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Register a new userImproved jet clustering algorithm with vertex information for multi-bottom final states
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In collider physics at the TeV scale, there are many important processes which involve six or more jets. The sensitivity of the physics analysis depends critically on the performance of the jet clustering algorithm. We present a full detector simulation study for the ILC of our new algorithm which makes use of secondary vertices which improves the reconstruction of b jets. This algorithm will have many useful applications, such as in measurements involving a light Higgs which decays predominantly into two b quarks. We focus on the measurement of the Higgs self-coupling, which has so far proven to be challenging but is one of the most important measurements at the ILC.
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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 jets neural network output value in $Z+1$ jet and $tbar{t}$ candidate samples, rich in light flavor and $b$ jets, respectively.
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The Jiangmen Underground Neutrino Observatory (JUNO) is designed to study neutrino mass hierarchy and measure three of the neutrino oscillation parameters with high precision using reactor antineutrinos. It is also able to study many other physical phenomena, including supernova neutrinos, solar neutrinos, geo-neutrinos, atmosphere neutrinos, and so forth. The central detector of JUNO contains 20,000~tons of liquid scintillator (LS) and about 18,000 20-inch photomultiplier tubes (PMTs), which is the largest liquid scintillator one under construction in the world up today. The energy resolution is expected to be 3%/$sqrt{E(MeV)}$. To meet the requirements of the experiment, an algorithm of vertex reconstruction, which takes into account time and charge information of PMTs, has been developed by deploying the maximum likelihood method and well understanding the complicated optical processes in the liquid scintillator.
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