Search for New Physics in the Mono b/c Signature with the ATLAS Detector

Searches for physics beyond the Standard Model (BSM) at the Large Hadron Collider often focus on final states with large missing transverse energy (MET) and heavy-flavor jets, which can provide sensitivity to dark matter and leptoquark scenarios. In this project, we investigate the mono-b/c signature (one energetic jet plus MET) using machine learning (ML) techniques such as Deep Neural Networks and Boosted Decision Trees. Preliminary results indicate that ML based methods have significantly increased sensitivity to BSM signals compared to traditional cut-and-count approach.