Measurement of Lepton-Jet Correlation in Deep-Inelastic Scattering with the H1 Detector Using Machine Learning for Unfolding

(H1 Collaboration)

doi:10.1103/PhysRevLett.128.132002

Measurement of Lepton-Jet Correlation in Deep-Inelastic Scattering with the H1 Detector Using Machine Learning for Unfolding

(H1 Collaboration)

Physics and Astronomy

P.N. Lebedev Physical Institute of the Russian Academy of Sciences
University of California at Riverside
A. Alikhanian Yerevan Institute of Physics
Rice University
Mongolian Academy of Sciences
German Electron Synchrotron
CNRS-IN2P3
University of Göttingen
Max Planck Institute for Physics (Werner Heisenberg Institute)
University of Birmingham
Alikhanov Institute for Theoretical and Experimental Physics
Centro de Investigacion y de Estudios Avanzados del Instituto Politécnico Nacional
Palacký University Olomouc
Shandong University
Oak Ridge National Laboratory
Czech Academy of Sciences
University of Liverpool
University of Wuppertal
Aix-Marseille Université
Paul Scherrer Institute
Université libre de Bruxelles
Centre d'Etudes de Saclay
Stony Brook University
Institute of Nuclear Physics
Universite Claude Bernard Lyon 1
Swiss Federal Institute of Technology Zurich
Lancaster University
University of Zurich
Heidelberg University
Lawrence Berkeley National Laboratory
Université Paris-Saclay

Research output: Contribution to journal › Article › peer-review

52 Scopus citations

Abstract

The first measurement of lepton-jet momentum imbalance and azimuthal correlation in lepton-proton scattering at high momentum transfer is presented. These data, taken with the H1 detector at HERA, are corrected for detector effects using an unbinned machine learning algorithm (multifold), which considers eight observables simultaneously in this first application. The unfolded cross sections are compared with calculations performed within the context of collinear or transverse-momentum-dependent factorization in quantum chromodynamics as well as Monte Carlo event generators.

Original language	English
Article number	132002
Journal	Physical Review Letters
Volume	128
Issue number	13
DOIs	https://doi.org/10.1103/PhysRevLett.128.132002
State	Published - Apr 1 2022

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10.1103/PhysRevLett.128.132002

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title = "Measurement of Lepton-Jet Correlation in Deep-Inelastic Scattering with the H1 Detector Using Machine Learning for Unfolding",

abstract = "The first measurement of lepton-jet momentum imbalance and azimuthal correlation in lepton-proton scattering at high momentum transfer is presented. These data, taken with the H1 detector at HERA, are corrected for detector effects using an unbinned machine learning algorithm (multifold), which considers eight observables simultaneously in this first application. The unfolded cross sections are compared with calculations performed within the context of collinear or transverse-momentum-dependent factorization in quantum chromodynamics as well as Monte Carlo event generators.",

author = "\{(H1 Collaboration)\} and V. Andreev and M. Arratia and A. Baghdasaryan and A. Baty and K. Begzsuren and A. Belousov and A. Bolz and V. Boudry and G. Brandt and D. Britzger and A. Buniatyan and L. Bystritskaya and Campbell, \{A. J.\} and \{Cantun Avila\}, \{K. B.\} and K. Cerny and V. Chekelian and Z. Chen and Contreras, \{J. G.\} and \{Cunqueiro Mendez\}, L. and J. Cvach and Dainton, \{J. B.\} and K. Daum and A. Deshpande and C. Diaconu and G. Eckerlin and S. Egli and E. Elsen and L. Favart and A. Fedotov and J. Feltesse and M. Fleischer and A. Fomenko and C. Gal and J. Gayler and L. Goerlich and N. Gogitidze and M. Gouzevitch and C. Grab and T. Greenshaw and G. Grindhammer and D. Haidt and Henderson, \{R. C.W.\} and J. Hessler and J. Hladk{\'y} and D. Hoffmann and R. Horisberger and T. Hreus and F. Huber and Jacobs, \{P. M.\} and M. Jacquet",

note = "Publisher Copyright: {\textcopyright} 2022 authors. Published by the American Physical Society.",

year = "2022",

month = apr,

day = "1",

doi = "10.1103/PhysRevLett.128.132002",

language = "English",

volume = "128",

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T1 - Measurement of Lepton-Jet Correlation in Deep-Inelastic Scattering with the H1 Detector Using Machine Learning for Unfolding

AU - (H1 Collaboration)

AU - Andreev, V.

AU - Arratia, M.

AU - Baghdasaryan, A.

AU - Baty, A.

AU - Begzsuren, K.

AU - Belousov, A.

AU - Bolz, A.

AU - Boudry, V.

AU - Brandt, G.

AU - Britzger, D.

AU - Buniatyan, A.

AU - Bystritskaya, L.

AU - Campbell, A. J.

AU - Cantun Avila, K. B.

AU - Cerny, K.

AU - Chekelian, V.

AU - Chen, Z.

AU - Contreras, J. G.

AU - Cunqueiro Mendez, L.

AU - Cvach, J.

AU - Dainton, J. B.

AU - Daum, K.

AU - Deshpande, A.

AU - Diaconu, C.

AU - Eckerlin, G.

AU - Egli, S.

AU - Elsen, E.

AU - Favart, L.

AU - Fedotov, A.

AU - Feltesse, J.

AU - Fleischer, M.

AU - Fomenko, A.

AU - Gal, C.

AU - Gayler, J.

AU - Goerlich, L.

AU - Gogitidze, N.

AU - Gouzevitch, M.

AU - Grab, C.

AU - Greenshaw, T.

AU - Grindhammer, G.

AU - Haidt, D.

AU - Henderson, R. C.W.

AU - Hessler, J.

AU - Hladký, J.

AU - Hoffmann, D.

AU - Horisberger, R.

AU - Hreus, T.

AU - Huber, F.

AU - Jacobs, P. M.

AU - Jacquet, M.

PY - 2022/4/1

Y1 - 2022/4/1

N2 - The first measurement of lepton-jet momentum imbalance and azimuthal correlation in lepton-proton scattering at high momentum transfer is presented. These data, taken with the H1 detector at HERA, are corrected for detector effects using an unbinned machine learning algorithm (multifold), which considers eight observables simultaneously in this first application. The unfolded cross sections are compared with calculations performed within the context of collinear or transverse-momentum-dependent factorization in quantum chromodynamics as well as Monte Carlo event generators.

AB - The first measurement of lepton-jet momentum imbalance and azimuthal correlation in lepton-proton scattering at high momentum transfer is presented. These data, taken with the H1 detector at HERA, are corrected for detector effects using an unbinned machine learning algorithm (multifold), which considers eight observables simultaneously in this first application. The unfolded cross sections are compared with calculations performed within the context of collinear or transverse-momentum-dependent factorization in quantum chromodynamics as well as Monte Carlo event generators.

UR - https://www.scopus.com/pages/publications/85127922635

U2 - 10.1103/PhysRevLett.128.132002

DO - 10.1103/PhysRevLett.128.132002

M3 - Article

C2 - 35426724

AN - SCOPUS:85127922635

SN - 0031-9007

VL - 128

JO - Physical Review Letters

JF - Physical Review Letters

IS - 13

M1 - 132002

ER -

Measurement of Lepton-Jet Correlation in Deep-Inelastic Scattering with the H1 Detector Using Machine Learning for Unfolding

Abstract

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