Designed a vertexing algorithm for the future HGC (High-granularity calorimeter) using only spatial and timing information to reconstruct interaction vertex locations to sub-millimeter precision, and applied this to Higgs to di-photon events.
HGCal simulation analyses for CMS - Sarah Marie Bruno
Compared the performance of the current ECAL (Electromagnetic calorimeter) and the future HGC for the Higgs to di-photon channel. Also worked at the CERN test beam with a prototype Shashlik detector.
Study of ECAL timing effects due to transparency using Pi0 decays from CMS - Kai ChangUsed neutral pion events to study ECAL crystal timing response and transparency in 2015 data, including the relationship between the two variables.
Precision timing analysis of July 2015 test beam data - Mohammad Hassan HassanhashahiWorked at the CERN test beam with a prototype Shashlik detector, and measured the timing resolution and rising edge properties of pulses from a Hamamatsu MCP-PMT (micro-channel plate photomultiplier tube).
Timing resolution studies of Hamamatsu silicon photomultipliers - Eric LiuWorked at the FNAL test beam with Hamamatsu SiPMs (silicon-based photomultipliers), measured timing resolution with a picosecond-pulsed laser.
Direct tests of a pixelated microchannel plate as the active element of a shower maximum detector - Federico PresuttiWorked at the FNAL test beam to investigate use of Photek/Photonis MCPs in an electromagnetic shower maximum detector.
Trained neural networks for track reconstruction using PyBrain and Theanets libraries.
Machine learning techniques for razor triggers - Marina KolosovaTrained neural networks to make razor trigger decisions, with focus on fast, hardware- compatible implementations.
Machine learning for fast data transfers - Nikhil KrishnanImplemented a principle component analysis using data transfer information from the CMS PhEDEx (Physics Experiment Data Export) tool.
Optimizing SUSY searches at CMS using machine learning techniques - Yuting LiInvestigated use of SOMs (self-organizing map) for outlier detection in razor searches, and NADEs (Neural autoregressive density estimator) for pseudo-data production.
Convolutional neural network - Sahand SeifnashriInvestigated use of GPU-based convolution neural networks for a quark-gluon jet discriminator.
Measured jet transverse momentum resolution and bias in pointing reconstruction, hadronic razor trigger efficiency, and electron/muon reconstruction efficiencies in 8 TeV data and 13 TeV Monte Carlo samples for the razor analysis.
I | Attachment | History | Action | Size | Date | Who | Comment |
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Bartlett.pdf | r1 | manage | 924.0 K | 2016-02-02 - 19:14 | UnknownUser | Bartlett Final Report | |
Bruno.pdf | r1 | manage | 1067.7 K | 2016-02-02 - 19:14 | UnknownUser | Bruno Final Report | |
Chang.pdf | r1 | manage | 5184.5 K | 2016-02-02 - 19:17 | UnknownUser | Chang Final Report | |
Filseth.pdf | r1 | manage | 2826.6 K | 2016-02-02 - 19:16 | UnknownUser | Filseth Final Report | |
Hassanshahi.pdf | r1 | manage | 1688.0 K | 2016-02-02 - 19:17 | UnknownUser | Hassanshahi Final Report | |
Jofrehei.pdf | r1 | manage | 586.1 K | 2016-02-02 - 19:18 | UnknownUser | Jofrehei Final Report | |
Kolosova.pdf | r1 | manage | 649.6 K | 2016-02-02 - 19:19 | UnknownUser | Kolosova Final Report | |
Krishnan.pdf | r1 | manage | 307.0 K | 2016-02-02 - 19:15 | UnknownUser | Krishnan Final Report | |
Li_final_report.pdf | r1 | manage | 766.0 K | 2016-02-02 - 19:18 | UnknownUser | Li Final Report | |
Liu.pdf | r1 | manage | 200.6 K | 2016-02-02 - 19:15 | UnknownUser | Liu Final Report | |
Presutti.pdf | r1 | manage | 2475.3 K | 2016-02-02 - 21:18 | UnknownUser | Presutti Final Report | |
Seif.pdf | r1 | manage | 831.9 K | 2016-02-02 - 19:18 | UnknownUser | Seif Final Report |