Author:
Dorigo Tommaso,Fumanelli Martina,Maccani Chiara,Mojsovska Marija,Strong Giles C.,Scarpa Bruno
Abstract
Abstract
The unsupervised search for overdense regions in high-dimensional feature spaces, where locally high population densities may be associated with anomalous contaminations to an otherwise more uniform population, is of relevance to applications ranging from fundamental research to industrial use cases. Motivated by the specific needs of searches for new phenomena in particle collisions, we propose a novel approach that targets signals of interest populating compact regions of the feature space. The method consists in a systematic scan of subspaces of a standardized copula of the feature space, where the minimum p-value of a hypothesis test of local uniformity is sought by greedy descent. We characterize the performance of the proposed algorithm and show its effectiveness in several experimental situations.
Publisher
Springer Science and Business Media LLC
Subject
Nuclear and High Energy Physics
Reference57 articles.
1. https://www.merriam-webster.com/dictionary/anomaly.
2. CMS collaboration, The CMS Experiment at the CERN LHC, 2008 JINST 3 S08004 [INSPIRE].
3. ATLAS collaboration, The ATLAS Experiment at the CERN Large Hadron Collider, 2008 JINST 3 S08003 [INSPIRE].
4. S.L. Glashow, Partial Symmetries of Weak Interactions, Nucl. Phys. 22 (1961) 579 [INSPIRE].
5. S. Weinberg, A Model of Leptons, Phys. Rev. Lett. 19 (1967) 1264 [INSPIRE].
Cited by
6 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献