Spectral clustering for jet reconstruction

Abstract

We present a new approach to jet definition alternative to clustering methods, such as the anti-kT 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 gg→H125 GeV→H40 GeVH40 GeV→bb¯bb¯, gg→H500 GeV→H125 GeVH125 GeV→bb¯bb¯ and gg,qq¯→tt¯→bb¯W+W−→bb¯jjlνl 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.

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Identifiers

ORCID for S. Jain: orcid.org/0000-0002-0964-879X

ORCID for S. Moretti: orcid.org/0000-0002-8601-7246

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