CERN Accelerating science

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Report number arXiv:2203.13923 ; Edinburgh 2022/08 ; FERMILAB-PUB-22-222-QIS-SCD-T ; MPP-2022-32, SLAC-PUB-17652 ; SMU-HEP-22-02 ; TIF-UNIMI-2022-6
Title Snowmass 2021 whitepaper: Proton structure at the precision frontier
Author(s) Amoroso, S. (DESY) ; Apyan, A. (Brandeis U.) ; Armesto, N. (Santiago de Compostela U., IGFAE) ; Ball, R.D. (U. Edinburgh, Higgs Ctr. Theor. Phys.) ; Bertone, V. (IRFU, Saclay) ; Bissolotti, C. (Argonne) ; Bluemlein, J. (DESY) ; Boughezal, R. (Argonne) ; Bozzi, G. (Cagliari U. ; INFN, Cagliari) ; Britzger, D. (Munich, Max Planck Inst.) ; Buckley, A. (Glasgow U.) ; Candido, A. (Milan U. ; INFN, Milan) ; Carrazza, S. (Milan U. ; INFN, Milan) ; Celiberto, F.G. (ECT, Trento ; FBK, CIT, Trento ; TIFPA-INFN, Trento) ; Cerci, S. (Adiyaman U.) ; Chachamis, G. (LIP, Lisbon) ; Cooper-Sarkar, A.M. (Oxford U.) ; Courtoy, A. (Mexico U.) ; Cridge, T. (U. Coll. London) ; Cruz-Martinez, J.M. (Milan U. ; INFN, Milan) ; Giuli, F. (CERN) ; Guzzi, M.G. (Kennesaw State U.) ; Gwenlan, C. (Oxford U.) ; Harland-Lang, L.A. (Oxford U., Theor. Phys.) ; Hekhorn, F. (Milan U. ; INFN, Milan) ; Hentschinski, M. ; Hobbs, T.J. (Fermilab ; IIT, Chicago) ; Hoeche, S. (Fermilab) ; Huss, A. (CERN) ; Huston, J. (Michigan State U.) ; Jadach, S. ; Jalilian-Marian, J. (Baruch Coll.) ; Klein, M. (Liverpool U.) ; Krintiras, G.K. (Kansas U.) ; Lin, H.-W. (Michigan State U.) ; Loizides, C. (ORNL, Oak Ridge (main)) ; Magni, G. (Vrije U., Amsterdam ; Nikhef, Amsterdam) ; Malaescu, B. (LPNHE, Paris) ; Mistlberger, B. (SLAC) ; Moch, S. (Hamburg U., Inst. Theor. Phys. II) ; Nadolsky, P.M. (Southern Methodist U.) ; Nocera, E.R. (U. Edinburgh, Higgs Ctr. Theor. Phys.) ; Olness, F.I. (Southern Methodist U.) ; Petriello, F. (Northwestern U. ; Argonne) ; Pires, J. (LIP, Lisbon ; Lisbon U.) ; Rabbertz, K. (KIT, Karlsruhe) ; Rojo, J. (Vrije U., Amsterdam ; Nikhef, Amsterdam) ; Royon, C. ; Schnell, G. (Basque U., Bilbao ; IKERBASQUE, Bilbao) ; Schwan, C. (Wurzburg U.) ; Siodmok, A. (Jagiellonian U.) ; Soper, D.E. (Oregon U.) ; Sutton, M. (Sussex U.) ; Thorne, R.S. (University Coll. London) ; Ubiali, M. (Cambridge U., DAMTP) ; Vita, G. (SLAC) ; Weber, J.H. (Humboldt U., Berlin) ; Whitehead, J. ; Xie, K. (Pittsburgh U.) ; Yuan, C.-P. (Michigan State U.) ; Zhou, B. (Johns Hopkins U.)
Publication 2023-01-17
Imprint 2022-03-25
Number of pages 79
Note 83 pages, 27 figures, contribution to Snowmass 2021; v.3: journal version
In: 2021 Snowmass Summer Study, Seattle, WA, United States, 11 - 20 July 2021, pp.
DOI 10.5506/APhysPolB.53.12-A1
Subject category hep-ex ; Particle Physics - Experiment ; hep-ph ; Particle Physics - Phenomenology
Abstract An overwhelming number of theoretical predictions for hadron colliders require parton distribution functions (PDFs), which are an important ingredient of theory infrastructure for the next generation of high-energy experiments. This whitepaper summarizes the status and future prospects for determination of high-precision PDFs applicable in a wide range of energies and experiments, in particular in precision tests of the Standard Model and in new physics searches at the high-luminosity Large Hadron Collider and Electron-Ion Collider. We discuss the envisioned advancements in experimental measurements, QCD theory, global analysis methodology, and computing that are necessary to bring unpolarized PDFs in the nucleon to the N2LO and N3LO accuracy in the QCD coupling strength. Special attention is given to the new tasks that emerge in the era of the precision PDF analysis, such as those focusing on the robust control of systematic factors both in experimental measurements and theoretical computations. Various synergies between experimental and theoretical studies of the hadron structure are explored, including opportunities for studying PDFs for nuclear and meson targets, PDFs with electroweak contributions or dependence on the transverse momentum, for incisive comparisons between phenomenological models for the PDFs and computations on discrete lattice, and for cross-fertilization with machine learning/AI approaches. [Submitted to the US Community Study on the Future of Particle Physics (Snowmass 2021).]
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