Probing nuclear parton densities and parton energy loss processes through photon + heavy-quark jet production in p-A and A-A collisions
T. Stavreva, F. Arleo, I. Schienbein

TL;DR
This paper investigates photon and heavy-quark jet production in p-A and A-A collisions to probe nuclear parton densities and parton energy loss, providing insights for future experiments at the LHC.
Contribution
It offers a detailed phenomenological analysis of photon + heavy-quark jet production, highlighting its sensitivity to nuclear PDFs and parton energy loss in dense QCD media.
Findings
Future p-A data can distinguish between different nuclear PDF sets.
Photon transverse momentum helps gauge initial parton energy in heavy-ion collisions.
Two-particle observables improve understanding of parton energy loss processes.
Abstract
We present a detailed phenomenological study of the associated production of a prompt photon and a heavy-quark jet (charm or bottom) in proton-nucleus (p-A) and nucleus-nucleus (A-A) collisions. The dominant contribution to the cross-section comes from the gluon--heavy-quark (gQ) initiated subprocess, making this process very sensitive to the gluon and the heavy quark nuclear parton densities. We show that the future p-A data to be collected at the LHC should allow one to disentangle the various nPDF sets currently available. In heavy-ion collisions, the photon transverse momentum can be used to gauge the initial energy of the massive parton which is expected to propagate through the dense QCD medium produced in those collisions. The two-particle final state provides a range of observables (jet asymmetry, photon-jet pair momentum, among others), through the use of which a better…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsParticle physics theoretical and experimental studies · High-Energy Particle Collisions Research · Computational Physics and Python Applications
