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相关论文: A Cell Resampler study of Negative Weights in Mult…

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We demonstrate that cell resampling can eliminate the bulk of negative event weights in large event samples of high multiplicity processes without discernible loss of accuracy in the predicted observables. The application of cell resampling…

高能物理 - 唯象学 · 物理学 2023-09-26 Jeppe R. Andersen , Andreas Maier , Daniel Maître

We propose the Positive Resampler to solve the problem associated with event samples from state-of-the-art predictions for scattering processes at hadron colliders typically involving a sizeable number of events contributing with negative…

高能物理 - 唯象学 · 物理学 2020-12-16 Jeppe R. Andersen , Christian Gutschow , Andreas Maier , Stefan Prestel

Monte Carlo event generators are an essential tool for data analysis in collider physics. To include subleading quantum corrections, these generators often need to produce negative weight events, which leads to statistical dilution of the…

高能物理 - 唯象学 · 物理学 2020-10-21 Benjamin Nachman , Jesse Thaler

High statistical precision is critical for Monte Carlo (MC) samples in high energy physics and is degraded by negatively weighted events. This paper investigates a procedure to learn the relationship between the negative and positive weight…

高能物理 - 实验 · 物理学 2026-01-15 Christopher Palmer , Braden Kronheim

We present a metric on the space of scattering events based on relative transverse momenta and with explicit sensitivity to intermediate resonances. With this new metric, negative weights in an event sample can be reduced substantially…

高能物理 - 唯象学 · 物理学 2026-05-14 Jeppe R. Andersen , Ella Cole , Andreas Maier

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

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

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

Monte Carlo simulations are an essential tool in particle physics data analysis. Events are typically generated alongside weights that redistribute the cross section of the simulated process across the phase space. These weights can be…

高能物理 - 唯象学 · 物理学 2026-05-13 Benjamin Nachman , Dennis Noll

Negatively weighted events, which appear in the Monte Carlo (MC) simulation of particle collisions, significantly increases the computational resource requirements of current and future collider experiments. This paper introduces and…

高能物理 - 唯象学 · 物理学 2025-02-13 Prasanth Shyamsundar

I show that with simple extensions of the shower algorithms in Monte Carlo programs, one can implement NLO corrections to the hardest emission that overcome the problems of negative weighted events found in previous implementations. Simple…

高能物理 - 唯象学 · 物理学 2011-05-05 Paolo Nason

We aim to improve the modelling of deep inelastic scattering by implementing multi-jet merging capabilities in Vincia parton shower in the general-purpose Monte Carlo event generator, Pythia. Merging allows to combine event samples of…

高能物理 - 唯象学 · 物理学 2024-08-16 Joni Laulainen , Ilkka Helenius , Christian T. Preuss

We have developed a Monte Carlo event generator for non-resonant diphoton ($\gamma\gamma$) production at hadron collisions in the framework of GR@PPA, which consistently includes additional one-jet production. The jet-matching method…

高能物理 - 唯象学 · 物理学 2013-05-30 Shigeru Odaka , Yoshimasa Kurihara

The most commonly employed formalisms of radiative energy loss have been derived in the high- energy approximation. In its present form, it is reliable only for the medium modifications of inclusive particle spectra. Modifications to this…

高能物理 - 唯象学 · 物理学 2009-11-18 Nestor Armesto , Leticia Cunqueiro , Carlos A. Salgado

We modify the reweighting factor of the projector used in diffusion Monte Carlo to reduce the time-step error of the total energy. Further, we present a reweighting scheme that has the desirable feature that it is exactly size-consistent,…

化学物理 · 物理学 2024-03-18 Tyler A. Anderson , Manolo C. Per , C. J. Umrigar

We propose a sampling method to include the negative contribution to probability density distribution in a sampling procedure. This sampling method is a universal solution for all negative probability problem and shows extraordinarily power…

仪器与探测器 · 物理学 2015-05-27 Bo Da , Shifeng Mao , ZheJun Ding

Negatively weighted events, which appear in the simulation of particle collisions, significantly increase the computational requirements of collider experiments. A new technique called ARCANE reweighting has been introduced in a companion…

高能物理 - 唯象学 · 物理学 2025-02-13 Prasanth Shyamsundar

The search for the Higgs boson(s) is one of the major priorities at the upgraded Fermilab Tevatron and at the CERN Large Hadron Collider (LHC). Monte Carlo event generators (MCs) are heavily utilized to extract and interpret the Higgs…

高能物理 - 唯象学 · 物理学 2009-10-31 C. Balazs , J. Huston , I. Puljak

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 novel method for the elimination of negative Monte Carlo event weights. The method is process-agnostic, independent of any analysis, and preserves all physical observables. We demonstrate the overall performance and systematic…

高能物理 - 唯象学 · 物理学 2022-06-01 Jeppe R. Andersen , Andreas Maier
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