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Development of systematic uncertainty-aware neural network trainings for binned-likelihood analyses at the LHC

Publication ,  Journal Article
Druzhkin, D; Borshch, V; Babaev, A; Uzunian, A; Slabospitskii, S; Kachanov, V; Skovpen, Y; Radchenko, O; Kozyrev, A; Dimova, T; Blinov, V ...
Published in: European Physical Journal C
November 1, 2025

We propose a neural network training method capable of accounting for the effects of systematic variations of the data model in the training process and describe its extension towards neural network multiclass classification. The procedure is evaluated on the realistic case of the measurement of Higgs boson production via gluon fusion and vector boson fusion in the ττ decay channel at the CMS experiment. The neural network output functions are used to infer the signal strengths for inclusive production of Higgs bosons as well as for their production via gluon fusion and vector boson fusion. We observe improvements of 12 and 16% in the uncertainty in the signal strengths for gluon and vector-boson fusion, respectively, compared with a conventional neural network training based on cross-entropy.

Duke Scholars

Published In

European Physical Journal C

DOI

EISSN

1434-6052

ISSN

1434-6044

Publication Date

November 1, 2025

Volume

85

Issue

11

Related Subject Headings

  • Nuclear & Particles Physics
  • 5107 Particle and high energy physics
  • 5102 Atomic, molecular and optical physics
  • 5101 Astronomical sciences
  • 0206 Quantum Physics
  • 0202 Atomic, Molecular, Nuclear, Particle and Plasma Physics
 

Citation

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Druzhkin, D., Borshch, V., Babaev, A., Uzunian, A., Slabospitskii, S., Kachanov, V., … Galloni, C. (2025). Development of systematic uncertainty-aware neural network trainings for binned-likelihood analyses at the LHC. European Physical Journal C, 85(11). https://doi.org/10.1140/epjc/s10052-025-14713-w
Druzhkin, D., V. Borshch, A. Babaev, A. Uzunian, S. Slabospitskii, V. Kachanov, Y. Skovpen, et al. “Development of systematic uncertainty-aware neural network trainings for binned-likelihood analyses at the LHC.” European Physical Journal C 85, no. 11 (November 1, 2025). https://doi.org/10.1140/epjc/s10052-025-14713-w.
Druzhkin D, Borshch V, Babaev A, Uzunian A, Slabospitskii S, Kachanov V, et al. Development of systematic uncertainty-aware neural network trainings for binned-likelihood analyses at the LHC. European Physical Journal C. 2025 Nov 1;85(11).
Druzhkin, D., et al. “Development of systematic uncertainty-aware neural network trainings for binned-likelihood analyses at the LHC.” European Physical Journal C, vol. 85, no. 11, Nov. 2025. Scopus, doi:10.1140/epjc/s10052-025-14713-w.
Druzhkin D, Borshch V, Babaev A, Uzunian A, Slabospitskii S, Kachanov V, Skovpen Y, Radchenko O, Kozyrev A, Dimova T, Blinov V, Volkov P, Savrin V, Perfilov M, Klyukhin V, Gribushin A, Ershov A, Dudko L, Dubinin M, Bunichev V, Boos E, Terkulov A, Kirakosyan M, Azarkin M, Andreev V, Polikarpov S, Chistov R, Chadeeva M, Zhokin A, Popov V, Lychkovskaya N, Gavrilov V, Ivanov K, Aushev T, Vorobyev A, Uvarov L, Sulimov V, Sosnov D, Oreshkin V, Murzin V, Kim V, Ivanov Y, Golovtcov V, Gavrilov G, Toropin A, Tlisova I, Krasnikov N, Kirsanov M, Kirpichnikov D, Karneyeu A, Golubev N, Gninenko S, Dermenev A, Andreev YU, Zhizhin I, Zarubin A, Yuldashev BS, Voytishin N, Teryaev O, Smirnov V, Shulha S, Shmatov S, Shalaev V, Savina M, Perelygin V, Palichik V, Nikitenko A, Matveev V, Malakhov A, Lanev A, Korenkov V, Kodolova O, Karjavine V, Gorbunov I, Golutvin I, Budkouski D, Alexakhin V, Afanasiev S, Warden A, Vetens W, Tsoi HF, Teague D, Smith WH, Sharma V, Shang V, Savin A, Pinna D, Pétré L, Parida G, Mondal S, Mohammadi A, Mallampalli A, Madhusudanan Sreekala J, Loveless R, Lanaro A, Koraka CK, Herve A, Herndon M, He H, Galloni C. Development of systematic uncertainty-aware neural network trainings for binned-likelihood analyses at the LHC. European Physical Journal C. 2025 Nov 1;85(11).
Journal cover image

Published In

European Physical Journal C

DOI

EISSN

1434-6052

ISSN

1434-6044

Publication Date

November 1, 2025

Volume

85

Issue

11

Related Subject Headings

  • Nuclear & Particles Physics
  • 5107 Particle and high energy physics
  • 5102 Atomic, molecular and optical physics
  • 5101 Astronomical sciences
  • 0206 Quantum Physics
  • 0202 Atomic, Molecular, Nuclear, Particle and Plasma Physics