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

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 spe...

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Detalles Bibliográficos
Autores: Aad, Georges, Aakvaag, E., Abbott, B., Abdelhameed, S., Abeling, K., Abicht, N. J., Abidi, S. H., Aboelela, M., Aboulhorma, A., Abramowicz, H., Abreu, H., Abulaiti, Y., Acharya, B. S., Ackermann, A., Adam Bourdarios, C., Adamczyk, L., Addepalli, S. V., Addison, M. J., Adelman, J., Adiguzel, A., Adye, T., Affolder, A. A., Afik, Y., Agaras, M. N., Agarwala, J., Aggarwal, A., Agheorghiesei, C., Ahmadov, F., Ahmed, W. S., Ahuja, S., Ai, X., Aielli, G., Aikot, A., Ait Tamlihat, M., Aitbenchikh, B., Akbiyik, M., Åkesson, T. P.A., Akimov, A. V., Akiyama, D., Akolkar, N. N., Aktas, S., Al Khoury, K., Alberghi, G. L., Albert, J., Albicocco, P., Albouy, G. L., Alderweireldt, S., Alegria, Z. L., Aleksa, M., Aleksandrov, I. N., Alexa, C., Alexopoulos, T., Alfonsi, F., Algren, M., Alhroob, M., Ali, B., Ali, H. M.J., Ali, S., Alibocus, S. W., Aliev, M., Alimonti, G., Alkakhi, W., Allaire, C., Allbrooke, B. M.M., Allen, J. F., Allendes Flores, C. A., Allport, P. P., Aloisio, A., Alonso, F., Alpigiani, C., Alsolami, Z. M.K., Alvarez Estevez, M., Alvarez Fernandez, A., Alves Cardoso, M., Alviggi, M. G., Aly, M., Amaral Coutinho, Y., Ambler, A., Amelung, C., Amerl, M., Ames, C. G., Amidei, D., Amini, B., Amirie, K. J., Amor Dos Santos, S. P., Amos, K. R., An, S., Ananiev, V., Anastopoulos, C., Andeen, T., Anders, J. K., Anderson, A. C., Andrean, S. Y., Andreazza, A., Angelidakis, S., Angerami, A., Anisenkov, A. V., Annovi, A., Antel, C., Antipov, E.
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2024
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/395351
Acceso en línea:http://hdl.handle.net/10261/395351
https://api.elsevier.com/content/abstract/scopus_id/85203423356
Access Level:acceso abierto
Palabra clave:ATLAS
Calibrations
CERN jets
Detector
http://metadata.un.org/sdg/9
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Descripción
Sumario: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.

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