• Open Access

pythia8 underlying event tune for RHIC energies

Manny Rosales Aguilar, Zilong Chang, Raghav Kunnawalkam Elayavalli, Renee Fatemi, Yang He, Yuanjing Ji, Dmitry Kalinkin, Matthew Kelsey, Isaac Mooney, and Veronica Verkest
Phys. Rev. D 105, 016011 – Published 11 January 2022

Abstract

We report an underlying event tune for the pythia8 Monte Carlo event generator that is applicable for hadron collisions primarily at s ranges available at the Relativistic Heavy-Ion Collider (RHIC). We compare our new pythia8 tuned predictions to midrapidity inclusive π± spectra, jet substructure, Drell-Yan production, and underlying event measurements from RHIC and the Tevatron, as well as underlying event data from the Large Hadron Collider. With respect to the default pythia8 Monash Tune, the new “Detroit” tune shows significant improvements in the description of the experimental data. Additionally, we explore the validity of pythia8 predictions for forward rapidity π in s=200GeV collisions, where neither tune is able to sufficiently describe the data. We advocate for the new tune to be used for pythia8 studies at current and future RHIC experiments, and discuss future tuning exercises at lower center-of-mass energies, where forward/backward kinematics are essential at the upcoming Electron-Ion Collider.

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  • Received 18 October 2021
  • Accepted 14 December 2021

DOI:https://doi.org/10.1103/PhysRevD.105.016011

Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI. Funded by SCOAP3.

Published by the American Physical Society

Physics Subject Headings (PhySH)

Particles & Fields

Authors & Affiliations

Manny Rosales Aguilar1, Zilong Chang2, Raghav Kunnawalkam Elayavalli3,2, Renee Fatemi1, Yang He4, Yuanjing Ji5, Dmitry Kalinkin6, Matthew Kelsey7,*, Isaac Mooney7, and Veronica Verkest7

  • 1University of Kentucky, Lexington, Kentucky 40506, USA
  • 2Brookhaven National Laboratory, Upton, New York 11973, USA
  • 3Yale University, New Haven, Connecticut 06517, USA
  • 4Shandong University, Qingdao, Shandong 266237, China
  • 5Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
  • 6Indiana University, Bloomington, Indiana 47408, USA
  • 7Wayne State University, Detroit, Michigan 48202, USA

  • *mkelsey@wayne.edu

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Vol. 105, Iss. 1 — 1 January 2022

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