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In calculating integral or discrete transforms, use has been made of fast algorithms for multiplying vectors by matrices whose elements are specified as values of special (Chebyshev, Legendre, Laguerre, etc.) functions. The currently…

Numerical Analysis · Mathematics 2022-08-11 Andrew V. Terekhov

A hybrid Monte Carlo (HMC) approach is employed to quantify the influence of inelastic deformation on the microstructural evolution of polycrystalline materials. This approach couples a time explicit material point method (MPM) for…

Materials Science · Physics 2015-05-19 Liangzhe Zhang , Remi Dingreville , Timothy Bartel , Mark T. Lusk

We discuss algorithms for domain wall fermions focussing on accelerating Hybrid Monte Carlo sampling of gauge configurations. Firstly a new multigrid algorithm for domain wall solvers and secondly a domain decomposed hybrid monte carlo…

High Energy Physics - Lattice · Physics 2022-04-01 Peter A Boyle , Dennis Bollweg , Christopher Kelly , Azusa Yamaguchi

In Hybrid Monte Carlo simulations for full QCD, the gauge fields evolve smoothly as a function of Molecular Dynamics time. Here we investigate improved methods of estimating the trial or starting solutions for the Dirac matrix inversion as…

High Energy Physics - Lattice · Physics 2009-10-28 R. C. Brower , T. Ivanenko , A. R. Levi , K. N. Orginos

We introduce methodologies for highly scalable quantum Monte Carlo simulations of electron-phonon models, and report benchmark results for the Holstein model on the square lattice. The determinant quantum Monte Carlo (DQMC) method is a…

Strongly Correlated Electrons · Physics 2022-07-18 Benjamin Cohen-Stead , Owen Bradley , Cole Miles , George Batrouni , Richard Scalettar , Kipton Barros

We develop a GPU-accelerated hybrid quantum Monte Carlo (QMC) algorithm to solve the fundamental yet difficult problem of $U(1)$ gauge field coupled to fermions, which gives rise to a $U(1)$ Dirac spin liquid state under the description of…

Strongly Correlated Electrons · Physics 2026-02-27 Kexin Feng , Chuang Chen , Zi Yang Meng

Recent years have seen a rise in the application of machine learning techniques to aid the simulation of hard-to-sample systems that cannot be studied using traditional methods. Despite the introduction of many different architectures and…

Disordered Systems and Neural Networks · Physics 2025-10-09 Luca Maria Del Bono , Federico Ricci-Tersenghi , Francesco Zamponi

Quantum adiabatic evolution algorithm suggested by Farhi et al. was effective in solving instances of NP-complete problems. The algorithm is governed by the adiabatic theorem. Therefore, in order to reduce the running time, it is essential…

Quantum Physics · Physics 2015-06-26 Joonwoo Bae , Younghun Kwon

We consider the problem of estimating the expected outcomes of Monte Carlo processes whose outputs are described by multidimensional random variables. We tightly characterize the quantum query complexity of this problem for various choices…

Quantum Physics · Physics 2021-07-09 Arjan Cornelissen , Sofiene Jerbi

The advantages of using Multi-Step corrections for simulations of lattice gauge theories with dynamical fermions will be discussed. This technique is suited for algorithms based on the Multi-Boson representation of the dynamical fermions as…

High Energy Physics - Lattice · Physics 2008-11-26 Enno E. Scholz , Istvan Montvay

We demonstrate that substantial progress can be achieved in the study of the phase structure of 4-dimensional compact QED by a joint use of hybrid Monte Carlo and multicanonical algorithms, through an efficient parallel implementation. This…

High Energy Physics - Lattice · Physics 2015-06-25 G. Arnold , Th. Lippert , K. Schilling

We demonstrate that substantial progress can be achieved in the study of the phase structure of 4-dimensional compact QED by a joint use of hybrid Monte Carlo and multicanonical algorithms, through an efficient parallel implementation. This…

High Energy Physics - Lattice · Physics 2016-08-25 G. Arnold , Th. Lippert , K. Schilling

A hybrid model of the Deutsch-Jozsa algorithm is presented, inspired by the proposals of hybrid computation by S. Lloyd and P. van Loock et. al. The model is based on two observations made about both the discrete and continuous algorithms…

Quantum Physics · Physics 2010-01-05 Luis A. Garcia , Jagdish R. Luthra

Fast Fourier transform (FFT) based methods have turned out to be an effective computational approach for numerical homogenisation. In particular, Fourier-Galerkin methods are computational methods for partial differential equations that are…

Numerical Analysis · Mathematics 2020-04-22 Jaroslav Vondřejc , Dishi Liu , Martin Ladecký , Hermann G. Matthies

We propose a technique for design of quantum Fourier transforms, and ensuing quantum algorithms, in a single interaction step by engineered Hamiltonians of circulant symmetry. The method uses adiabatic evolution and is robust against…

Quantum Physics · Physics 2009-10-07 B. T. Torosov , N. V. Vitanov

By decomposing the important sampled imaginary time Schr\"odinger evolution operator to fourth order with positive coefficients, we derived a number of distinct fourth order Diffusion Monte Carlo algorithms. These sophisticated algorithms…

Nuclear Theory · Physics 2009-11-06 Harald A. Forbert , Siu A. Chin

Stochastic quantisation is applied to the problem of calculating real-time evolution on a Minkowskian space-time lattice. We employ optimized updating using reweighting, or gauge fixing, respectively. These procedures do not affect the…

High Energy Physics - Lattice · Physics 2009-11-13 Denes Sexty

The phaseless Auxiliary Field Quantum Monte Carlo method provides a well established approximation scheme for accurate calculations of ground state energies of many-fermions systems. Here we apply the method to the calculation of imaginary…

Strongly Correlated Electrons · Physics 2015-06-17 M. Motta , D. E. Galli , S. Moroni , E. Vitali

We present a Hamiltonian Monte Carlo algorithm to sample from multivariate Gaussian distributions in which the target space is constrained by linear and quadratic inequalities or products thereof. The Hamiltonian equations of motion can be…

Computation · Statistics 2013-06-06 Ari Pakman , Liam Paninski

We propose automated augmented conjugate inference, a new inference method for non-conjugate Gaussian processes (GP) models. Our method automatically constructs an auxiliary variable augmentation that renders the GP model conditionally…

Machine Learning · Statistics 2020-02-27 Théo Galy-Fajou , Florian Wenzel , Manfred Opper