Top Tagging
Tilman Plehn, Michael Spannowsky
TL;DR
Boosted hadronic tops motivate jet-substructure approaches to identify t t decays within fat jets amid dense QCD backgrounds. The review contrasts clustering-history taggers and jet-shape/tagger families, and details grooming techniques (filtering, trimming, pruning) that mitigate soft QCD effects while preserving signal. It catalogs major algorithms (YSplitter, Seattle, Johns Hopkins, HEPTopTagger, Thaler-Wang, N-subjettiness) and discusses performance, data validations, and applications to beyond-Standard-Model searches. The outlook emphasizes data-driven validation and multi-observable strategies to achieve robust boosted-top tagging in the LHC environment.
Abstract
Top tagging is a recent approach to identifying boosted hadronic top quarks. It avoids reconstructing individual top decay products and instead uses a jet algorithm to reconstruct the entire top decay. Quite generally, geometrically large jets including heavy particles (fat jets) can be analyzed on the level of their subjet constituents. LHC data will soon allow us to establish this new analysis method. We discuss different tagging algorithms, their critical QCD aspects, and currently available experimental results. For the development of taggers and their different applications this review should provide a firm theoretical and algorithmic background.
