However, can we apply machine learning methods to determine the exact groups of particles that become a jet irrespective of what radius they end up having?
Notes:
The anti-kt algorithm from fastjet is used to cluster particles into jets by preferentially merging constituents with high transverse momentum with respect to their nearest neighbours. It results in jets that are roughly circular in the (y, φ) plane. The C/A algorithm relies only on distance weighting and determines angular jets. Due to the purely spatial character of the distance variables, C/A de-clusters the best and so is the best suited for studying jet substructure.
A jet definition needs
However, can we apply machine learning methods to determine the exact groups of particles that become a jet irrespective of what radius they end up having?
Notes: The anti-kt algorithm from fastjet is used to cluster particles into jets by preferentially merging constituents with high transverse momentum with respect to their nearest neighbours. It results in jets that are roughly circular in the (y, φ) plane. The C/A algorithm relies only on distance weighting and determines angular jets. Due to the purely spatial character of the distance variables, C/A de-clusters the best and so is the best suited for studying jet substructure.