Measurement and modeling of electron-cloud-induced betatron tune shifts at the Cornell Electron-Positron Storage Ring test accelerator
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71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Engineering topics
Poprocki, S.
Publications and source records attributed to Poprocki, S..
Many-core applications to online track reconstruction in HEP experiments
Interest in parallel architectures applied to real time selections is growing in High Energy Physics (HEP) experiments. In this paper we describe performance measurements of Graphic Processing Units (GPUs) and Intel Many Integrated Core architecture (MIC) when applied to a typical HEP online task: the selection of events based on the trajectories of charged particles. We use as benchmark a scaled-up version of the algorithm used at CDF experiment at Tevatron for online track reconstruction – the SVT algorithm – as a realistic test-case for low-latency trigger systems using new computing architectures for LHC experiment. We examine the complexity/performance trade-off in porting existing serial algorithms to many-core devices. Measurements of both data processing and data transfer latency are shown, considering different I/O strategies to/from the parallel devices.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
An Artificial neural network based $b$ jet identification algorithm at the CDF Experiment
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 $t\bar{t}$ candidate samples, rich in light flavor and $b$ jets, respectively.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗