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

The ATLAS Collaboration

研究成果: ジャーナルへの寄稿記事

1 引用 (Scopus)

抄録

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. As an example, results are shown for 3.2 fb- 1 of proton–proton collision data at a centre-of-mass energy of 13 TeV collected with the ATLAS detector at the LHC in 2015, in which more than 700 event classes and more than 10 5 regions have been analysed. No significant deviations are found and consequently no data-derived signal regions for a follow-up analysis have been defined.

元の言語英語
記事番号120
ジャーナルEuropean Physical Journal C
79
発行部数2
DOI
出版物ステータス出版済み - 2 1 2019

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Physics
deviation
physics
Experiments
Detectors
center of mass
indication
collisions
sensitivity
detectors
energy

All Science Journal Classification (ASJC) codes

  • Engineering (miscellaneous)
  • Physics and Astronomy (miscellaneous)

これを引用

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

:: European Physical Journal C, 巻 79, 番号 2, 120, 01.02.2019.

研究成果: ジャーナルへの寄稿記事

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title = "A strategy for a general search for new phenomena using data-derived signal regions and its application within the ATLAS experiment",
abstract = "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. As an example, results are shown for 3.2 fb- 1 of proton–proton collision data at a centre-of-mass energy of 13 TeV collected with the ATLAS detector at the LHC in 2015, in which more than 700 event classes and more than 10 5 regions have been analysed. No significant deviations are found and consequently no data-derived signal regions for a follow-up analysis have been defined.",
author = "{The ATLAS Collaboration} and M. Aaboud and G. Aad and B. Abbott and O. Abdinov and B. Abeloos and Abhayasinghe, {D. K.} and Abidi, {S. H.} and Abouzeid, {O. S.} and Abraham, {N. L.} and H. Abramowicz and H. Abreu and Y. Abulaiti and Acharya, {B. S.} and S. Adachi and L. Adam and L. Adamczyk and J. Adelman and M. Adersberger and A. Adiguzel and T. Adye and Affolder, {A. A.} and Y. Afik and C. Agheorghiesei and Aguilar-Saavedra, {J. A.} and F. Ahmadov and G. Aielli and S. Akatsuka and {\AA}kesson, {T. P.A.} and E. Akilli and Akimov, {A. V.} and Alberghi, {G. L.} and J. Albert and P. Albicocco and {Alconada Verzini}, {M. J.} and S. Alderweireldt and M. Aleksa and Aleksandrov, {I. N.} and C. Alexa and T. Alexopoulos and M. Alhroob and B. Ali and G. Alimonti and J. Alison and Alkire, {S. P.} and C. Allaire and Allbrooke, {B. M.M.} and Allen, {B. W.} and Allport, {P. P.} and A. Aloisio and Kiyotomo Kawagoe",
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AU - Allaire, C.

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AB - 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. As an example, results are shown for 3.2 fb- 1 of proton–proton collision data at a centre-of-mass energy of 13 TeV collected with the ATLAS detector at the LHC in 2015, in which more than 700 event classes and more than 10 5 regions have been analysed. No significant deviations are found and consequently no data-derived signal regions for a follow-up analysis have been defined.

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