EPPS16: nuclear parton distributions with LHC data
Abstract
We introduce a global analysis of collinearly factorized nuclear parton distribution functions (PDFs) including, for the first time, data constraints from LHC proton–lead collisions. In comparison to our previous analysis, EPS09, where data only from charged-lepton–nucleus deep inelastic scattering (DIS), Drell–Yan (DY) dilepton production in proton–nucleus collisions and inclusive pion production in deuteron–nucleus collisions were the input, we now increase the variety of data constraints to cover also neutrino–nucleus DIS and low-mass DY production in pion–nucleus collisions. The new LHC data significantly extend the kinematic reach of the data constraints. We now allow much more freedom for the flavor dependence of nuclear effects than in other currently available analyses. As a result, especially the uncertainty estimates are more objective flavor by flavor. The neutrino DIS plays a pivotal role in obtaining a mutually consistent behavior for both up and down valence quarks, and the LHC dijet data clearly constrain gluons at large momentum fraction. Mainly for insufficient statistics, the pion–nucleus DY and heavy-gauge-boson production in proton–lead collisions impose less visible constraints. The outcome – a new set of next-to-leading order nuclear PDFs called EPPS16 – is made available for applications in high-energy nuclear collisions.
Main Authors
Format
Articles
Research article
Published
2017
Series
Subjects
Publication in research information system
Publisher
Springer
The permanent address of the publication
https://urn.fi/URN:NBN:fi:jyu-201703201705Käytä tätä linkitykseen.
Review status
Peer reviewed
ISSN
1434-6044
DOI
https://doi.org/10.1140/epjc/s10052-017-4725-9
Language
English
Published in
European Physical Journal C
Citation
- Eskola, K., Paakkinen, P., Paukkunen, H., & Salgado, C. A. (2017). EPPS16: nuclear parton distributions with LHC data. European Physical Journal C, 77(3), Article 163. https://doi.org/10.1140/epjc/s10052-017-4725-9
Funder(s)
Research Council of Finland
Funding program(s)
Akatemiahanke, SA
Academy Project, AoF
![Research Council of Finland Research Council of Finland](/jyx/themes/jyx/images/funders/sa_logo.jpg?_=1739278984)
Additional information about funding
This research was supported by the Academy of Finland, Project 297058 of K.J.E.; by the European Research Council Grant HotLHC ERC-2011-StG-279579; by Ministerio de Ciencia e Innovación of Spain under project FPA2014-58293-C2-1-P; and by Xunta de Galicia (Conselleria de Educacion) – H.P. and C.A.S. are part of the Strategic Unit AGRUP2015/11. P.P. acknowledges the financial support from the Magnus Ehrnrooth Foundation. Part of the computing has been done in T. Lappi’s project at CSC, the IT Center for Science in Espoo, Finland.
Copyright© The Author(s) 2017. This article is published with open access at Springerlink.com and distributed under the terms of the Creative Commons Attribution 4.0 International License. Funded by SCOAP3.