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CERN Accelerating science

Article
Report number arXiv:2211.10447
Title Theory pipeline for PDF fitting
Author(s) Barontini, Andrea (Milan U. ; INFN, Milan) ; Candido, Alessandro (Milan U. ; INFN, Milan) ; Cruz-Martinez, Juan (Milan U. ; INFN, Milan ; CERN) ; Hekhorn, Felix (Milan U. ; INFN, Milan) ; Schwan, Christopher (Wurzburg U.) ; Magni, Giacomo (Vrije U., Amsterdam)
Publication 2022-11-18
Imprint 2022-11-18
Number of pages 6
Note 6 pages, 1 figure. Contribution to the Proceedings of the ICHEP 2022 Conference
In: PoS ICHEP2022pp.784
PoS ICHEP2022 (2022) pp.784
In: 41st International Conference on High Energy Physics (ICHEP 2022), Bologna, Italy, 6 - 13 Jul 2022, pp.784
DOI 10.22323/1.414.0784
10.22323/1.414.0784 (publication)
Subject category hep-ph ; Particle Physics - Phenomenology
Abstract Fitting PDFs requires the integration of a broad range of datasets, both from data and theory side, into a unique framework. While for data the integration mainly consists in the standardization of the data format, for the theory predictions there are multiple ingredients involved. Different providers are developed by separate groups for different processes, with a variety of inputs (runcards) and outputs (interpolation grids). Moreover, since processes are measured at different scales, DGLAP evolution has to be provided for the PDF candidate, or precomputed into the grids. We are working towards the automation of all these steps in a unique framework, that will be useful for any PDF fitting groups, and possibly also for phenomenological studies.
Copyright/License CC-BY-NC-ND-4.0
preprint: (License: CC BY 4.0)



Corresponding record in: Inspire


 Element opprettet 2023-01-26, sist endret 2024-10-02


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