1999
DOI: 10.1016/s0010-4655(99)00209-x
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Vegas revisited: Adaptive Monte Carlo integration beyond factorization

Abstract: We present a new adaptive Monte Carlo integration algorithm for ill-behaved integrands with non-factorizable singularities. The algorithm combines Vegas with multi channel sampling and performs significantly better than Vegas for a large class of integrals appearing in physics. IntroductionThroughout physics, it is frequently necessary to evaluate the integral I(f ) of a function f on a manifold M using a measure µ(1) *

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Cited by 131 publications
(121 citation statements)
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“…The finite Catani-Seymour dipole subtraction terms and real emission matrix elements are built around amplitudes generated with the O'Mega [43] matrix-element generator. Adaptive single-channel Monte Carlo integration is implemented using the Vamp [44] library. Contrary to the first calculation, the second calculation does not implement subprocesses involving external bottom quarks which only amount to ≈ 3% of the LO cross section and thus can be safely neglected at order α 2 s α s .…”
Section: Conventions and Calculational Setupmentioning
confidence: 99%
“…The finite Catani-Seymour dipole subtraction terms and real emission matrix elements are built around amplitudes generated with the O'Mega [43] matrix-element generator. Adaptive single-channel Monte Carlo integration is implemented using the Vamp [44] library. Contrary to the first calculation, the second calculation does not implement subprocesses involving external bottom quarks which only amount to ≈ 3% of the LO cross section and thus can be safely neglected at order α 2 s α s .…”
Section: Conventions and Calculational Setupmentioning
confidence: 99%
“…The modern release series (v2) has been developed to meet the demands of LHC physics analysis, while its generic treatment of beam-spectra and initial-state photon radiation makes it especially well suited for lepton collider physics. The program has a modular structure and consists of several subcomponents, the most important being O'Mega [27], Vamp [62] and Circe [63]: O'Mega computes multi-leg tree-level matrix elements as helicity amplitudes in a recursive way that avoids Feynman diagrams. Vamp is used for Monte-Carlo integration and grid sampling.…”
Section: Jhep12(2016)075mentioning
confidence: 99%
“…Its structure is strictly object-oriented, so that a modular structure enables the convenient interface to numerous other programs. The main sub-components of WHIZARD are O'Mega [2], VAMP [3] and CIRCE [4]: O'Mega provides multi-leg tree-level matrix elements using the helicity formalism. VAMP is used for Monte-Carlo integration and grid sampling.…”
Section: The Whizard Event Generatormentioning
confidence: 99%