Skip to main content

Search

Show all results for

Home

Publication

Update of the Binoth Les Houches Accord for a standard interface between Monte Carlo tools and one-loop programs

About
Privacy
Disclaimer

Copyright © 2025 EPFL, all rights reserved

Graph Chatbot

Valentin Hirschi
2014
journal articles

Abstract

We present an update of the Binoth Les Houches Accord (BLHA) to standardise the interface between Monte Carlo programs and codes providing one-loop matrix elements. (C) 2013 Elsevier B.V. All rights reserved.

Official source

https://infoscience.epfl.ch/entities/publication/aa623d4e-b479-42e0-affb-d23f88ef5779

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Related concepts (9)

Monte Carlo method

Monte Carlo methods, or Monte Carlo experiments, are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results. The underlying concept is to use randomness to solve problems that might be deterministic in principle. They are often used in physical and mathematical problems and are most useful when it is difficult or impossible to use other approaches. Monte Carlo methods are mainly used in three problem classes: optimization, numerical integration, and generating draws from a probability distribution.

Markov chain Monte Carlo

In statistics, Markov chain Monte Carlo (MCMC) methods comprise a class of algorithms for sampling from a probability distribution. By constructing a Markov chain that has the desired distribution as its equilibrium distribution, one can obtain a sample of the desired distribution by recording states from the chain. The more steps that are included, the more closely the distribution of the sample matches the actual desired distribution. Various algorithms exist for constructing chains, including the Metropolis–Hastings algorithm.

In computer science a for-loop or for loop is a control flow statement for specifying iteration. Specifically, a for loop functions by running a section of code repeatedly until a certain condition has been satisfied. For-loops have two parts: a header and a body. The header defines the iteration and the body is the code that is executed once per iteration. The header often declares an explicit loop counter or loop variable. This allows the body to know which iteration is being executed.

Related publications (2)

Tri-Axial Magnetic Field Sensor up to VHF with Frequency Weighing

German Augusto Ramirez Arroyave

This contribution presents an isotropic magnetic field probe with shaped frequency response in the band 100 kHz - 400 MHz to ponder the aggregate response according to the ICNIRP 2020 guidelines. The basic sensor is a printed loop which is modelled as a Th ...

IEEE2023

Dynamic prediction-based relocation policies in one-way station-based carsharing systems with complete journey reservations

Nikolaos Geroliminis, Burak Boyaci, Martin Jean Marie Joseph Repoux, Mor Kaspi

In this paper, we study the operations of a one-way station-based carsharing system implementing a complete journey reservation policy. We consider the percentage of served demand as a primary performance measure and analyze the effect of several dynamic s ...

PERGAMON-ELSEVIER SCIENCE LTD2019