16 citations · 25 across the 4 of their papers we have counts for
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hep-ph2024
Top Quark Mass Extractions from Energy Correlators: A Feasibility Study
Jack Holguin, Ian Moult, Aditya Pathak +3
In a recent article, we proposed an energy correlator-based method to achieve a precision top quark mass extraction from jet substructure, using the -boson mass as a standard ca…
hep-ph2024★ 5 cited
A rotation-equivariant graph neural network for learning hadronic SMEFT effects
Suman Chatterjee, Sergio Sánchez Cruz, Robert Schöfbeck +1
We introduce a graph neural network architecture designed to extract novel phenomena in the Standard Model Effective Field Theory (SMEFT) context from LHC collision data. The propo…