Carlo method to compute the ground state of nuclear Hamiltonians, and I show several applications to interesting problems both in nuclear physics and in nuclear…

Nuclear Theory · Physics 2007-12-11 Stefano Gandolfi

We investigate the two-dimensional cooperon-fermion model in the correlated regime with a new continuous-time diagrammatic determinant quantum Monte Carlo (DDQMC) algorithm. We estimate the transition temperature $T_{c}$, examine the…

Superconductivity · Physics 2015-03-19 Kai-Yu Yang , E. Kozik , Xin Wang , M. Troyer

The Fokker-Planck (FP) particle method accelerates rarefied-gas simulations by replacing the binary collisions of the commonly used Direct Simulation Monte Carlo (DSMC) method with a drift=diffusion process. Like all particle methods, the…

Numerical Analysis · Mathematics 2026-01-22 Lukas Netterdon , Veronica Montanaro , Manuel Torrilhon , Hossein Gorji

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

A new pseudopotential generation method is presented which significantly improves transferability. The method exploits the flexibility contained in the separable Kleinman-Bylander form of the nonlocal pseudopotential [Phys. Rev. Lett. 48,…

Condensed Matter · Physics 2007-05-23 Nicholas J. Ramer , Andrew M. Rappe

We present a reduced-scaling auxiliary-field quantum Monte Carlo (AFQMC) framework designed for large molecular systems and ensembles, with or without coupling to optical cavities. Our approach leverages the natural block sparsity of…

Chemical Physics · Physics 2026-02-03 Yu Zhang

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

Due to their diverse nature, the faithful description of excited states within electronic structure theory methods remains one of the grand challenges of modern theoretical chemistry. Quantum Monte Carlo (QMC) methods have been applied very…

Chemical Physics · Physics 2020-06-05 Anthony Scemama , Michel Caffarel , Anouar Benali , Denis Jacquemin , Pierre-François Loos

We present an accurate numerical study of the equation of state of nuclear matter based on realistic nucleon--nucleon interactions by means of Auxiliary Field Diffusion Monte Carlo (AFDMC) calculations. The AFDMC method samples the spin and…

Nuclear Theory · Physics 2008-11-26 Stefano Gandolfi , Francesco Pederiva , Stefano Fantoni , Kevin E. Schmidt

Quantum Monte Carlo (QMC) is applied to obtain the fundamental (quasiparticle) electronic band gap, $\Delta_f$, of a semiconducting two-dimensional (2D) phosphorene whose optical and electronic properties fill the void between graphene and…

Mesoscale and Nanoscale Physics · Physics 2019-02-06 Tobias Frank , Rene Derian , Kamil Tokar , Lubos Mitas , Jaroslav Fabian , Ivan Stich

We introduce a semistochastic implementation of the power method to compute, for very large matrices, the dominant eigenvalue and expectation values involving the corresponding eigenvector. The method is semistochastic in that the matrix…

Strongly Correlated Electrons · Physics 2013-10-24 F. R. Petruzielo , A. A. Holmes , Hitesh J. Changlani , M. P. Nightingale , C. J. Umrigar
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