Study Jet-Induced Medium Response And Diffusion Wake In High-Energy Heavy-Ion Collisions

Jets as the hard probes of the quark gluon plasma are produced during the initial hard scattering in the high-energy heavy-ion collisions.When a jet goes through the quark gluon plasma（QGP）,it will experience energy loss and p_Tbroadening.This phenomenon is called jet quenching.It was observed at the Relativistic Heavy Ion Collider（RHIC）at Brookhaven National Laboratory,confirming the formation of quark gluon plasma.Similar results were later verified at the Large Hadron Collider（LHC）at CERN.Jet quenching will also induce medium response in the form of Mach cone.Ac-cording to theoretical calculations,the angle of the front wake of a Mach cone depends on the speed of sound in the medium which is given by the equation of state.In the meantime,the width of the front wake in dependent on the shear viscosity.Thus search-ing for and studying Mach cone in the high-energy heavy-ion collisions can help us glean properties of QGP.In order to study jet quenching and medium response in the high-energy heavy-ion collisions,we have developed the CoLBT-hydro model based on the Linear Boltzmann Transport Model（LBT）.The CoLBT-hydro can describe both particle propagation and medium evolution.Therefore CoLBT-hydro calculation can cover the whole range of transverse momentum.We use this model to study phenomenon of jet quenching and medium response at different collision energy.According to our results,we find that medium response can lead to enhancement of soft hadrons in the direction of the jet.However,the gluon radiation has the similar effects.It is difficult for us to distinguish them in the final results.There is a region of negative energy density distribution behind the Mach wave,called the diffusion wake,causing depletion of soft hadrons in the opposite direction of the jet,making the yield of soft hadrons in this region in nuclear-nuclear collisions lower than the result in nucleon-nucleon collisions.To search for the signal of diffusion wake,we calculated correlations between Z and soft hadrons in azimuthal angle at the LHC energy.We find the signal was covered by the initial multiple parton interaction（MPI）effect.We proposed a mixed-event procedure to subtract this effect.Meanwhile,according to our study,the shape and size of the diffusion wake are dependent on the jet initial production position.We further employ the longitudinal and transverse gradient jet tomography for the first time to localize the initial jet production positions.The signal of diffusion wake is amplified in some specific events classified by the predicted initial jet position.Since the jet is a 3-dimensional observable,the jet-induced diffusion wake should also has a 3D structure.We use correlations between jet and soft hadrons in azimuthal angle?φ=φ_h-φ_jetand pseudo rapidity?η=η_h-η_jetinγ-jet events to study it.We find that a valley is formed in this correlation in the background of jet by the diffusion.When we integrate?φin the range_|?φ|>π/2.0,we will get a double-peak structure in the rapidity distribution.We refer this structure as the unique signal of the diffusion wake.Based on this work,we use a two-Gaussian fit to extract MPI and diffusion wake contributions from the rapidity distribution.Finally,we study MPI and diffusion wake’s sensitivity to jet energy loss,shear viscosity and equation of state.Nowadays,deep learning is widely used in the high-energy heavy-ion collisions,we also implement point cloud neural networks to assist 2D jet tomography to improve the prediction accuracy.We use data from CoLBT-hydro model to train the neural network,and then predict the jet initial positions based on this network.Later we study Mach cone and diffusion wake dependence on the jet initial position.We also use pseudo data generated by LIDO model to check our network for model dependence.In the future,we hope that this approach will be implemented in experiments to help find singals of Mach cone and diffusion wake.