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We present a Monte Carlo algorithm that allows the simultaneous determination of a few extremal eigenpairs of a very large matrix without the need to compute the inner product of two vectors or store all the components of any one vector.…

Computational Physics · Physics 2015-05-13 T. E. Booth , J. E. Gubernatis

I show how to construct Monte Carlo algorithms (programs), prove that they are correct and document them. Complicated algorithms are build using a handful of elementary methods. This construction process is transparently illustrated using…

Computational Physics · Physics 2007-05-23 S. Jadach

We introduce a new method to price American-style options on underlying investments governed by stochastic volatility (SV) models. The method does not require the volatility process to be observed. Instead, it exploits the fact that the…

Computational Finance · Quantitative Finance 2012-07-26 Bhojnarine R. Rambharat , Anthony E. Brockwell

We propose a novel stochastic algorithm that randomly samples entire rows and columns of the matrix as a way to approximate an arbitrary matrix function using the power series expansion. This contrasts with existing Monte Carlo methods,…

Data Structures and Algorithms · Computer Science 2024-09-23 Nicolas L. Guidotti , Juan A. Acebrón , José Monteiro

We present a rigorous efficient event-chain Monte Carlo algorithm for long-range interacting particle systems. Using a cell-veto scheme within the factorized Metropolis algorithm, we compute each single-particle move with a fixed number of…

Statistical Mechanics · Physics 2016-09-28 Sebastian C. Kapfer , Werner Krauth

A method for generating random $U(1)$ variables with Boltzmann distribution is presented. It is based on the rejection method with transformation of variables. High efficiency is achieved for all range of temparatures or coupling…

High Energy Physics - Lattice · Physics 2009-10-22 Tetsuya Hattori , Hideo Nakajima

When calculating satellite trajectories in low-earth orbit, engineers need to adequately estimate aerodynamic forces. But to this day, obtaining the drag acting on the complicated shapes of modern spacecraft suffers from many sources of…

Computational Physics · Physics 2013-12-16 J. Brent Parham , L. A. Barba

We study a method, Extra Chance Generalized Hybrid Monte Carlo, to avoid rejections in the Hybrid Monte Carlo method and related algorithms. In the spirit of delayed rejection, whenever a rejection would occur, extra work is done to find a…

Probability · Mathematics 2014-10-29 Cédric M. Campos , J. M. Sanz-Serna

Monte Carlo methods use random sampling to estimate numerical quantities which are hard to compute deterministically. One important example is the use in statistical physics of rapidly mixing Markov chains to approximately compute partition…

Quantum Physics · Physics 2017-07-12 Ashley Montanaro

Various Monte Carlo programs, developed either by small groups or widely available, have been used to calculate the effects of decays of radioactive chains, from the original parent nucleus to the final stable isotopes. These chains include…

Nuclear Experiment · Physics 2015-05-27 Kareem Kazkaz , Nick Walsh

The standard kinetic Monte Carlo algorithm is an extremely efficient method to carry out serial simulations of dynamical processes such as thin-film growth. However, in some cases it is necessary to study systems over extended time and…

Materials Science · Physics 2007-05-23 Yunsic Shim , Jacques G. Amar

We propose three novel gerrymandering algorithms which incorporate the spatial distribution of voters with the aim of constructing gerrymandered, equal-population, connected districts. Moreover, we develop lattice models of voter…

Physics and Society · Physics 2021-07-01 Kyle Gatesman , James Unwin

Parton showers in Monte Carlo event generators reflect to a certain accuracy our understanding of QCD radiation at all orders. For observables sensitive to interjet energy flow in well defined regions of phase space, it has been known for…

High Energy Physics - Phenomenology · Physics 2007-06-19 Mrinal Dasgupta

We propose a sequential Markov chain Monte Carlo (SMCMC) algorithm to sample from a sequence of probability distributions, corresponding to posterior distributions at different times in on-line applications. SMCMC proceeds as in usual MCMC…

Statistics Theory · Mathematics 2013-08-20 Yun Yang , David B. Dunson

We investigate the simulation of events with gaps between jets with a veto on additional radiation in the gap in Herwig++. We discover that the currently-used random treatment of radiation in the parton shower is generating some unphysical…

High Energy Physics - Phenomenology · Physics 2015-05-27 Alex Schofield , Michael H. Seymour

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

This article addresses online variational estimation in parametric state-space models. We propose a new procedure for efficiently computing the evidence lower bound and its gradient in a streaming-data setting, where observations arrive…

Methodology · Statistics 2026-02-09 Mathis Chagneux , Mathias Müller , Pierre Gloaguen , Sylvain Le Corff , Jimmy Olsson

A method for organizing next-to-leading order QCD calculations using a veto which enforces the cancellations between virtual and real emission diagrams is applied to hadronic collisions. The method employs phase space slicing with the…

High Energy Physics - Phenomenology · Physics 2009-11-07 Matt Dobbs

We describe a number of strategies for minimizing and calculating accurately the statistical uncertainty in quantum Monte Carlo calculations. We investigate the impact of the sampling algorithm on the efficiency of the variational Monte…

Computational Physics · Physics 2012-02-14 R. M. Lee , G. J. Conduit , N. Nemec , P. Lopez Rios , N. D. Drummond

The purpose of this paper is to design an algorithm for the computation of the counterparty risk which is competitive in regards of a brute force "Monte-Carlo of Monte-Carlo" method (with nested simulations). This is achieved using marked…

Computational Finance · Quantitative Finance 2012-03-13 Pierre Henry-Labordere