Abstract
We present the development and validation of the Higgs Optimized b Identification Tagger (HOBIT), a multivariate b-jet identification algorithm optimized for Higgs boson searches at the CDF experiment at the Fermilab Tevatron. At collider experiments, b taggers allow one to distinguish particle jets containing B hadrons from other jets; these algorithms have been used for many years with great success at CDF. HOBIT has been designed specifically for use in searches for light Higgs bosons decaying via H ! b\bar{b}. This fact combined with the extent to which HOBIT synthesizes and extends the best ideas of previous taggers makes HOBIT unique among CDF b-tagging algorithms. Employing feed-forward neural network architectures, HOBIT provides an output value ranging from approximately -1 (“light-jet like”) to 1 (“b-jet like”); this continuous output value has been tuned to provide maximum sensitivity in light Higgs boson search analyses. When tuned to the equivalent light jet rejection rate, HOBIT tags 54% of b jets in simulated 120 GeV/c2 Higgs boson events compared to 39% for SecVtx, the most commonly used b tagger at CDF. We present features of the tagger as well as its characterization in the form of b-jet finding efficiencies and false (light-jet) tag rates.
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URL
https://arxiv.org/abs/1205.1812