Charm multiplicity distribution in high energy pp collisions with PYTHIA
Y. N. Lima, C. Jahnke, M. Munhoz, F. S. Navarra
TL;DR
This work uses PYTHIA-8 to predict open charm (quarks and D mesons) multiplicity distributions in high-energy pp collisions across multiple $\sqrt{s}$ and pseudorapidity windows, exploring MPI and color reconnection effects, quark-hadron duality, and KNO scaling. By comparing partonic charm counts with hadronic D-meson counts, the study tests the robustness of quark-hadron duality and assesses whether charm production follows simple statistical forms such as Poisson or Negative Binomial distributions. The results show charm multiplicities are narrowly distributed and largely consistent with Poisson expectations, grow slowly with energy, and largely preserve duality with hadrons; KNO scaling is not strictly satisfied, especially at large $| au|$, and MPI effects become more pronounced for wide rapidity ranges. Overall, the paper provides a quantitative baseline for charm yields in pp collisions that will inform future measurements at Run-3 and HL-LHC, including tests of Poisson/NBD fits and scaling properties in charm production.
Abstract
With the growth of statistics in the future experiments at the LHC, the number of events with charm production will increase substantially. It may become possible to measure the multiplicity distribution of charm particles. Using PYTHIA-8, we generated charm multiplicity distributions in $pp$ collisions for different pseudorapidity ranges ($|η| < 0.5, 1.0, 2.0, 3.0$) and center-of-mass energies ($\sqrt{s}=$ 0.9, 2.36, 2.76, 7.0, 8.0, 13.0 TeV). We investigated the role played by multiple parton interactions and color reconnection. We compared the multiplicity distribution of D mesons with the charm quark multiplicity distribution. We observe that the "quark-hadron" duality hypothesis is satisfied. With the obtained distributions we tested the validity of the Koba-Nielsen-Olesen scaling. We also parameterized the charm distributions considering the Poisson and negative binomial distributions.
