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Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
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 - 2022/3/31
Y1 - 2022/3/31
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.
U2 - 10.1103/PhysRevLett.128.132002
DO - 10.1103/PhysRevLett.128.132002
M3 - Journal article
VL - 128
JO - Physical review letters
JF - Physical review letters
SN - 1079-7114
IS - 13
M1 - 132002
ER -