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The simulation of diffusion-based molecular communication systems with absorbing receivers often requires a high computational complexity to produce accurate results. In this work, a new a priori Monte Carlo (APMC) algorithm is proposed to…

Emerging Technologies · Computer Science 2018-03-14 Yiran Wang , Adam Noel , Nan Yang

We give some new performance results for the Hybrid Monte Carlo (HMC) simulation of dynamical clover-improved Wilson fermions using an improved pseudo-fermion action. The generalisation of even-odd preconditioning for the standard Wilson…

High Energy Physics - Lattice · Physics 2009-04-25 Martin Hasenbusch

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

The Iterative Quasi-Monte Carlo (iQMC) method is a recently developed hybrid method for neutron transport simulations. iQMC replaces standard quadrature techniques used in deterministic linear solvers with Quasi-Monte Carlo simulation for…

Computational Physics · Physics 2025-01-13 Samuel Pasmann , Ilham Variansyah , C. T. Kelley , Ryan G. McClarren

We propose a modification of the Hybrid Monte Carlo (HMC) algorithm that overcomes the topological freezing of a two-dimensional $U(1)$ gauge theory with and without fermion content. This algorithm includes reversible jumps between…

High Energy Physics - Lattice · Physics 2023-05-09 David Albandea , Pilar Hernández , Alberto Ramos , Fernando Romero-López

We examine a wide class of stochastic approximation algorithms for solving (stochastic) nonlinear problems on Riemannian manifolds. Such algorithms arise naturally in the study of Riemannian optimization, game theory and optimal transport,…

Optimization and Control · Mathematics 2022-12-29 Mohammad Reza Karimi , Ya-Ping Hsieh , Panayotis Mertikopoulos , Andreas Krause

We consider how to accelerate fermionic molecular dynamics algorithms by introducing n pseudofermion fields coupled with the nth root of the fermionic kernel. This reduces the maximum pseudofermionic force, and thus allows a larger…

High Energy Physics - Lattice · Physics 2011-04-11 M. A. Clark , A. D. Kennedy

We introduce CriticSMC, a new algorithm for planning as inference built from a composition of sequential Monte Carlo with learned Soft-Q function heuristic factors. These heuristic factors, obtained from parametric approximations of the…

We present the ground state extension of the efficient quantum Monte Carlo algorithm for lattice fermions of arXiv:1411.0683. Based on continuous-time expansion of imaginary-time projection operator, the algorithm is free of systematic…

Strongly Correlated Electrons · Physics 2015-07-02 Lei Wang , Mauro Iazzi , Philippe Corboz , Matthias Troyer

A novel a priori Monte Carlo (APMC) algorithm is proposed to accurately simulate the molecules absorbed at spherical receiver(s) with low computational complexity in diffusion-based molecular communication (MC) systems. It is demonstrated…

Emerging Technologies · Computer Science 2018-12-18 Yiran Wang , Adam Noel , Nan Yang

The goal of this article is to introduce the Hamiltonian Monte Carlo (HMC) method -- a Hamiltonian dynamics-inspired algorithm for sampling from a Gibbs density $\pi(x) \propto e^{-f(x)}$. We focus on the "idealized" case, where one can…

Data Structures and Algorithms · Computer Science 2021-08-30 Nisheeth K. Vishnoi

We propose a new framework for Hamiltonian Monte Carlo (HMC) on truncated probability distributions with smooth underlying density functions. Traditional HMC requires computing the gradient of potential function associated with the target…

Machine Learning · Statistics 2017-09-12 Kexin Yi , Finale Doshi-Velez

Numerical Generalized Randomized Hamiltonian Monte Carlo is introduced, as a robust, easy to use and computationally fast alternative to conventional Markov chain Monte Carlo methods for continuous target distributions. A wide class of…

Computation · Statistics 2022-02-01 Tore Selland Kleppe

Monte Carlo (MC) simulations are essential computational approaches with widespread use throughout all areas of science. We present a method for accelerating lattice MC simulations using fully connected and convolutional artificial neural…

Strongly Correlated Electrons · Physics 2019-07-31 Shaozhi Li , Philip M. Dee , Ehsan Khatami , Steven Johnston

Hybrid Monte-Carlo (HMC) sampling smoother is a fully non-Gaussian four-dimensional data assimilation algorithm that works by directly sampling the posterior distribution formulated in the Bayesian framework. The smoother in its original…

Numerical Analysis · Computer Science 2016-12-21 Ahmed Attia , Razvan Stefanescu , Adrian Sandu

Stochastic Gradient Hamiltonian Monte Carlo (SGHMC) is a momentum version of stochastic gradient descent with properly injected Gaussian noise to find a global minimum. In this paper, non-asymptotic convergence analysis of SGHMC is given in…

Machine Learning · Statistics 2020-02-26 Huy N. Chau , Miklos Rasonyi

The Hybrid Monte Carlo algorithm for the simulation of QCD with dynamical staggered fermions is compared with Kramers equation algorithm. We find substantially different autocorrelation times for local and nonlocal observables. The…

High Energy Physics - Lattice · Physics 2009-10-28 M. E. Berbenni-Bitsch , A. P. Gottlob , S. Meyer , M. Puetz

We offer a new proposal for the Monte Carlo treatment of many-fermion systems in continuous space. It is based upon Diffusion Monte Carlo with significant modifications: correlated pairs of random walkers that carry opposite signs;…

Condensed Matter · Physics 2009-10-31 M. H. Kalos , Francesco Pederiva

The standard hybrid Monte Carlo algorithm uses the second order integrator at the molecular dynamics step. This choice of the integrator is not always the best. Using the Wilson fermion action, we study the performance of the hybrid Monte…

High Energy Physics - Lattice · Physics 2009-11-07 Tetsuya Takaishi

We construct asymptotic arguments for the relative efficiency of rejection-free Monte Carlo (MC) methods compared to the standard MC method. We find that the efficiency is proportional to $\exp{({const} \beta)}$ in the Ising, $\sqrt{\beta}$…

Statistical Mechanics · Physics 2009-11-11 H. Watanabe , S. Yukawa , M. A. Novotny , N. Ito