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

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

PHYSICAL REVIEW LETTERS(2022)

Cited 30|Views41
No score
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.
More
Translated text
Key words
h1 detector,lepton-jet,deep-inelastic
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined