A strategy for a general search for new phenomena using data-derived signal regions and its application within the ATLAS experiment

0521011 - FZÚ 2020 RIV DE eng J - Journal Article
Aaboud, M. - Aad, G. - Abbott, B. - Chudoba, Jiří - Hejbal, Jiří - Hladík, Ondřej - Jačka, Petr - Jakoubek, Tomáš - Kepka, Oldřich - Kroll, Jiří - Kupčo, Alexander - Lokajíček, Miloš - Lysák, Roman - Marčišovský, Michal - Mikeštíková, Marcela - Němeček, Stanislav - Penc, Ondřej - Šícho, Petr - Staroba, Pavel - Svatoš, Michal - Taševský, Marek … Total 2891 authors
A strategy for a general search for new phenomena using data-derived signal regions and its application within the ATLAS experiment.
European Physical Journal C. Roč. 79, č. 2 (2019), s. 1-45, č. článku 120. ISSN 1434-6044. E-ISSN 1434-6052
Research Infrastructure: CERN-CZ - 90058
Institutional support: RVO:68378271
Keywords : ATLAS * CERN LHC Coll * numerical calculations: Monte Carlo * sensitivity * statistica * background * benchmark
OECD category: Particles and field physics
Impact factor: 4.389, year: 2019
Method of publishing: Open access

This paper describes a strategy for a general search used by the ATLAS Collaboration to find potential indications of new physics. Events are classified according to their final state into many event classes. For each event class an automated search algorithm tests whether the data are compatible with the Monte Carlo simulated expectation in several distributions sensitive to the effects of new physics. The significance of a deviation is quantified using pseudo-experiments. A data selection with a significant deviation defines a signal region for a dedicated follow-up analysis with an improved background expectation. The analysis of the data-derived signal regions on a new dataset allows a statistical interpretation without the large look-elsewhere effect. The sensitivity of the approach is discussed using Standard Model processes and benchmark signals of new physics.

Permanent Link: http://hdl.handle.net/11104/0305667