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相关论文: MC@NLO event generation by reweighting unweighted …

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We introduce a new technique, that we dub Born spreading, aimed at reducing the number of negative-weight $\mathbb S$ events in the MC@NLO matching of NLO calculations with parton-shower simulations. We show that such a technique, based on…

高能物理 - 唯象学 · 物理学 2023-10-09 Rikkert Frederix , Paolo Torrielli

The generation of unit-weight events for complex scattering processes presents a severe challenge to modern Monte Carlo event generators. Even when using sophisticated phase-space sampling techniques adapted to the underlying transition…

高能物理 - 唯象学 · 物理学 2022-05-18 Katharina Danziger , Timo Janßen , Steffen Schumann , Frank Siegert

We present a novel integrator based on normalizing flows which can be used to improve the unweighting efficiency of Monte-Carlo event generators for collider physics simulations. In contrast to machine learning approaches based on surrogate…

高能物理 - 唯象学 · 物理学 2020-04-22 Christina Gao , Stefan Hoeche , Joshua Isaacson , Claudius Krause , Holger Schulz

We apply Continuous Normalizing Flows trained with the Flow Matching method to the problem of phase-space sampling in Monte Carlo event generation for high-energy collider physics. Focusing on lepton-pair and top quark pair production with…

高能物理 - 唯象学 · 物理学 2026-04-07 Enrico Bothmann , Timo Janßen , Max Knobbe , Bernhard Schmitzer , Fabian Sinz

Event generation with neural networks has seen significant progress recently. The big open question is still how such new methods will accelerate LHC simulations to the level required by upcoming LHC runs. We target a known bottleneck of…

高能物理 - 唯象学 · 物理学 2021-04-28 Mathias Backes , Anja Butter , Tilman Plehn , Ramon Winterhalder

We study a phenomenological ansatz for merging next-to-next-to-leading order (NNLO) calculations with Monte Carlo event generators. We reweight them to match bin-integrated NNLO differential distributions. To test this procedure, we study…

We propose a method for matching the next-to-leading order (NLO) calculation of a given QCD process with a parton shower Monte Carlo (MC) simulation. The method has the following features: fully exclusive events are generated, with…

高能物理 - 唯象学 · 物理学 2010-11-11 S. Frixione , B. R. Webber

An increase in theoretical precision of Monte Carlo event generators is typically accompanied by an increased need for computational resources. One major obstacle are negative weighted events, which appear in Monte Carlo simulations with…

高能物理 - 唯象学 · 物理学 2021-10-29 Katharina Danziger , Stefan Höche , Frank Siegert

We present an algorithm for unweighted event generation in the partonic process pp -> WZ (j) with leptonic decays at next-to-leading order in alpha_S. Monte Carlo programs for processes such as this frequently generate events with negative…

高能物理 - 唯象学 · 物理学 2009-10-31 M. Dobbs , M. Lefebvre

Merging the benefits of an NLO calculation with event generators is a topic of current interest. Among other things, it is advantageous to be able to generate unweighted events according to NLO matrix elements. I report on an algorithm…

高能物理 - 唯象学 · 物理学 2007-05-23 Stefan Weinzierl

An important area of high energy physics studies at the Large Hadron Collider (LHC) currently concerns the need for more extensive and precise comparison data. Important tools in this realm are event reweighing and evaluation of more…

In this publication, uncertainties in and differences between the MC@NLO and POWHEG methods for matching next-to-leading order QCD calculations with parton showers are discussed. Implementations of both algorithms within the event generator…

高能物理 - 唯象学 · 物理学 2012-09-25 Stefan Hoeche , Frank Krauss , Marek Schonherr , Frank Siegert

In this work we present a new approach for the combination of electroweak (EW) corrections at high energies, the so-called EW Sudakov logarithms (EWSL), and next-to-leading-order QCD predictions matched to parton-shower simulations…

高能物理 - 唯象学 · 物理学 2024-05-24 Davide Pagani , Timea Vitos , Marco Zaro

In this work, we revisit unweighted event generation for multi-parton tree-level processes in massless QCD. We introduce a two-step approach, in which initially unweighted events are generated at leading-colour (LC) accuracy, followed by a…

高能物理 - 唯象学 · 物理学 2025-01-14 Rikkert Frederix , Timea Vitos

We present a Monte-Carlo event generator for simulating chargino pair-production at the International Linear Collider (ILC) at next-to-leading order in the electroweak couplings. By properly resumming photons in the soft and collinear…

高能物理 - 唯象学 · 物理学 2008-11-26 W. Kilian , J. Reuter , T. Robens

Data analyses in particle physics rely on an accurate simulation of particle collisions and a detailed simulation of detector effects to extract physics knowledge from the recorded data. Event generators together with a GEANT-based…

高能物理 - 实验 · 物理学 2025-05-12 CMS Collaboration

We show how a careful analysis of the behaviour of a parton shower Monte Carlo in the vicinity of the soft and collinear regions allows one to formulate a modified MC@NLO-matching prescription that reduces the number of negative-weight…

高能物理 - 唯象学 · 物理学 2020-08-26 R. Frederix , S. Frixione , S. Prestel , P. Torrielli

This is the user's manual of [email protected]. This package is a practical implementation, based upon the HERWIG event generator, of the recently proposed MC@NLO formalism for matching the next-to-leading order calculation of a QCD process with a…

高能物理 - 唯象学 · 物理学 2007-05-23 S. Frixione , B. R. Webber

Efficient generation of LHC events is hindered by the rapidly rising cost of evaluating QCD matrix elements with increasing multiplicity. We build on a recently proposed two-step strategy in which unweighted events are first generated using…

高能物理 - 唯象学 · 物理学 2026-01-28 Rikkert Frederix , Timea Vitos

We consider associated $Zh$ production with $Z \to \ell^+ \ell^-$ and $h \to b \bar b$ decays in hadronic collisions. In the framework of the Standard Model effective field theory (SMEFT) we calculate the QCD corrections to this process and…

高能物理 - 唯象学 · 物理学 2022-07-11 Ulrich Haisch , Darren J. Scott , Marius Wiesemann , Giulia Zanderighi , Silvia Zanoli
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