Undergraduate Research & Scholarships

Adrian Deutscher-Bishop

Use of Conditional Normalizing Flows in Background Modeling

Detecting a specific event from a particle accelerator requires having a model of the background of that event. Usually, this is done using Monte Carlo simulations of events, but these can be inaccurate. This summer, I will continue my research into Conditional Normalizing Flows, which are a type of neural network which transforms Monte Carlo simulations of events into backgrounds that more resemble the actual data.

Message To Sponsor

Thank you so much for supporting my summer research. Ever since I started doing research with URAP, I have really felt like I have been prepared for a career in particle physics, and have picked up analysis skills and particle physics knowledge that I never would have from just my classes. I look forward to continuing my research this summer!