Journal article
The PDF4LHC21 combination of global PDF fits for the LHC Run III
- Abstract:
- A precise knowledge of the quark and gluon structure of the proton, encoded by the parton distribution functions (PDFs), is of paramount importance for the interpretation of high-energy processes at present and future lepton–hadron and hadron–hadron colliders. Motivated by recent progress in the PDF determinations carried out by the CT, MSHT, and NNPDF groups, we present an updated combination of global PDF fits: PDF4LHC21. It is based on the Monte Carlo combination of the CT18, MSHT20, and NNPDF3.1 sets followed by either its Hessian reduction or its replica compression. Extensive benchmark studies are carried out in order to disentangle the origin of the differences between the three global PDF sets. In particular, dedicated fits based on almost identical theory settings and input datasets are performed by the three groups, highlighting the role played by the respective fitting methodologies. We compare the new PDF4LHC21 combination with its predecessor, PDF4LHC15, demonstrating their good overall consistency and a modest reduction of PDF uncertainties for key LHC processes such as electroweak gauge boson production and Higgs boson production in gluon fusion. We study the phenomenological implications of PDF4LHC21 for a representative selection of inclusive, fiducial, and differential cross sections at the LHC. The PDF4LHC21 combination is made available via the LHAPDF library and provides a robust, user-friendly, and efficient method to estimate the PDF uncertainties associated to theoretical calculations for the upcoming Run III of the LHC and beyond.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 11.7MB, Terms of use)
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- Publisher copy:
- 10.1088/1361-6471/ac7216
- Publisher:
- IOP Publishing
- Journal:
- Journal of Physics G: Nuclear and Particle Physics More from this journal
- Volume:
- 49
- Issue:
- 8
- Article number:
- 80501
- Publication date:
- 2022-07-05
- Acceptance date:
- 2022-05-23
- DOI:
- EISSN:
-
1361-6471
- ISSN:
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0954-3899
- Language:
-
English
- Keywords:
- Pubs id:
-
1268526
- Local pid:
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pubs:1268526
- Deposit date:
-
2022-10-07
Terms of use
- Copyright holder:
- Ball et al.
- Copyright date:
- 2022
- Rights statement:
- © 2022 The Author(s). Published by IOP Publishing Ltd. Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
- Licence:
- CC Attribution (CC BY)
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