Spectral-function features fed to a dense network improve expected gluino-mass reach by ~150 GeV over ATLAS Gtt-0L-C and ~250 GeV over kinematics-only ML for the fully hadronic channel.
Exploring Optimal Transport for Event-Level Anomaly Detection at the Large Hadron Collider,
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Machine learning fully hadronic events with spectral functions
Spectral-function features fed to a dense network improve expected gluino-mass reach by ~150 GeV over ATLAS Gtt-0L-C and ~250 GeV over kinematics-only ML for the fully hadronic channel.