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26 April 2024 |
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An artificial neural network based $b$ jet identification algorithm at the CDF Experiment | | J. Freeman
; J.D. Lewis
; W. Ketchum
; S. Poprocki
; A. Pronko
; V. Rusu
; P. Wittich
; | | Date: |
24 Aug 2011 | | Abstract: | We present the development and validation of a new multivariate $b$ jet
identification algorithm ("$b$ tagger") used 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. Employing
feed-forward neural network architectures, this tagger is unique in its
emphasis on using information from individual tracks. This tagger not only
contains the usual advantages of a multivariate technique such as maximal use
of information in a jet and tunable purity/efficiency operating points, but is
also capable of evaluating jets with only a single track. To demonstrate the
effectiveness of the tagger, we employ a novel method wherein we calculate the
false tag rate and tag efficiency as a function of the placement of a lower
threshold on a jet’s neural network output value in $Z+1$ jet and $tar{t}$
candidate samples, rich in light flavor and $b$ jets, respectively. | | Source: | arXiv, 1108.4738 | | Services: | Forum | Review | PDF | Favorites | |
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