The automated Matrix-Element reweighting and its applications at the LHC

15th International Workshop on Advanced Computing and Analysis Techniques in Physics Research

物理学;计算机科学

Mertens, Alexandre^1

Centre for Cosmology, Particle Physics and Phenomenology (CP3), Université Catholique de Louvain, Chemin du Cyclotron 2, B-1348 Louvain-la-Neuve, Belgium^1

关键词: Background discrimination;    Computing resource;    Differential spectra;    Large-scale deployment;    Multi variate analysis;    Numerical estimation;    Theoretical points;    Top mass measurement;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/523/1/012028/pdf
DOI  :  10.1088/1742-6596/523/1/012028

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

Given a sample of experimental events and a set of theoretical models, the matrix element method (MEM) is a procedure to select the most plausible model that governs the production of these events. From a theoretical point of view, it is probably the most powerful multi-variate analysis technique since it maximally uses the information contained in the Feynman amplitudes. This technique is now widely known since it has been used for the precision top mass measurement at Tevatron, for example. The MadWeight software is presented. MadWeight is a phase-space generator designed for the automated numerical estimation of matrix elements based on MadGraph amplitudes. With the modern computing resources, it allows the large-scale deployment of the MEM technique on high-statistics data and simulated samples. Several applications of the method at LHC are discussed, including the measurement of the spin and parity of the recently discovered boson, signal-to-background discrimination, full differential spectrum estimation and other promising applications.