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A comprehensive Bayesian analysis of the 3D dynamics of high-energy nuclear collisions is presented. We perform a systematic model-to-data comparison using simulations of large and small collision systems, and a broad range of measurements from the PHENIX, STAR, PHOBOS, and BRAHMS collaborations spanning nearly two decades of RHIC operations. In particular, we perform fully 3D multi-stage simulations including rapidity-dependent energy deposition with global energy conservation using the 3D Glauber model, along with relativistic viscous hydrodynamics with MUSIC. We calibrate the model on rapidity- and pT-differential observables and analyze the respective constraints on initial state and transport properties they provide. We emphasize the additional constraints provided by rapidity-dependent measurements, the differences in large and small system calibrations, and the tension exhibited by particular observables. We use our calibrated model to make predictions of observables in p-Au and 3He-Au collisions. Furthermore, we facilitate direct comparison of experimental measurements by highlighting the dependence of flow measurements on the rapidity of the regions of interest and reference, as well as the importance of the centrality selection. In particular, we examine the apparent differences between the STAR and PHENIX v2 and v3 measurements in small systems. 

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 $\gamma$ -tagged jets. The results show that quark jets undergo a nonmonotonic modification compared with gluon jets in observables such as the Pb-Pb to $p\text{−}p$ 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, $\gamma$ -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 $\gamma$ -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 $\gamma$ -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. 

An investigation of high-transverse-momentum (high- $p_T$ ) photon-triggered jets in proton-proton ( $p\text{−}p$ ) and ion-ion ( $A\text{−}A$ ) collisions at $\sqrt{s_{NN}}=0.2$ and $5.02\mathrm{TeV}$ is carried out, using the multistage description of in-medium jet evolution. Monte Carlo simulations of hard scattering and energy loss in heavy-ion collisions are performed using parameters tuned in a previous study of the nuclear modification factor ( $R_{AA}$ ) for inclusive jets and high- $p_T$ hadrons. We obtain a good reproduction of the experimental data for photon-triggered jet $R_{AA}$ , as measured by the ATLAS detector, the distribution of the ratio of jet to photon $p_T$ ( $X_{J\gamma }$ ), measured by both CMS and ATLAS, and the photon-jet azimuthal correlation as measured by CMS. We obtain a moderate description of the photon-triggered jet $I_{AA}$ , as measured by STAR. A noticeable improvement in the comparison is observed when one goes beyond prompt photons and includes bremsstrahlung and decay photons, revealing their significance in certain kinematic regions, particularly at $X_{J\gamma }>1$ . Moreover, azimuthal angle correlations demonstrate a notable impact of bremsstrahlung photons on the distribution, emphasizing their role in accurately describing experimental results. This work highlights the success of the multistage model of jet modification to straightforwardly predict (this set of) photon-triggered jet observables. This comparison, along with the role played by bremsstrahlung photons, has important consequences on the inclusion of such observables in a future Bayesian analysis. Published by the American Physical Society2025 

The Collaboration reports a new determination of the jet transport parameter $\hat{q}$ in the quark-gluon plasma (QGP) using Bayesian inference, incorporating all available inclusive hadron and jet yield suppression data measured in heavy-ion collisions at the BNL Relativistic Heavy Ion Collider (RHIC) and the CERN Large Hadron Collider (LHC). This multi-observable analysis extends the previously published Bayesian inference determination of $\hat{q}$ , which was based solely on a selection of inclusive hadron suppression data. is a modular framework incorporating detailed dynamical models of QGP formation and evolution, and jet propagation and interaction in the QGP. Virtuality-dependent partonic energy loss in the QGP is modeled as a thermalized weakly coupled plasma, with parameters determined from Bayesian calibration using soft-sector observables. This Bayesian calibration of $\hat{q}$ utilizes active learning, a machine-learning approach, for efficient exploitation of computing resources. The experimental data included in this analysis span a broad range in collision energy and centrality, and in transverse momentum. In order to explore the systematic dependence of the extracted parameter posterior distributions, several different calibrations are reported, based on combined jet and hadron data; on jet or hadron data separately; and on restricted kinematic or centrality ranges of the jet and hadron data. Tension is observed in comparison of these variations, providing new insights into the physics of jet transport in the QGP and its theoretical formulation. Published by the American Physical Society2025 

Abstract Quantum Chromodynamics predicts a phase transition from hadronic matter to quark–gluon plasma (QGP) at high temperatures and energy densities, where quarks and gluons (partons) are no longer confined within hadrons. The QGP forms in ultrarelativistic heavy-ion collisions. Anisotropic flow coefficients, quantifying the azimuthal expansion of produced matter, probe QGP properties. Flow measurements in high-energy heavy-ion collisions show a distinctive grouping of anisotropic flow for baryons and mesons at intermediate transverse momentum – a feature associated with flow imparted at the quark level, confirming QGP existence. The observation of QGP-like features in proton–proton and proton–ion collisions has sparked debate about QGP formation in smaller systems. For the first time, we demonstrate the distinctive grouping of anisotropic flow for baryons and mesons in high-multiplicity proton–lead and proton–proton collisions at the Large Hadron Collider (LHC). These results are described by a model including hydrodynamic flow followed by hadron formation via quark coalescence, consistent with the formation of partonic flowing systems in these collisions.