5 papers
Resummed Distribution Functions: Making Perturbation Theory Positive and Normalized
Rikab Gambhir, Radha Mastandrea
Fixed-order perturbative calculations for differential cross sections can suffer from non-physical artifacts: they can be non-positive, non-normalizable, and non-finite, none of wh…
The Pareto Frontier of Resilient Jet Tagging
Rikab Gambhir, Matt LeBlanc, Yuanchen Zhou
Classifying hadronic jets using their constituents' kinematic information is a critical task in modern high-energy collider physics. Often, classifiers are designed by targeting th…
A Search for "New Physics'' "Beyond the Standard Model'' in Open Data with Machine Learning
Rikab Gambhir
In this new era of large data, it is important to make sure we do not miss any signs of new physics. Using the publicly-available open data collected by the arXiv.org experiment in…
Isolating Unisolated Upsilons with Anomaly Detection in CMS Open Data
Rikab Gambhir, Radha Mastandrea, Benjamin Nachman +1
We present the first study of anti-isolated Upsilon decays to two muons () in proton-proton collisions at the Large Hadron Collider. Using a machine learning (ML)-bas…
SPECTER: Efficient Evaluation of the Spectral EMD
Rikab Gambhir, Andrew J. Larkoski, Jesse Thaler
The Energy Mover's Distance (EMD) has seen use in collider physics as a metric between events and as a geometric method of defining infrared and collinear safe observables. Recentl…