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It has been a big challenge for lattice QCD to simulate dynamical quarks near the chiral limit. Theoretically, it is well-known that the naive chiral symmetry cannot be realized on the lattice (the Nielsen-Ninomiya theorem). Also…

High Energy Physics - Lattice · Physics 2017-08-23 Hidenori Fukaya

Estimating the trace of the inverse of a large matrix is an important problem in lattice quantum chromodynamics. A multilevel Monte Carlo method is proposed for this problem that uses different degree polynomials for the levels. The…

High Energy Physics - Lattice · Physics 2023-06-19 Paul Lashomb , Ronald B. Morgan , Travis Whyte , Walter Wilcox

The polynomial subtraction method, a new numerical approach for reducing the noise variance of Lattice QCD disconnected matrix elements calculation, is introduced in this paper. We use the MinRes polynomial expansion of the QCD matrix as…

High Energy Physics - Lattice · Physics 2014-05-09 Quan Liu , Walter Wilcox , Ron Morgan

We study efficiency of higher order integrator schemes for the hybrid Monte Carlo (HMC) algorithm. Numerical tests are performed for Quantum Chromo Dynamics (QCD) with two flavors of Wilson fermions. We compare 2nd, 4th and 6th order…

High Energy Physics - Lattice · Physics 2009-10-31 Tetsuya Takaishi

We first obtain the most general and compact parametrization of the unitary transformation diagonalizing any 3 by 3 hermitian matrix H, as a function of its elements and eigenvalues. We then study a special class of fermion mass matrices,…

High Energy Physics - Phenomenology · Physics 2010-04-06 Gilles Couture , Cherif Hamzaoui , Steven S. Y. Lu , Manuel Toharia

We explore the possibility of computing fermionic correlators on the lattice by combining a domain decomposition with a multi-level integration scheme. The quark propagator is expanded in series of terms with a well defined hierarchical…

High Energy Physics - Lattice · Physics 2016-05-18 Marco Cè , Leonardo Giusti , Stefan Schaefer

Sequence model based NLP applications can be large. Yet, many applications that benefit from them run on small devices with very limited compute and storage capabilities, while still having run-time constraints. As a result, there is a need…

Computation and Language · Computer Science 2020-10-08 Urmish Thakker , Jesse Beu , Dibakar Gope , Ganesh Dasika , Matthew Mattina

We discuss recent algorithmic improvements in simulating finite temperature QCD on a lattice. In particular, the Rational Hybrid Monte Carlo(RHMC) algorithm is employed to generate lattice configurations for 2+1 flavor QCD. Unlike the…

High Energy Physics - Lattice · Physics 2008-11-26 M. Cheng , M. A. Clark , C. Jung , R. D. Mawhinney

Hierarchical matrices approximate a given matrix by a decomposition into low-rank submatrices that can be handled efficiently in factorized form. $\mathcal{H}^2$-matrices refine this representation following the ideas of fast multipole…

Numerical Analysis · Mathematics 2024-04-24 Steffen Börm

We simulate Quantum Chromodynamics in four Euclidean dimensions with two (degenerate mass) flavors of dynamical quarks. The Dirac operator is the so-called chirally improved operator that has been studied so far in quenched calculations. We…

High Energy Physics - Lattice · Physics 2007-05-23 C. B. Lang , Pushan Majumdar , Wolfgang Ortner

We introduce a new algorithm which we call the {Rational Hybrid Monte Carlo} Algorithm (RHMC). This method uses a rational approximation to the fermionic kernel together with a noisy Kennedy-Kuti acceptance step to give an efficient…

High Energy Physics - Lattice · Physics 2009-10-31 Ivan Horvath , A. D. Kennedy , Stefan Sint

We present numerical methods to solve the Generalized Hartree-Fock theory for fermionic systems in lattices, both in thermal equilibrium and out of equilibrium. Specifically, we show how to determine the covariance matrix corresponding to…

Quantum Physics · Physics 2013-04-10 Christina V. Kraus , J. Ignacio Cirac

We investigate the properties of the Hybrid Monte-Carlo algorithm (HMC) in high dimensions. HMC develops a Markov chain reversible w.r.t. a given target distribution $\Pi$ by using separable Hamiltonian dynamics with potential $-\log\Pi$.…

To evaluate the effectiveness of machine learning in systems with competing interactions, we developed a self-learning quantum Monte Carlo (SLQMC) method to simulate the phase transition in the classical Holstein-spin-fermion model. In…

Strongly Correlated Electrons · Physics 2025-09-09 Shaozhi Li

Particle MCMC involves using a particle filter within an MCMC algorithm. For inference of a model which involves an unobserved stochastic process, the standard implementation uses the particle filter to propose new values for the stochastic…

Computation · Statistics 2016-09-26 Paul Fearnhead , Loukia Meligkotsidou

The computational cost of many signal processing and machine learning techniques is often dominated by the cost of applying certain linear operators to high-dimensional vectors. This paper introduces an algorithm aimed at reducing the…

Machine Learning · Computer Science 2016-03-30 Luc Le Magoarou , Rémi Gribonval

Harmonic model predictive control (HMPC) is a model predictive control (MPC) formulation which displays several benefits over other MPC formulations, especially when using a small prediction horizon. These benefits, however, come at the…

Optimization and Control · Mathematics 2022-11-16 Pablo Krupa , Daniel Limon , Alberto Bemporad , Teodoro Alamo

Efficient continuous time quantum Monte Carlo (CT-QMC) algorithms that do not suffer from time discretization errors have become the state-of-the-art for most discrete quantum models. They have not been widely used yet for fermionic quantum…

Strongly Correlated Electrons · Physics 2015-07-08 Mauro Iazzi , Matthias Troyer

We discuss some of the implications of simulating QCD when the action used for the sea quarks is different from that used for the valence quarks. We present exploratory results for the hadron mass spectrum and pseudoscalar meson decay…

High Energy Physics - Lattice · Physics 2009-11-10 UKQCD Collaboration , K. C. Bowler , B. Joó , R. D. Kenway , C. M. Maynard , R. J. Tweedie

A new algorithm is introduced to integrate the equations of rotational motion. The algorithm is derived within a leapfrog framework and the quantities involved into the integration are mid-step angular momenta and on-step orientational…

Computational Physics · Physics 2007-05-23 Igor P. Omelyan
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