24-27 November 2022
Karlsruhe Institute of Technology
Europe/Berlin timezone

Substructure tagging with mass and pt dependent variable-R jet clustering and a soft drop veto

27 Nov 2022, 10:00
Gaede-Hörsaal (KIT Campus South)


KIT Campus South

KIT Campus map: https://www.kit.edu/campusplan/ Building: 30.22 Room: 130.1 Address: Campus South, Gaede Hörsaal Coordinates: 49.01265, 8.41044


Dr. Anna Benecke (UC Louvain)


The Heavy Object Tagger with Variable R (HOTVR) is an algorithm for the clustering and identification of boosted, hadronically decaying, heavy particles. The central feature of the HOTVR algorithm is a vetoed jet clustering with variable distance parameter R, that decreases with increasing transverse momentum of the jet. In this talk, we present improvements to the HOTVR algorithm, replacing the mass jump with a soft drop veto in the clustering. We study the performance of jet substructure tagging with HOTVR and ungroomed variable R jets, where we use machine learning techniques and energy flow polynomials to analyse the information loss from the soft drop veto. In addition, we show preliminary results of a distance parameter that changes with the jet mass and the transverse momentum, allowing to achieve an optimal value of R for W, Z, H bosons and top quarks simultaneously.

Category Particle / Astroparticle / Cosmology (Experiment)

Primary authors

Dr. Anna Benecke (UC Louvain) Anna Albrecht (Universität Hamburg) Dr. Roman Kogler (DESY Hamburg) Finley Quinton (Universität Hamburg)

Presentation Materials

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