Bayesian constraints on early-time jet quenching from large collision systems yield predictions of measurable energy loss in oxygen-oxygen collisions.
Aadet al.(ATLAS), Measurements of azimuthal anisotropies of jet production in Pb+Pb collisions at√sN N =5.02TeVwiththeATLASdetector,Phys.Rev
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ATLAS observes increasing dijet imbalance with centrality in O+O and Ne+Ne collisions at 5.36 TeV, consistent with medium-induced energy loss in small systems.
ATLAS reports significant suppression (I_AA < 1) of photon-tagged two-jet yields in Pb+Pb versus pp collisions at 5.02 TeV across three observables, compared to JEWEL, JETSCAPE, and LBT models.
An LSTM model trained on simulated jet substructure learns to predict true jet energy loss and distinguishes quenching signatures even after realistic detector effects are applied.
citing papers explorer
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Bayesian Constraints on Pre-Equilibrium Jet Quenching and Predictions for Oxygen Collisions
Bayesian constraints on early-time jet quenching from large collision systems yield predictions of measurable energy loss in oxygen-oxygen collisions.
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Observation of centrality-dependent dijet transverse momentum imbalance in O+O and Ne+Ne collisions at $\sqrt{s_{NN}}$ = 5.36 TeV with the ATLAS detector
ATLAS observes increasing dijet imbalance with centrality in O+O and Ne+Ne collisions at 5.36 TeV, consistent with medium-induced energy loss in small systems.
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Measurement of isolated photon plus two-jet correlations in Pb+Pb and $pp$ collisions at 5.02 TeV with ATLAS
ATLAS reports significant suppression (I_AA < 1) of photon-tagged two-jet yields in Pb+Pb versus pp collisions at 5.02 TeV across three observables, compared to JEWEL, JETSCAPE, and LBT models.
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Validating a Machine Learning Approach to Identify Quenched Jets in Heavy-Ion Collisions
An LSTM model trained on simulated jet substructure learns to predict true jet energy loss and distinguishes quenching signatures even after realistic detector effects are applied.