The effect of recoils on soft-drop-groomed observables in $γ$-tagged jets in a multistage approach
Y. Tachibana, C. Sirimanna, A. Majumder, A. Angerami, R. Arora, S. A. Bass, Y. Chen, R. Datta, L. Du, R. Ehlers, H. Elfner, R. J. Fries, C. Gale, Y. He, B. V. Jacak, P. M. Jacobs, S. Jeon, Y. Ji, F. Jonas, L. Kasper, M. Kordell, A. Kumar, R. Kunnawalkam-Elayavalli, J. Latessa, Y. -J. Lee, R. Lemmon, M. Luzum, S. Mak, A. Mankolli, C. Martin, H. Mehryar, T. Mengel, C. Nattrass, J. Norman, C. Parker, J. -F. Paquet, J. H. Putschke, H. Roch, G. Roland, B. Schenke, L. Schwiebert, A. Sengupta, C. Shen, M. Singh, D. Soeder, R. A. Soltz, I. Soudi, J. Velkovska, G. Vujanovic, X. -N. Wang, X. Wu, W. Zhao
Abstract
We investigate medium-induced modifications to jet substructure observables that characterize hard components in central Pb-Pb collisions at $\sqrt{s_{NN}}=5.02$~TeV. Using a multistage Monte Carlo simulation of in-medium jet shower evolution, we explore flavor-dependent medium effects through simulations of inclusive and $γ$-tagged jets. The results show that quark jets undergo a nonmonotonic modification compared with gluon jets in observables such as the Pb-Pb to $p$-$p$ ratio of the soft drop prong angle $r_g$, the relative prong transverse momentum $k_{T,g}$, and the groomed mass $m_g$ distributions. Due to this nonmonotonic modification, $γ$-tagged jets, enriched in quark jets, provide surprisingly clear signals of medium-induced structural modifications, distinct from effects dominated by selection bias. Further systematic studies demonstrate that these effects are dominated by recoil medium response. This work highlights the potential of hard substructures in $γ$-tagged jets as powerful tools for probing the jet-medium interactions in high-energy heavy-ion collisions, in particular by enabling detailed investigations of jet-medium parton scatterings via their associated medium response. All simulations for $γ$-tagged jet analyses carried out in this paper used triggered events containing at least one hard photon, which highlights the utility of these observables for future Bayesian analysis.
