Rapidity dependence of deuteron production in Au+Au collisions at $\sqrt{s_{NN}}$ = 200 GeV
BRAHMS Collaboration: I. Arsene, I. G. Bearden, D. Beavis, S. Bekele,, C. Besliu, B. Budick, H. B{\o}ggild, C. Chasman, C. H. Christensen, P., Christensen, H. H. Dalsgaard, R. Debbe, J. J. Gaardh{\o}je, C. E., J{\o}rgensen, K. Hagel, H. Ito, A. Jipa, E. B. Johnson, R. Karabowicz

TL;DR
This study measures proton and deuteron production over a wide rapidity range in high-energy Au+Au collisions, analyzing coalescence parameters and phase-space densities to understand particle formation and rapidity dependence.
Contribution
It provides new measurements of coalescence parameters and phase-space densities at various rapidities, revealing similarities between protons and anti-protons near mid-rapidity and differences from lower energy results.
Findings
Protons and anti-protons have similar coalescence parameters near mid-rapidity.
Little variation of coalescence parameters with rapidity from 0 to 3.
Strong dependence of parameters on transverse momentum at all rapidities.
Abstract
We have measured the distributions of protons and deuterons produced in high energy heavy ion Au+Au collisions at RHIC over a very wide range of transverse and longitudinal momentum. Near mid-rapidity we have also measured the distribution of anti-protons and anti-deuterons. We present our results in the context of coalescence models. In particular we extract the "volume of homogeneity" and the average phase-space density for protons and anti-protons. Near central rapidity the coalescence parameter and the space averaged phase-space density are very similar for both protons and anti-protons. For protons we see little variation of either or the space averaged phase-space density as the rapidity increases from 0 to 3. However both these quantities depend strongly on at all rapidities. These results are in contrast to lower energy data where the…
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.
