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The hybrid Monte Carlo (HMC) algorithm is a ubiquitous method in computational physics with applications ranging from condensed matter to lattice QCD and beyond. However, HMC simulations often suffer from long autocorrelation times,…

High Energy Physics - Lattice · Physics 2025-05-07 Johann Ostmeyer , Pavel Buividovich

A numerically implementable Multi-scale Many-Body approach to strongly correlated electron systems is introduced. An extension to quantum cluster methods, it approximates correlations on any given length-scale commensurate with the strength…

Strongly Correlated Electrons · Physics 2012-01-04 C. Slezak , M. Jarrell , Th. Maier , J. Deisz

Fourier acceleration is a technique used in Hybrid Monte Carlo simulations to decrease the autocorrelation between subsequent field configurations in the generated ensemble. It has been shown, in the perturbative limit, to eliminate the…

High Energy Physics - Lattice · Physics 2025-04-25 Cameron Cianci , Luchang Jin , Joshua Swaim

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

Inverse rendering methods have achieved remarkable performance in reconstructing high-fidelity 3D objects with disentangled geometries, materials, and environmental light. However, they still face huge challenges in reflective surface…

Computer Vision and Pattern Recognition · Computer Science 2024-11-22 Tengjie Zhu , Zhuo Chen , Jingnan Gao , Yichao Yan , Xiaokang Yang

The analysis developed by L\"uscher and Schaefer of the Hybrid Monte Carlo (HMC) algorithm is extended to include Fourier acceleration. We show for the $\phi^4$ theory that Fourier acceleration substantially changes the structure of the…

High Energy Physics - Lattice · Physics 2018-12-14 Norman H. Christ , Evan W. Wickenden

We present a continuous-time Monte Carlo method for quantum impurity models, which combines a weak-coupling expansion with an auxiliary-field decomposition. The method is considerably more efficient than Hirsch-Fye and free of time…

Strongly Correlated Electrons · Physics 2008-06-02 Emanuel Gull , Philipp Werner , Olivier Parcollet , Matthias Troyer

A quantum Monte Carlo method combining update of the loop algorithm with the global flip of the world line is proposed as an efficient method to study the magnetization process in an external field, which has been difficult because of…

Statistical Mechanics · Physics 2009-10-31 Hiroaki Onishi , Masamichi Nishino , Naoki Kawashima , Seiji Miyashita

We investigate the performance of the hybrid Monte Carlo algorithm in updating non-trivial global topological structures. We find that the hybrid Monte Carlo algorithm has serious problems decorrelating the global topological charge. This…

High Energy Physics - Lattice · Physics 2016-08-15 G. Boyd , B. Allés , M. D'Elia , A. Di Giacomo , E. Vicari

We present results from numerical simulations of three different 3d four-fermion models that exhibit Z_2, U(1), and SU(2) x SU(2) chiral symmetries, respectively. We performed the simulations by using the hybrid Monte Carlo algorithm. We…

High Energy Physics - Lattice · Physics 2010-10-27 Stavros Christofi , Costas Strouthos

We study the improvement of simulations of QCD with dynamical Wilson fermions by combining the Hybrid Monte Carlo algorithm with parallel tempering. As an indicator for decorrelation we use the topological charge.

High Energy Physics - Lattice · Physics 2015-06-25 E. -M. Ilgenfritz , Werner Kerler , H. Stüben

I consider the problem of integrating a function $f$ over the $d$-dimensional unit cube. I describe a multilevel Monte Carlo method that estimates the integral with variance at most $\epsilon^{2}$ in $O(d+\ln(d)d_{t}\epsilon^{-2})$ time,…

Computation · Statistics 2022-09-21 Nabil Kahalé

We explore a self-learning Markov chain Monte Carlo method based on the Adversarial Non-linear Independent Components Estimation Monte Carlo, which utilizes generative models and artificial neural networks. We apply this method to the…

Disordered Systems and Neural Networks · Physics 2021-01-06 Matija Medvidovic , Juan Carrasquilla , Lauren E. Hayward , Bohdan Kulchytskyy

By means of Metropolis Monte Carlo simulations of a coarse-grained model for flexible polymers, we investigate how the integrated autocorrelation times of different energetic and structural quantities depend on the temperature. We show…

Computational Physics · Physics 2014-08-19 Kai Qi , Michael Bachmann

The performance of Hamiltonian Monte Carlo simulations crucially depends on both the integration timestep and the number of integration steps. We present an adaptive general-purpose framework to automatically tune such parameters, based on…

Computational Physics · Physics 2025-12-10 Henrik Christiansen , Federico Errica , Francesco Alesiani

To accelerate the HMC with field transformation, we consider a variant of the trivializing map, the decimation map, which can be regarded as a coarse-graining transformation. Using the 2D $U(1)$ pure gauge model, combined with the guided…

High Energy Physics - Lattice · Physics 2023-12-11 Nobuyuki Matsumoto , Richard C. Brower , Taku Izubuchi

We consider a class of discrete time stochastic control problems motivated by some financial applications. We use a pathwise stochastic control approach to provide a dual formulation of the problem. This enables us to develop a numerical…

Probability · Mathematics 2011-12-20 Lajos Gergely Gyurko , Ben Hambly , Jan Hendrik Witte

We derive exact analytic results for several four-point correlation functions for statistical models exhibiting phase separation in two-dimensions. Our theoretical results are then specialized to the Ising model on the two-dimensional strip…

Statistical Mechanics · Physics 2021-10-27 Alessio Squarcini , Antonio Tinti

We present a method based on the Path Integral Monte Carlo formalism for the calculation of ground-state time correlation functions in quantum systems. The key point of the method is the consideration of time as a complex variable whose…

Statistical Mechanics · Physics 2015-06-24 Riccardo Rota , Joaquim Casulleras , Ferran Mazzanti , Jordi Boronat

We study autocorrelation times of physical observables in lattice QCD as a function of the molecular dynamics trajectory length in the hybrid Monte-Carlo algorithm. In an interval of trajectory lengths where energy and reversibility…

High Energy Physics - Lattice · Physics 2008-11-26 Harvey B. Meyer , Hubert Simma , Rainer Sommer , Michele Della Morte , Oliver Witzel , Ulli Wolff