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A neural network clustering algorithm for the ATLAS silicon pixel detector

Publication ,  Journal Article
Aad, G; Abbott, B; Abdallah, J; Khalek, SA; Abdinov, O; Aben, R; Abi, B; Abolins, M; AbouZeid, OS; Abramowicz, H; Abreu, H; Abreu, R; Adye, T ...
Published in: Journal of Instrumentation
September 1, 2014
Published version (DOI)

A novel technique to identify and split clusters created by multiple charged particles in the ATLAS pixel detector using a set of artificial neural networks is presented. Such merged clusters are a common feature of tracks originating from highly energetic objects, such as jets. Neural networks are trained using Monte Carlo samples produced with a detailed detector simulation. This technique replaces the former clustering approach based on a connected component analysis and charge interpolation. The performance of the neural network splitting technique is quantified using data from proton-proton collisions at the LHC collected by the ATLAS detector in 2011 and from Monte Carlo simulations. This technique reduces the number of clusters shared between tracks in highly energetic jets by up to a factor of three. It also provides more precise position and error estimates of the clusters in both the transverse and longitudinal impact parameter resolution.

Duke Scholars

Ayana T. Arce
Author Ayana T. Arce Physics
Alfred T. Goshaw
Author Alfred T. Goshaw Physics
Ashutosh V. Kotwal
Author Ashutosh V. Kotwal Physics
Mark C. Kruse
Author Mark C. Kruse Physics
Seog Oh
Author Seog Oh Physics
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Published In

Journal of Instrumentation

DOI

10.1088/1748-0221/9/09/P09009

EISSN

1748-0221

Publication Date

September 1, 2014

Volume

9

Issue

9

Related Subject Headings

  • Nuclear & Particles Physics
  • 51 Physical sciences
  • 40 Engineering
  • 09 Engineering
  • 02 Physical Sciences
 

Citation

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Aad, G., Abbott, B., Abdallah, J., Khalek, S. A., Abdinov, O., Aben, R., … Arnal, V. (2014). A neural network clustering algorithm for the ATLAS silicon pixel detector. Journal of Instrumentation, 9(9). https://doi.org/10.1088/1748-0221/9/09/P09009
Aad, G., B. Abbott, J. Abdallah, S. A. Khalek, O. Abdinov, R. Aben, B. Abi, et al. “A neural network clustering algorithm for the ATLAS silicon pixel detector.” Journal of Instrumentation 9, no. 9 (September 1, 2014). https://doi.org/10.1088/1748-0221/9/09/P09009.
Aad G, Abbott B, Abdallah J, Khalek SA, Abdinov O, Aben R, et al. A neural network clustering algorithm for the ATLAS silicon pixel detector. Journal of Instrumentation. 2014 Sep 1;9(9).
Aad, G., et al. “A neural network clustering algorithm for the ATLAS silicon pixel detector.” Journal of Instrumentation, vol. 9, no. 9, Sept. 2014. Scopus, doi:10.1088/1748-0221/9/09/P09009.
Aad G, Abbott B, Abdallah J, Khalek SA, Abdinov O, Aben R, Abi B, Abolins M, AbouZeid OS, Abramowicz H, Abreu H, Abreu R, Abulaiti Y, Acharya BS, Adamczyka L, Adams DL, Adelman J, Adomeit S, Adye T, Agatonovic-Jovin T, Aguilar-Saavedra JA, Agustoni M, Ahlen SP, Ahmadov F, Aielli G, Akerstedt H, Åkesson TPA, Akimoto G, Akimov AV, Alberghi GL, Albert J, Albrand S, Verzini MJA, Aleksa M, Aleksandrov IN, Alexa C, Alexander G, Alexandre G, Alexopoulos T, Alhroob M, Alimonti G, Alio L, Alison J, Allbrooke BMM, Allison LJ, Allport PP, Almond J, Aloisio A, Alonso A, Alonso F, Alpigiani C, Altheimer A, Gonzalez BA, Alviggi MG, Amako K, Coutinho YA, Amelung C, Amidei D, Amor Dos Santos SP, Amorim A, Amoroso S, Amram N, Amundsen G, Anastopoulos C, Ancu LS, Andari N, Andeen T, Anders CF, Anders G, Anderson KJ, Andreazza A, Andrei V, Anduaga XS, Angelidakis S, Angelozzi I, Anger P, Angerami A, Anghinolfi F, Anisenkov AV, Anjos N, Annovi A, Antonaki A, Antonelli M, Antonov A, Antos J, Anulli F, Aoki M, Bella LA, Apolle R, Arabidze G, Aracena I, Arai Y, Araquea JP, Arce ATH, Arguin JF, Argyropoulos S, Arik M, Armbruster AJ, Arnaez O, Arnal V. A neural network clustering algorithm for the ATLAS silicon pixel detector. Journal of Instrumentation. 2014 Sep 1;9(9).
Journal cover image

Published In

Journal of Instrumentation

DOI

10.1088/1748-0221/9/09/P09009

EISSN

1748-0221

Publication Date

September 1, 2014

Volume

9

Issue

9

Related Subject Headings

  • Nuclear & Particles Physics
  • 51 Physical sciences
  • 40 Engineering
  • 09 Engineering
  • 02 Physical Sciences