Abstract
Dielectrons produced in ultra-relativistic heavy-ion collisions provide a unique probe of the whole system evolution as they are unperturbed by final-state interactions. The dielectron continuum is extremely rich in physics sources: thermal radiation is of particular interest as it carries information about the temperature of the hot and dense system created in such collisions. The dielectron invariant mass distribution is sensitive to medium modifications of the spectral function of vector mesons that are linked to the potential restoration of chiral symmetry. Correlated electron pairs from semi-leptonic charm and beauty decays provide information about the heavy-quark energy loss.A summary of the LHC Run-1 preliminary results in all three collisions systems (pp, p-Pb and Pb-Pb) is presented. Furthermore, the status of the ongoing Run-2 analyses is discussed with a focus on pp collisions collected with a high charged-particle multiplicity trigger, on new analysis methods to separate prompt from non-prompt sources, and on the usage of machine learning methods for background rejection.
Highlights
The study of opposite sign dileptons in ultra-relativistic heavy ion collisions allows us to investigate the electromagnetic radiation released in the hot and dense medium created after the collision
Dielectrons are an ideal probe at collider experiments, since they are accessible at low pT and midrapidity, i.e. the rapidity region with the highest energy density
The data are well reproduced by expectations from the cocktail within uncertainties and reflect the much harder DCAee spectrum of the non prompt semileptonic decays in the intermediate mass region (IMR), showing the potential of this analysis to evaluate the contribution from heavy flavour sources in our spectra
Summary
The study of opposite sign dileptons (pairs of leptons) in ultra-relativistic heavy ion collisions allows us to investigate the electromagnetic radiation released in the hot and dense medium created after the collision. The status of the ongoing Run-2 analyses is discussed with a focus on pp collisions collected with a high charged-particle multiplicity trigger, on new analysis methods to separate prompt from non-prompt sources, and on the usage of machine learning methods for background rejection.
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