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Simultaneous energy and mass calibration of large-radius jets with the ATLAS detector using a deep neural network

Journal articles  - Journal Article
Aad, G; Aakvaag, E; Abbott, B; Abdelhameed, S; Abeling, K; Abicht, NJ; Abidi, SH; Aboelela, M; Aboulhorma, A; Abramowicz, H; Abreu, H; Adye, T ...
Published in: Machine Learning Science and Technology
September 1, 2024
Published version (DOI)

The energy and mass measurements of jets are crucial tasks for the Large Hadron Collider experiments. This paper presents a new calibration method to simultaneously calibrate these quantities for large-radius jets measured with the ATLAS detector using a deep neural network (DNN). To address the specificities of the calibration problem, special loss functions and training procedures are employed, and a complex network architecture, which includes feature annotation and residual connection layers, is used. The DNN-based calibration is compared to the standard numerical approach in an extensive series of tests. The DNN approach is found to perform significantly better in almost all of the tests and over most of the relevant kinematic phase space. In particular, it consistently improves the energy and mass resolutions, with a 30% better energy resolution obtained for transverse momenta pT > 500 GeV.

Duke Scholars

Ashutosh V. Kotwal
Author Ashutosh V. Kotwal Physics
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Published In

Machine Learning Science and Technology

DOI

10.1088/2632-2153/ad611e

EISSN

2632-2153

Publication Date

September 1, 2024

Volume

5

Issue

3

Related Subject Headings

  • 4611 Machine learning
  • 4601 Applied computing
 

Citation

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Aad, G., Aakvaag, E., Abbott, B., Abdelhameed, S., Abeling, K., Abicht, N. J., … Antipov, E. (2024). Simultaneous energy and mass calibration of large-radius jets with the ATLAS detector using a deep neural network. Machine Learning Science and Technology, 5(3). https://doi.org/10.1088/2632-2153/ad611e
Aad, G., E. Aakvaag, B. Abbott, S. Abdelhameed, K. Abeling, N. J. Abicht, S. H. Abidi, et al. “Simultaneous energy and mass calibration of large-radius jets with the ATLAS detector using a deep neural network.” Machine Learning Science and Technology 5, no. 3 (September 1, 2024). https://doi.org/10.1088/2632-2153/ad611e.
Aad G, Aakvaag E, Abbott B, Abdelhameed S, Abeling K, Abicht NJ, et al. Simultaneous energy and mass calibration of large-radius jets with the ATLAS detector using a deep neural network. Machine Learning Science and Technology. 2024 Sep 1;5(3).
Aad, G., et al. “Simultaneous energy and mass calibration of large-radius jets with the ATLAS detector using a deep neural network.” Machine Learning Science and Technology, vol. 5, no. 3, Sept. 2024. Scopus, doi:10.1088/2632-2153/ad611e.
Aad G, Aakvaag E, Abbott B, Abdelhameed S, Abeling K, Abicht NJ, Abidi SH, Aboelela M, Aboulhorma A, Abramowicz H, Abreu H, Abulaiti Y, Acharya BS, Ackermann A, Adam Bourdarios C, Adamczyk L, Addepalli SV, Addison MJ, Adelman J, Adiguzel A, Adye T, Affolder AA, Afik Y, Agaras MN, Agarwala J, Aggarwal A, Agheorghiesei C, Ahmadov F, Ahmed WS, Ahuja S, Ai X, Aielli G, Aikot A, Ait Tamlihat M, Aitbenchikh B, Akbiyik M, Åkesson TPA, Akimov AV, Akiyama D, Akolkar NN, Aktas S, Al Khoury K, Alberghi GL, Albert J, Albicocco P, Albouy GL, Alderweireldt S, Alegria ZL, Aleksa M, Aleksandrov IN, Alexa C, Alexopoulos T, Alfonsi F, Algren M, Alhroob M, Ali B, Ali HMJ, Ali S, Alibocus SW, Aliev M, Alimonti G, Alkakhi W, Allaire C, Allbrooke BMM, Allen JF, Allendes Flores CA, Allport PP, Aloisio A, Alonso F, Alpigiani C, Alsolami ZMK, Alvarez Estevez M, Alvarez Fernandez A, Alves Cardoso M, Alviggi MG, Aly M, Amaral Coutinho Y, Ambler A, Amelung C, Amerl M, Ames CG, Amidei D, Amini B, Amirie KJ, Amor Dos Santos SP, Amos KR, An S, Ananiev V, Anastopoulos C, Andeen T, Anders JK, Anderson AC, Andrean SY, Andreazza A, Angelidakis S, Angerami A, Anisenkov AV, Annovi A, Antel C, Antipov E. Simultaneous energy and mass calibration of large-radius jets with the ATLAS detector using a deep neural network. Machine Learning Science and Technology. 2024 Sep 1;5(3).

Published In

Machine Learning Science and Technology

DOI

10.1088/2632-2153/ad611e

EISSN

2632-2153

Publication Date

September 1, 2024

Volume

5

Issue

3

Related Subject Headings

  • 4611 Machine learning
  • 4601 Applied computing