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 → \( b\overline{b}b\overline{b} \), gg → H500 GeV → H125 GeVH125 GeV → \( b\overline{b}b\overline{b} \) and gg, \( q\overline{q} \) → \( t\overline{t} \) → \( b\overline{b}{W}^{+}{W}^{-} \) → \( b\overline{b} jj\mathrm{\ell}{v}_{\mathrm{\ell}} \) 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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Cerro, G., Dasmahapatra, S., Day-Hall, H.A. et al. Spectral clustering for jet physics. J. High Energ. Phys. 2022, 165 (2022). https://doi.org/10.1007/JHEP02(2022)165
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DOI: https://doi.org/10.1007/JHEP02(2022)165