Sequential machine learning on jet declustering history trees outperforms static models at identifying jet quenching in heavy-ion collision simulations.
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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.
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Jet Quenching Identification via Supervised Learning in Simulated Heavy-Ion Collisions
Sequential machine learning on jet declustering history trees outperforms static models at identifying jet quenching in heavy-ion collision simulations.
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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.