Show simple item record

dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorLaenen, E.L.M.P.
dc.contributor.authorHasenack, Toon
dc.date.accessioned2024-08-07T23:07:53Z
dc.date.available2024-08-07T23:07:53Z
dc.date.issued2024
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/47164
dc.description.abstractWe present the first NNPDFpol2.0 results, where we fit polarised parton distribution functions to deep inelastic scattering, W-production in Drell-Yan and (di)jet data including charm contributions at next-to-next leading order. The effect on singlet and non-singlet distributions turns out to be small, however the gluon pPDF is quite significantly altered. We continue by considering EIC pseudo-data and its implications on the distributions. Next to this, we attempt to lay a strong theoretical foundation of factorisation by using the framework of soft-collinear effective theory.
dc.description.sponsorshipUtrecht University
dc.language.isoEN
dc.subjectA machine learning analysis of polarised proton substructure
dc.titleA machine learning analysis of polarised proton substructure
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.keywordsPolarised Parton Distribution Functions, NNPDF, Gluon Spin
dc.subject.courseuuTheoretical Physics
dc.thesis.id36160


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record