Efficient description of experimental effects in amplitude analyses

Autor:	Mathad, Abhijit, O'Hanlon, Daniel, Poluektov, Anton, Rabadan, Raul
Rok vydání:	2019
Předmět:	Physics - Data Analysis Statistics and Probability High Energy Physics - Experiment
Zdroj:	2021 JINST 16 P06016
Druh dokumentu:	Working Paper
DOI:	10.1088/1748-0221/16/06/P06016
Popis:	Amplitude analysis is a powerful technique to study hadron decays. A significant complication in these analyses is the treatment of instrumental effects, such as background and selection efficiency variations, in the multidimensional kinematic phase space. This paper reviews conventional methods to estimate efficiency and background distributions and outlines the methods of density estimation using Gaussian processes and artificial neural networks. Such techniques see widespread use elsewhere, but have not gained popularity in use for amplitude analyses. Finally, novel applications of these models are proposed, to estimate background density in the signal region from the sidebands in multiple dimensions, and a more general method for model-assisted density estimation using artificial neural networks. Comment: 34 pages, 15 figures, 4 tables. Version submitted to JINST
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1902.01452 Zobrazit plný text záznamu View this record from Arxiv