1 citations · 1 across the 5 of their papers we have counts for
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A Phase-Space Inclusive Figure of Merit Based in Optimal Transport for Validating Monte Carlo Reweightings
Rishabh Jain, Lauren Hay, Matt LeBlanc +1
Validating whether the underlying physics of a model has been retained after a full phase-space reweighting poses a unique challenge. Often, validation relies on comparing histogra…
Optimizing Cell-Based Negative Weight Mitigation with Optimal Transport
Lauren Hay, Rishabh Jain, Matt LeBlanc +1
As the accuracy of experimental results in high energy physics (HEP) increases, so does the demand for precision Monte Carlo (MC) simulation. Higher-accuracy event generation at ne…
Learning the Geometry of Collider Events with Metric-Aware Deep Sets
Lauren Hay, Rishabh Jain, Matt LeBlanc +1
Optimal transport gives structured data a geometry, but exact evaluation is costly in large pairwise analyses that exploit relationships among distances. Learned surrogates are fas…
Optimal-Transport-Based Cell Resampling for Negative and Pathological Event Weights
Regan Doherty, Lauren Hay, Rishabh Jain +4
Negative and pathologically large Monte Carlo event weights strain the computing budgets of experiments at the Large Hadron Collider. Cell resampling algorithms locally redistribut…
Massive tree-level splitting functions beyond kinematical limits
Stefan Höche, Matt LeBlanc, Jennifer Roloff +1
We present a compact form of the massive tree-level QCD splitting functions and discuss a decomposition of the results in terms of lower-order expressions, scalar dipole a…
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…