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Arrays of Rydberg atoms are a powerful platform to realize strongly-interacting quantum many-body systems. A common Rydberg Hamiltonian is free of the sign problem, meaning that its equilibrium properties are amenable to efficient…

Strongly Correlated Electrons · Physics 2023-07-20 Ejaaz Merali , Isaac J. S. De Vlugt , Roger G. Melko

Polynomial approximations to the inverse of the fermion matrix are used to filter the dynamics of the upper energy scales in HMC simulations. The use of a multiple time-scale integration scheme allows the filtered pseudofermions to be…

High Energy Physics - Lattice · Physics 2015-05-28 Waseem Kamleh , Mike Peardon

Complete spectra of the staggered Dirac operator $\Dirac$ are determined in four-dimensional $SU(2)$ gauge fields with and without dynamical fermions. An attempt is made to relate the performance of multigrid and conjugate gradient…

High Energy Physics - Lattice · Physics 2009-10-22 Thomas Kalkreuter

Three topics concerning fermion simulation algorithms are discussed: 1.) A performance comparison of the multiboson technique to simulate dynamical fermions and the Kramers equation algorithm, 2.) the question of reversibility in the Hybrid…

High Energy Physics - Lattice · Physics 2007-05-23 Karl Jansen , Beat Jegerlehner , Chuan Liu

We introduce a numerical algorithm to stochastically sample the dual fermion perturbation series around the dynamical mean field theory, generating all topologies of two-particle interaction vertices. We show results in the weak and strong…

Strongly Correlated Electrons · Physics 2016-07-07 Sergei Iskakov , Andrey E. Antipov , Emanuel Gull

A Dirac choice for the averaging kernel $C$ is implemented numerically. This improved kernel will be needed in gauge covariant multigrid computations for propagators of staggered fermions. Results for $C$ and the variational coarse grid…

High Energy Physics - Lattice · Physics 2016-08-31 Thomas Kalkreuter

We compare the performances of the exact one-flavor algorithm (EOFA) and the rational hybrid Monte Carlo algorithm (RHMC), for dynamical simulations of lattice QCD with domain-wall fermion.

High Energy Physics - Lattice · Physics 2014-12-04 Yu-Chih Chen , Ting-Wai Chiu

An exact, nonlocal, finite step-size algorithm for Monte Carlo simulation of theories with dynamical fermions is proposed. The algorithm is based on obtaining the new configuration U' from the old one U by solving the equation $ M(U') \eta…

High Energy Physics - Lattice · Physics 2009-11-07 T. Bakeyev

We study discretization effects of the Wilson and staggered Dirac operator with $N_{\rm c}>2$ using chiral random matrix theory (chRMT). We obtain analytical results for the joint probability density of Wilson-chRMT in terms of a…

High Energy Physics - Lattice · Physics 2012-02-09 Mario Kieburg , Jacobus J. M. Verbaarschot , Savvas Zafeiropoulos

We apply the Hybrid Monte Carlo method to the simulation of overlap fermions. We give the fermionic force for the molecular dynamics update. We present early results on a small dynamical chiral ensemble.

High Energy Physics - Lattice · Physics 2009-11-10 N. Cundy , S. Krieg , A. Frommer , Th. Lippert , K. Schilling

We demonstrate the applicability of a recently proposed multiscale thermalization algorithm to two-color quantum chromodynamics (QCD) with two mass-degenerate fermion flavors. The algorithm involves refining an ensemble of gauge…

High Energy Physics - Lattice · Physics 2016-12-06 William Detmold , Michael G. Endres

Continuous-time determinantal algorithm is proposed for the quantum Monte Carlo simulation of the interacting fermions. The scheme does not invoke Hubbard-Stratonovich transformation. The fermionic action is divided into two parts. One of…

Strongly Correlated Electrons · Physics 2007-05-23 A. N. Rubtsov

Ridge regression (RR) is an important machine learning technique which introduces a regularization hyperparameter $\alpha$ to ordinary multiple linear regression for analyzing data suffering from multicollinearity. In this paper, we present…

Quantum Physics · Physics 2021-08-03 Chao-Hua Yu , Fei Gao , Qiao-Yan Wen

Diagrammatic Monte Carlo (DiagMC) is a numeric technique that allows one to calculate quantities specified in terms of diagrammatic expansions, the latter being a standard tool of many-body quantum statistics. The sign problem that is…

Statistical Mechanics · Physics 2019-10-18 Kris Van Houcke , Evgeny Kozik , Nikolay Prokof'ev , Boris Svistunov

In the simplified setting of the Schwinger model we present a systematic study on the simulation of dynamical fermions by global accept/reject steps that take into account the fermion determinant. A family of exact algorithms is developed,…

High Energy Physics - Lattice · Physics 2008-11-26 Francesco Knechtli , Ulli Wolff

We propose improved estimators to compute the reweighting factors which are needed for lattice QCD calculations that rely on twisted-mass reweighting for the light quark contribution and the Rational Hybrid Monte Carlo (RHMC) algorithm for…

High Energy Physics - Lattice · Physics 2024-03-19 Simon Kuberski

We report on simulations of QCD with many flavors of degenerate quarks, the DBW2 gauge action and naive staggered fermions, using the rational hybrid Monte Carlo algorithm. We primarily focus on eight degenerate quark flavors where a…

High Energy Physics - Lattice · Physics 2009-02-05 Xiao-Yong Jin , Robert D. Mawhinney

We propose a modification of the Hybrid-Monte-Carlo algorithm that allows for a larger step-size of the integration scheme at constant acceptance rate. The key ingredient is that the pseudo-fermion action is split into two parts. We test…

High Energy Physics - Lattice · Physics 2009-11-07 Martin Hasenbusch

We performed dynamical simulations with HYP smeared staggered fermions using the recently proposed partial-global stochastic Metropolis algorithm with fermion matrix reduction and determinant breakup improvements. In this paper we discuss…

High Energy Physics - Lattice · Physics 2009-11-07 Andrei Alexandru , Anna Hasenfratz

Hamiltonian Monte Carlo (HMC) improves the computational efficiency of the Metropolis algorithm by reducing its random walk behavior. Riemannian Manifold HMC (RMHMC) further improves HMC's performance by exploiting the geometric properties…

Computation · Statistics 2015-06-22 Shiwei Lan , Vassilios Stathopoulos , Babak Shahbaba , Mark Girolami