We investigate the nuclear modification of heavy flavor decayed dielectrons in relativistic heavy-ion collisions using a Linear Boltzmann Transport (LBT) model. We find that heavy quark energy loss and coalescence significantly modify the dielectron invariant mass spectrum. As a consequence of these medium effects, the extracted QGP temperature is higher than that obtained from the vacuum baselines. The angular distributions of dielectrons further illuminate the underlying dynamics between heavy quarks and the medium: while collective radial expansion enhances near side correlations, scatterings between quarks and the medium, primarily elastic and non-perturbative interactions, lead to a broadening of the away side distribution.

In the established paradigm of jet quenching in relativistic heavy-ion collisions, jets from initial hard parton scatterings are suppressed due to their interaction with the quark-gluon plasma (QGP), serving as crucial tomographic probes of QGP properties. Within the linear Boltzmann transport model, we find that the QGP is also capable of absorbing and reprocessing energy deposited by the hard jets into emergent jet-like objects, providing an alternative production mechanism of thermal recoil jets. These emergent thermal recoil jets exhibit distinct transverse momentum (p_T) and jet-cone size (R) dependencies different from the hard jets, and interpret the puzzling observation of the enhanced yields of hadron triggered jets at large azimuthal angle relative to the away side and solely at small p_T and large R. These thermal recoil jets are predicted to have unique substructures, such as a jet shape that increases with radius and a thermal-like distribution of their constituents, which await verification in future experimental analyses.

Jets are powerful tomographic probes of the quark–gluon plasma (QGP) created in relativistic heavy-ion collisions. While the expanding landscape of jet observables reveals multiple aspects of jet-medium interactions, a precise and simultaneous description of the nuclear modification factors of hadrons and full jets remains challenging for current theoretical models. In this work, we present two key improvements to the linear Boltzmann transport (LBT) model to bridge this gap. First, instead of implementing in-medium parton transport after vacuum parton showers complete, we introduce a medium scale at which in-medium parton transport is inserted into the vacuum shower evolution, providing a more realistic description of parton–QGP interactions. Second, we incorporate color-flow information into the LBT model, enabling string connections between partons with configurations correlated to the medium-modified parton showers before hadronization. We demonstrate that both improvements alter the predicted ratio of hadron to jet quenching, leading to a satisfactory unified description of the nuclear modification factors of hadrons and jets with different flavors.

We study the bremsstrahlung photon production from a hard jet parton induced by rescattering with a dense nuclear medium. Using the charged current interaction channel of deep inelastic scattering between an electron and a large nucleus, we derive the spectrum of medium-induced photons emitted from high-energy heavy and light quarks at the next-to-leading twist in a unified framework. Going beyond the collinear expansion approximation, we show that the photon spectrum is determined by the full momentum distribution of the gluon exchanged between the propagating quark and the medium, or equivalently, by the differential elastic scattering rate of the hard quark inside the medium. Modeling the gluon field with a static Debye screened potential reduces the photon spectrum to a dependence on the transverse momentum distribution of the exchanged gluon. This work provides a more reliable input for future phenomenological studies of quark mass effects on jet-induced photon production in relativistic heavy-ion collisions.

Dielectrons from heavy flavor hadron decays not only constitute a crucial background to their thermal spectrum in high-energy nuclear collisions, from which the temperature of the quark-gluon plasma (QGP) is extracted, but also provide a valuable probe of heavy quark interactions with the QGP. Using a linear Boltzmann transport (LBT) model to describe heavy quark evolution inside the QGP and a hybrid fragmentation-coalescence model for their hadronization, we find that heavy quark energy loss softens the invariant mass spectrum of their decayed dielectrons and yields a higher value of the extracted QGP temperature, while coalescence hardens the spectrum and yields a lower value. Taking into account full medium effects leads to higher values of the extracted temperature than using vacuum baselines of heavy flavor decayed dielectrons in analyzing the experimental data. In addition, we find the angular correlations between dielectron pairs are sensitive to heavy quark interactions with the QGP: the radial flow of the QGP enhances the near-side correlations, and scatterings between heavy quarks and the QGP broaden the away-side correlations, with elastic and string interactions playing a dominant role.

Jet interactions with the color-deconfined quantum chromodynamics medium in relativistic heavy-ion collisions are conventionally assessed by measuring the modification of the distributions of jet observables with respect to their baselines in proton-proton collisions. Deep learning methods enable per-jet evaluation of these modifications, enhancing the use of jets as precision probes of the nuclear medium. In this work, we predict the jet-by-jet fractional energy loss chi for jets evolving through a quark-gluon plasma (QGP) medium using a linear Boltzmann transport model. To approximate realistic experimental conditions, we embed medium-modified jets in a thermal background and apply constituent subtraction for background removal. Two network architectures are studied: convolutional neural networks (CNNs) using jet images, and dynamic graph convolutional neural networks (DGCNNs) using particle clouds. We find that CNNs achieve accurate predictions for background-free jets but degrade in the presence of the QGP background and remain below the background-free baseline even after background subtraction. In contrast, DGCNNs applied to background-subtracted particle clouds maintain high accuracy across the entire chi range, demonstrating the advantage of point-cloud-based graph neural networks that exploit full jet structure under realistic conditions.

Jet quenching provides a valuable measure of the opacity of the quark-gluon plasma (QGP) produced in high-energy heavy-ion collisions. However, substantial suppression of charged hadron spectra is observed in highly peripheral collisions, despite the expectation of negligible jet-QGP interactions in this regime. To address this, we develop a HIJING-based initial condition model that accounts for the impact parameter dependence of both inelastic nucleon-nucleon (NN) collisions and the number of hard partonic scatterings per inelastic NN collision. This dependence introduces a geometric bias effect on the jet yield within a given centrality class of nucleus-nucleus (AA) collisions, suppressing the high-pT hadron spectrum in peripheral collisions due to dilute nucleon overlap at large AA impact parameters. By combining this improved initial condition model with a linear Boltzmann transport model for jet-QGP interactions, we obtain a satisfactory description of the centrality dependence of charged hadron suppression in Pb+Pb collisions at sNN=5.02 TeV.

We address the challenge of simultaneously describing jet and hadron quenching in the quark-gluon plasma by extending the linear Boltzmann transport (LBT) model. We introduce a medium virtuality scale to interleave vacuum and in-medium parton showers, and track color flows of jet partons in both their elastic and inelastic scatterings with the QGP to guide their further vacuum showers and string hadronization after they exit the QGP. These mechanisms jointly alter the predicted relative suppression between hadrons and jets. The updated LBT model yields a consistent description of the nuclear modification factors of jets and hadrons with different flavors.

We apply a Dense Neural Network (DNN) approach to reconstruct jet momentum within a quark-gluon plasma (QGP) background, using simulated data from PYTHIA and Linear Boltzmann Transport (LBT) Models for comparative analysis. We find that medium response particles from the LBT simulation, scattered out of the QGP background but belonging to medium-modified jets, lead to oversubtraction of the background if the DNN model is trained on vacuum jets from PYTHIA simulation. By training the DNN model on quenched jets generated using LBT or the combination of jet samples from PYTHIA and LBT, we significantly reduce this prediction bias and achieve more accurate background subtraction compared to conventional Area-based and Constituent Subtraction methods widely adopted in experimental measurements. We further study the performance of these machine learning models on evaluating the nuclear modification factor of jets, and find that while the unfolding procedure is necessary for correcting residuals in reconstructed jet momenta, models trained on samples incorporating quenched jets still achieve superior accuracy than those trained on vacuum jets even after unfolding.

The nuclear modification factor (RAA) of Bc mesons in high-energy nuclear collisions provides a novel probe of heavy quark interactions with the quark-gluon plasma (QGP). Based on a linear Boltzmann transport model that incorporates both Yukawa and string types of interactions between heavy quarks and the QGP, we study the production and evolution of heavy quarks and Bc mesons within the same framework. A Bc bound state dissociates while one of its constituent heavy quarks scatters with the QGP with momentum transfer greater than its binding energy. The medium-modified charm and bottom quarks can recombine into Bc mesons, and the medium-modified bottom quarks can also fragment to Bc mesons. We find that most primordial Bc mesons generated from the initial hard collisions dissociate inside the QGP. The production of Bc mesons is primarily driven by the recombination mechanism at low transverse momentum and fragmentation at high transverse momentum. The string interaction dominates over the Yukawa interaction in the nuclear modification of Bc mesons. The participant number dependence of the Bc meson RAA is determined by the complicated interplay between the heavy quark yield, energy loss, and the QGP volume. We obtain a reasonable description of the RAA of Bc mesons in Pb + Pb collisions at root sNN = 5.02 TeV, and provide predictions for Au + Au collisions at root sNN = 200 GeV.

Jet quenching is recognized as critical evidence for the existence of the quark-gluon plasma (QGP) and serves as an essential probe to study its transport properties. Measurements of hadron-triggered semi-inclusive recoil jets have gained popularity due to its capability to probe jets over an extended phase space at low transverse momenta (pT) and large radii. Recent ALICE measurements showed that the IAA, yield ratio of recoil jets between heavy-ion and p+p collisions, rises with jet pT and exceeds unity at high pT, contradicting conventional expectations that jet quenching should result in IAA values less than one. In this contribution, we re-examine the surface bias and study the effects of energy losses for both trigger hadrons and recoil jets on IAA, employing the Linear Boltzmann Transport (LBT) model to simulate jet-medium interactions. Our findings suggest that a large portion of hadrons used for the triggers undergoes substantial energy loss, despite surface bias. In particular, the energy loss of the trigger hadrons elevates the IAA baseline, corresponding to the case of no energy loss for recoil jets, to be greatly larger than unity. This enhancement of the baseline implies that the measured IAA values being larger than unity could still signal jet quenching.

Heavy flavor jets provide ideal tools to probe the mass effect on jet substructure in both vacuum and quark-gluon plasma. An energy-energy correlator (EEC) is an excellent jet substructure observable owning to its strong sensitivity to jet physics at different scales. We perform a complete realistic simulation on medium modification of heavy and light flavor jet EECs in heavy-ion collisions. A clear flavor hierarchy is observed for jet EECs in both vacuum and quark-gluon plasma due to the mass effect. The medium modification of inclusive jet EECs at different angular scales exhibits a very rich structure: suppression at intermediate angles, and enhancement at small and large angles, which can be well explained by the interplay of mass effect, energy loss, medium-induced radiation, and medium response. These unique features of jet EECs are shown to probe the physics of jet-medium interaction at different scales, and can be readily validated by upcoming experiments.

With the explosion of data on jet based observables in relativistic heavy-ion collisions at the Large Hadron Collider and the Relativistic Heavy-Ion Collider, perturbative QCD based simulations of these processes, often interacting with an expanding viscous fluid dynamical background, have taken center stage. This review is meant to bridge the gap between theory, simulation and phenomenology of jet modification in a dense medium. We will demonstrate how the existence of such end-to-end event generators with semi-realistic or even fully realistic final states allows for the most rigorous comparisons between pQCD based jet modification theory and experiment. State-of-the-art calculations of several jet based observables are presented. Extensions of this theory to jets in the small systems of p-A and e-A collisions is discussed.

Jet interactions with the color-deconfined QCD medium in relativistic heavy-ion collisions are conventionally assessed by measuring the modification of the distributions of jet observables with respect to their baselines in proton-proton collisions. Deep learning methods enable per-jet evaluation of these modifications, enhancing the use of jets as precision probes of the nuclear medium. In this work, we predict the jet-by-jet fractional energy loss χ for jets evolving through a quark-gluon plasma (QGP) medium using a Linear Boltzmann Transport (LBT) model. To approximate realistic experimental conditions, we embed medium-modified jets in a thermal background and apply Constituent Subtraction for background removal. Two network architectures are studied: convolutional neural networks (CNNs) using jet images, and dynamic graph convolutional neural networks (DGCNNs) using particle clouds. We find that CNNs achieve accurate predictions for background-free jets but degrade in the presence of the QGP background and remain below the background-free baseline even after background subtraction. In contrast, DGCNNs applied to background-subtracted particle clouds maintain high accuracy across the entire χ range, demonstrating the advantage of point-cloud-based graph neural networks that exploit full jet structure under realistic conditions.

Collective flow coefficients and spin polarization are valuable probes of the geometry and flow velocity field of the quark-gluon plasma (QGP) produced in relativistic heavy-ion collisions. Using a modified TRENTo initial condition coupled to a (3 + 1)-dimensional [(3+1)D] viscous hydrodynamic model CLVisc, we study the directed flow and elliptic flow coefficients of hadrons, together with the global polarization of A and A hyperons in asymmetric Cu + Au collisions. We extend the 2D TRENTo model to the 3D space, and find that the initial tilted geometry of the QGP fireball with respect to the longitudinal direction leads to a decrease of directed flow from positive to negative values with increasing pseudorapidity, an enhancement of elliptic flow at forward and backward pseudorapidities, and a nonmonotonic dependence of global polarization on the transverse momentum of hyperons. The initial longitudinal flow velocity gradient further enhances the values of directed flow and global polarization. Our model calculation provides a satisfactory description of the rapidity, transverse momentum, and centrality dependences of the directed flow of charged hadrons in Cu + Au collisions for the first time, and we propose that such asymmetric heavy-ion collisions create a better environment for studying the initial tilted geometry and longitudinal flow field of the QGP than symmetric Au + Au collisions do.

Jet-induced medium excitation is a crucial part of jet interactions with the quark-gluon plasma (QGP) in relativistic heavy-ion collisions, and has recently been confirmed by experiment for the first time. Based on the AMPT model simulation, we propose the strangeness enhancement around quenched jets as a novel signature of jet-induced medium excitation. By applying the jet-particle correlation techniques, we calculate jet-induced particle yields around the jets and find a significant enhancement of the strange-to-non-strange-hadron ratio and the double-to-single-strange-hadron ratio correlated with jets in relativistic nucleus-nucleus collisions relative to proton-proton collisions. This enhancement increases with both the strength of jet-QGP interactions and the radial distance from jet axis. These observations align with the features of jet-induced medium excitation and parton coalescence in hadron formation, and await experimental validation in the future measurements.

Jet quenching parameter q ^ is essential for characterizing the interaction strength between jet partons and nuclear matter. Based on the quark-meson model, we develop a new framework for calculating q ^ at finite chemical potentials, in which q ^ is related to the spectral function of the chiral order parameter. A mean field perturbative calculation up to the one-loop order indicates that the momentum broadening of jets is enhanced at both high temperature and high chemical potential, and approximately proportional to the parton number density in the partonic phase. We further investigate the behavior of q ^ in the vicinity of the critical endpoint (CEP) by coupling our calculation with a recently developed equation of state that includes a CEP in the universality class of the Ising model, from which we discover the partonic critical opalescence, i.e., the divergence of scattering rate of jets and their momentum broadening at the CEP, contributed by scatterings via the σ exchange process. Hence, for the first time, jet quenching is connected with the search of CEP.

We study bottom quark energy loss via the nuclear modification factor (RAA) and elliptic flow (v2) of nonprompt D0 and J/ψ in relativistic heavy-ion collisions at the Large Hadron Collider (LHC). The space-time profile of quark-gluon plasma is obtained from the hydrodynamics simulation, the dynamical evolution of heavy quarks inside the color deconfined QCD medium is simulated using a linear Boltzmann transport model that combines Yukawa and string potentials of heavy-quark-medium interactions, the hadronization of heavy quarks is performed using a hybrid coalescence-fragmentation model, and the decay of B mesons is simulated via . Using this numerical framework, we calculate the transverse momentum (pT) dependent RAA and v2 of direct D mesons, B mesons, and nonprompt D0 and J/ψ from B meson decay in Pb+Pb collisions at sNN=5.02 TeV. We find the mass hierarchy of the nuclear modification of prompt D and B mesons depends on their pT. Both RAA and v2 of heavy flavor particles show strong pT and centrality dependences due to the interplay between parton energy loss, medium geometry and flow, and hadronization of heavy quarks. Nonprompt D0 and J/ψ share similar patterns of RAA and v2 to B mesons except for a pT shift during the decay processes. Therefore, future more precise measurements on nonprompt D0 and J/ψ can help further pin down the bottom quark dynamics inside the quark-gluon plasma. Published by the American Physical Society 2024

In relativistic heavy-ion collisions, jet quenching in quark-gluon plasma (QGP) has been extensively studied, revealing important insights into the properties of the color deconfined nuclear matter. Over the past decade, there has been a surge of interest in the exploration of QGP droplets in small collision systems, such as p + p or p + A collisions, driven by the observation of collective flow phenomena. However, the absence of jet quenching, a key QGP signature, in these systems poses a puzzle. Understanding how jet quenching evolves with system size is crucial for uncovering the underlying physics. In this study, we employ the linear Boltzmann transport (LBT) model to investigate jet modification in 96 Ru + 96 Ru, 96 Zr + 96 Zr, and 197 Au + 197 Au collisions at root s NN = 200 GeV. Our findings highlight the system size sensitivity exhibited by jet nuclear modification factor (RAA) R AA ) and jet shape (rho), rho ), contrasting to the relatively weak responses of jet mass (M), M ), girth (g) g ) and momentum dispersion (pTD) p T D ) to system size variations. These results offer invaluable insights into the system size dependence of the QGP properties and await experimental validation at the Relativistic Heavy-Ion Collider.