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hep-ph2026
Compact Representation of Particle-Collision Events for Physics-Informed Machine Learning
Wasikul Islam, Sergei Chekanov
We introduce a compact, physics-driven event representation, RMM-C46, designed to compress the high-dimensional rapidity mass matrix (RMM) into a low-dimensional, interpretable fea…
hep-ph2025
New Physics Searches at the LHC through Event-based Anomaly Detection and Development of ADFilter Web-tool
Wasikul Islam, Sergei Chekanov, Nicholas Luongo
This work presents advancements in model-agnostic searches for new physics at the Large Hadron Collider (LHC) through the application of event-based anomaly detection techniques ut…
hep-ph2025
Enhancing Sensitivity for Di-Higgs Boson Searches Using Anomaly Detection and Supervised Machine Learning Techniques
Sergei V. Chekanov, Wasikul Islam, Nicholas Luongo
This paper explores different strategies for enhancing sensitivity to new heavy resonances that decay into two or more Higgs bosons. This is achieved using two neural network archi…