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Computer simulation plays a central role in modern day materials science. The utility of a given computational approach depends largely on the balance it provides between accuracy and computational cost. Molecular crystals are a class of…

We present a nonlinear (in the sense of McKean) generalization of Hamiltonian Monte Carlo (HMC) termed nonlinear HMC (nHMC) capable of sampling from nonlinear probability measures of mean-field type. When the underlying confinement…

Probability · Mathematics 2023-09-22 Nawaf Bou-Rabee , Katharina Schuh

Quantum Monte Carlo methods are powerful tools for studying quantum many-body systems but face difficulties in accessing excited states and in treating sign problems. We present a continuous-time path-integral Monte Carlo method for…

Strongly Correlated Electrons · Physics 2025-12-16 Abhishek Karna , Hansen S. Wu , Shailesh Chandrasekharan , Ribhu K. Kaul

We develop ultratransferable pseudopotentials for the contact interaction that are 100 times more accurate than contemporary approximations. The pseudopotential offers scattering properties very similar to the contact potential, has a…

Quantum Gases · Physics 2014-03-04 Pascal O. Bugnion , Richard J. Needs , Gareth J. Conduit

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 demonstrate numerically the diffraction-free propagation of sub-wavelength sized optical beams through simple elements built of metal-dielectric multilayers. The proposed metamaterial consists of silver and a high refractive index…

Optics · Physics 2011-06-07 R. Kotynski , T. Stefaniuk , A. Pastuszczak

Density functional theory has been an essential analysis tool for both theoretical and experimental chemists since accurate hybrid functionals were developed. Here we propose a local hybrid method derived from the optimized effective…

Chemical Physics · Physics 2017-03-24 Jaewook Kim , Kwangwoo Hong , Sang-Yeon Hwang , Seongok Ryu , Sunghwan Choi , Woo Youn Kim

A density functional theory (DFT) approach to computing transition metal oxide heat of formation without adjustable parameters is presented. Different degrees of $d$-electron localization in oxides are treated within the DFT+$U$ approach…

Materials Science · Physics 2022-04-01 Johannes Voss

We review the use of the path integral Monte Carlo (PIMC) methodology to the study of finite-size quantum clusters, with particular emphasis on recent applications to pure and impurity-doped He clusters. We describe the principles of PIMC,…

Chemical Physics · Physics 2016-11-23 Patrick Huang , Yongkyung Kwon , K. Birgitta Whaley

We consider Metropolis Hastings MCMC in cases where the log of the ratio of target distributions is replaced by an estimator. The estimator is based on m samples from an independent online Monte Carlo simulation. Under some conditions on…

Computation · Statistics 2012-06-01 Geoff K. Nicholls , Colin Fox , Alexis Muir Watt

Here, we report a numerical implementation of the nonlocal homogenization approach recently proposed in [M. Silveirinha, Phys. Rev. B 75, 115104 (2007)], using the finite difference frequency-domain method to discretize the…

Materials Science · Physics 2015-05-13 Joao T. Costa , Mario G. Silveirinha , Stanislav I. Maslovski

The Hamiltonian Monte Carlo method generates samples by introducing a mechanical system that explores the target density. For distributions on manifolds it is not always simple to perform the mechanics as a result of the lack of global…

Computation · Statistics 2019-04-22 Alessandro Barp , Anthony Kennedy , Mark Girolami

Semiconductor artificial graphene nanostructures where Hubbard model parameter $U/t$ can be of the order of 100, provide a highly controllable platform to study strongly correlated quantum many-particle phases. We use accurate variational…

Mesoscale and Nanoscale Physics · Physics 2023-11-01 Gökhan Öztarhan , E. Bulut Kul , Emre Okcu , A. D. Güçlü

Electronic correlations beyond static mean-field theories are of fundamental importance in describing the properties of complex materials - such as transition-metal oxides - where the low-energy physics is driven by localized d or f…

Strongly Correlated Electrons · Physics 2025-03-17 Mario Caserta , Tommaso Chiarotti , Marco Vanzini , Nicola Marzari

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

The number of low-energy constants (LECs) in chiral effective field theory ($\chi$EFT) grows rapidly with increasing chiral order, necessitating the use of Markov chain Monte Carlo techniques for sampling their posterior probability density…

Nuclear Theory · Physics 2024-07-29 Isak Svensson , Andreas Ekström , Christian Forssén

We present density-functional theory (DFT) and quantum Monte Carlo (QMC) calculations designed to resolve experimental and theoretical controversies over the optical properties of H-terminated C nanoparticles (diamondoids). The QMC results…

Materials Science · Physics 2008-01-03 N. D. Drummond , A. J. Williamson , R. J. Needs , G. Galli

The Diffusion Monte Carlo (DMC) method is applied to compute the ground state energies of the water monomer and dimer and their D 2 O isotopomers using MB-pol; the most recent and most accurate ab inito- based potential energy surface…

Chemical Physics · Physics 2015-10-28 Joel Mallory , Vladimir Mandelshtam

A generalized version of the fidelity susceptibility of single-band and multi-orbital Hubbard models is systematically studied using single-site dynamical mean-field theory in combination with a hybridization expansion continuous-time…

Strongly Correlated Electrons · Physics 2016-12-08 Li Huang , Yilin Wang , Lei Wang , Philipp Werner

Hamiltonian Monte Carlo (HMC) is widely used for sampling from high dimensional target distributions with densities known up to proportionality. While HMC exhibits favorable scaling properties in high dimensions, it struggles with strongly…

Computation · Statistics 2025-07-30 Joonha Park
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