Unbinned Deep Learning Jet Substructure Measurement in High $Q^2$ ep collisions at HERA

Andreev, V.; Hessler, J.; Vallée, C.; Daum, K.; Gouzevitch, M.; Baghdasaryan, A.; Britzger, D.; Patel, G. D.; Traynor, D.; Chekelian, V.; Žlebčík, R.; H1 Collaboration; Laycock, P.; Mehta, A.; Egli, S.; Picuric, I.; Wünsch, E.; Park, S.; Olsson, J. E.; Schmookler, B. A.; Maxfield, S. J.; Baty, A.; Hreus, T.; Tustin, G.; Sun, C.; Huber, F.; Kapichine, M.; Schöning, A.; Lipka, K.; Spaskov, V.; Valkárová, A.; Petrukhin, A.; Zohrabyan, H.; Acosta, F. Torales; Favart, L.; Henderson, R. C. W.; Li, W.; Katzy, J.; Rizvi, E.; Van Mechelen, P.; Campbell, A. J.; Drees, A.; Polifka, R.; Jacquet, M.; Fleischer, M.; Malinovski, E.; Lobodzinski, B.; Hoffmann, D.; Martyn, H.-U.; Steder, M.; Eckerlin, G.; Contreras, J. G.; Roosen, R.; Krücker, D.; Begzsuren, K.; Nachman, B.; Mikuni, V. M.; Wegener, D.; Elsen, E.; Janssen, T.; Sauvan, E.; Perez, E.; Tu, Z.; Gayler, J.; Kleinwort, C.; Arratia, M.; Ravdandorj, T.; Jung, A. W.; Newman, P. R.; Lin, J.; Goerlich, L.; Feltesse, J.; Brandt, G.; Shushkevich, S.; Fomenko, A.; Hladký, J.; Pitzl, D.; Lee, S. H.; Krüger, K.; List, B.; Jacobs, P. M.; Bolz, A.; Meyer, J.; Mondal, M. M.; Radescu, V.; Gal, C.; Levonian, S.; List, J.; Grindhammer, G.; Cunqueiro Mendez, L.; Thompson, P. D.; Greenshaw, T.; Tseepeldorj, B.; Buniatyan, A.; Kostka, P.; Reimer, P.; Kretzschmar, J.; Chen, Z.; Soloviev, Y.; Zhang, Z.; Diaconu, C.; Cerny, Karel; Nowak, G.; Sankey, D. P. C.; Schmitt, Stefan; Klest, H. T.; Ozerov, D.; Müller, K.; Sykora, T.; Boudry, V.; Morozov, A.; Raicevic, N.; Landon, M. P. J.; Žáček, J.; Preins, S.; Rostovtsev, A.; Dainton, J. B.; Straumann, U.; Pascaud, C.; Fedotov, A.; Schoeffel, L.; Sauter, M.; Gogitidze, N.; South, D.; Grab, C.; Bystritskaya, L.; Long, O. R.; Mikocki, S.; Naumann, Th.; Schnell, G.; Zhang, J.; Kogler, R.; Zomer, F.; Cvach, J.; Sopicki, P.; Meyer, A. B.; Haidt, D.; Lange, W.; Deshpande, A.; Sefkow, F.; Horisberger, R.; Stella, B.; Rotaru, M.; Cantun Avila, K. B.; Klein, M.; Niebuhr, C.; Specka, A.; Kiesling, C.; Robmann, P.

doi:10.1016/j.physletb.2023.138101

Journal Article

PUBDB-2023-07051

Unbinned Deep Learning Jet Substructure Measurement in High $Q^2$ ep collisions at HERA

Andreev, V. ; Arratia, M. ; Baghdasaryan, A. ; Baty, A. ; Begzsuren, K. ; Bolz, A. ; Boudry, V. ; Brandt, G. ; Britzger, D. ; Buniatyan, A. ; Bystritskaya, L. ; Campbell, A. J. ; Cantun Avila, K. B. ; Cerny, K.Extern* ; Chekelian, V. ; Chen, Z. ; Contreras, J. G. ; Cunqueiro Mendez, L. ; Cvach, J. ; Dainton, J. B. ; Daum, K. ; Deshpande, A.Extern* ; Diaconu, C. ; Drees, A. ; Eckerlin, G. ; Egli, S. ; Elsen, E. ; Favart, L. ; Fedotov, A. ; Feltesse, J. ; Fleischer, M. ; Fomenko, A. ; Gal, C. ; Gayler, J. ; Goerlich, L. ; Gogitidze, N. ; Gouzevitch, M. ; Grab, C. ; Greenshaw, T. ; Grindhammer, G. ; Haidt, D. ; Henderson, R. C. W.Extern* ; Hessler, J. ; Hladký, J. ; Hoffmann, D. ; Horisberger, R. ; Hreus, T. ; Huber, F. ; Jacobs, P. M. ; Jacquet, M. ; Janssen, T. ; Jung, A. W. ; Kapichine, M. ; Katzy, J. ; Kiesling, C. ; Klein, M. ; Kleinwort, C. ; Klest, H. T. ; Kogler, R. ; Kostka, P. ; Kretzschmar, J. ; Krücker, D. ; Krüger, K. ; Landon, M. P. J. ; Lange, W. ; Laycock, P. ; Lee, S. H.Extern* ; Levonian, S. ; Li, W. ; Lin, J. ; Lipka, K. ; List, B. ; List, J. ; Lobodzinski, B. ; Long, O. R. ; Malinovski, E. ; Martyn, H.-U. ; Maxfield, S. J. ; Mehta, A. ; Meyer, A. B. ; Meyer, J. ; Mikocki, S. ; Mikuni, V. M. ; Mondal, M. M. ; Morozov, A. ; Müller, K. ; Nachman, B. ; Naumann, T. ; Newman, P. R. ; Niebuhr, C. ; Nowak, G. ; Olsson, J. E. ; Ozerov, D. ; Park, S. ; Pascaud, C. ; Patel, G. D. ; Perez, E.Extern* ; Petrukhin, A. ; Picuric, I. ; Pitzl, D. ; Polifka, R. ; Preins, S. ; Radescu, V. ; Raicevic, N. ; Ravdandorj, T. ; Reimer, P. ; Rizvi, E. ; Robmann, P. ; Roosen, R. ; Rostovtsev, A. ; Rotaru, M. ; Sankey, D. P. C. ; Sauter, M. ; Sauvan, E. ; Schmitt, S. (Corresponding author)DESY* ; Schmookler, B. A. ; Schnell, G. ; Schoeffel, L. ; Schöning, A. ; Sefkow, F.DESY* ; Shushkevich, S. ; Soloviev, Y. ; Sopicki, P. ; South, D. ; Spaskov, V. ; Specka, A. ; Steder, M. ; Stella, B. ; Straumann, U. ; Sun, C. ; Sykora, T.Extern* ; Thompson, P. D. ; Acosta, F. T. ; Traynor, D. ; Tseepeldorj, B. ; Tu, Z. ; Tustin, G. ; Valkárová, A. ; Vallée, C. ; Van Mechelen, P. ; Wegener, D. ; Wünsch, E. ; Žáček, J. ; Zhang, J. ; Zhang, Z. ; Žlebčík, R. ; Zohrabyan, H. ; Zomer, F. ; H1 Collaboration (Collaboration author)DESY*

2023
North-Holland Publ. Amsterdam

Physics letters / B 844, 138101 (2023) [10.1016/j.physletb.2023.138101]

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Please use a persistent id in citations: doi:10.1016/j.physletb.2023.138101

Report No.: DESY-23-034; arXiv:2303.13620

Abstract: The radiation pattern within high energy quark- and gluon-initiated jets (jet substructure) is used extensively as a precision probe of the strong force as well as an environment for optimizing event generators with numerous applications in high energy particle and nuclear physics. Looking at electron-proton collisions is of particular interest as many of the complications present at hadron colliders are absent. A detailed study of modern jet substructure observables, jet angularities, in electron-proton collisions is presented using data recorded using the H1 detector at HERA. The measurement is unbinned and multi-dimensional, using machine learning to correct for detector effects. All of the available reconstructed object information of the respective jets is interpreted by a graph neural network, achieving superior precision on a selected set of jet angularities. Training these networks was enabled by the use of a large number of GPUs in the Perlmutter supercomputer at Berkeley Lab. The particle jets are reconstructed in the laboratory frame, using the $k_{\mathrm{T}}$ jet clustering algorithm. Results are reported at high transverse momentum transfer $Q^2>150$ GeV${}^2$, and inelasticity $0.2 < y < 0.7$. The analysis is also performed in sub-regions of $Q^2$, thus probing scale dependencies of the substructure variables. The data are compared with a variety of predictions and point towards possible improvements of such models.

Keyword(s): electron p: deep inelastic scattering ; energy: high ; electron p: interaction ; particle: energy ; transverse momentum: high ; structure ; DESY HERA Stor ; H1 ; nuclear physics ; quark: jet ; gluon: jet ; higher-dimensional ; Berkeley Lab ; machine learning ; momentum transfer ; network ; neural network ; strong coupling ; track data analysis: jet ; data analysis method ; numerical calculations: Monte Carlo ; experimental results

Classification:

ddc:530

Note: 30 pages, 10 figures, 8 tables, corrected authorlist

Contributing Institute(s):

H1 Kollaboration (H1)

Research Program(s):

611 - Fundamental Particles and Forces (POF4-611) (POF4-611)

Experiment(s):

HERA: H1

Appears in the scientific report 2023

Database coverage:
Medline

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