Spectral Clustering for Jet Physics
arXiv:2104.01972 · doi:10.1007/JHEP02(2022)165
Abstract
We present a new approach to jet definition alternative to clustering methods, such as the anti- scheme, that exploit kinematic data directly. Instead the new method uses kinematic information to represent the particles in a multidimensional space, as in spectral clustering. After confirming its Infra-Red (IR) safety, we compare its performance in analysing , and events from Monte Carlo (MC) samples, specifically, in reconstructing the relevant final states, to that of the anti-kT algorithm. Finally, we show that the results for spectral clustering are obtained without any change in the parameter settings of the algorithm, unlike the anti-kT case, which requires the cone size to be adjusted to the physics process under study.
arXiv comment31 pages, 17 figures
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