Bulletin of the American Physical Society
83rd Annual Meeting of the APS Southeastern Section
Volume 61, Number 19
Thursday–Saturday, November 10–12, 2016; Charlottesville, Virginia
Session D1: Particle Physics I |
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Chair: Chris Neu, University of Virginia Room: West Ballroom |
Thursday, November 10, 2016 3:45PM - 3:57PM |
D1.00001: The search for `mirror' fermions with distinguished signatures at the 13 TeV LHC Shreyashi Chakdar, Vinh Hoang, K Ghosh, Pham Hung, S. Nandi There are four ideas that has been proposed to explain the tiny neutrino masses: the see-saw mechanism with a RH neutrino at the GUT scale, radiatively generated neutrino masses, the neutrino mass arising from a 2nd Higgs doublet having a tiny VEV and coupling only to the neutrinos, and finally the EW-scale $\nu_R$ model. This last framework includes new quarks and leptons of opposite chirality at the electroweak scale (for the same SM gauge symmetry $SU(2)_W \times U(1)_Y$) compared to the SM. This model satisfies the EW precision tests and upon introducing an extra Higgs doublet the constraint coming from the 125-GeV scalar. Since in this model, the mirror fermions are required to be in the EW scale, these can be produced at the LHC giving final states with a very low background from the SM. One such final state is the same sign dileptons with large missing $p_T$ for the events. We explore the constraint provided by the $8$ TeV LHC and prospect of observing this signal in the $13$ TeV. Additional signals will be the presence of displaced vertices depending on the smallness of the Yukawa couplings of the mirror leptons with the ordinary leptons and the singlet Higgs present in the scenario. Of particular importance is also the production of the RH neutrinos at collider energies. [Preview Abstract] |
(Author Not Attending)
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D1.00002: A search for supersymmetry in all-hadronic final states using top tager with the CMS detector at the LHC Yagya Joshi A search for supersymmetry in all-hadronic events with missing transverse momentum using top quark tagging is presented. The data were collected during 2016 in proton-proton collisions at a center-of-mass energy of 13 TeV with the CMS detector at the LHC. . Sensitivity to the potential signal, over a range of scalar-top and neutralino masses is obtained by selecting events into bins with large missing momentum,~ MT2, the number of bottom quark and all-hadronic top quark selected with a top-quark tagger. [Preview Abstract] |
Thursday, November 10, 2016 4:09PM - 4:21PM |
D1.00003: Measuring the top-Higgs coupling at CMS Evan Wolfe, Chris Neu With the discovery of the scalar boson in 2012~and measurements corresponding thus far to the standard model prediction of the Higgs, the future of experimental particle physics has become much more broad with respect to the search for new physics.~ Observations of the interaction between the Higgs boson and top quark are also needed to clearly identify the new boson's properties and allow its full classification in the standard model.~Theory predicts the Higgs to couple strongest to the top quark, allowing an excellent probe into the current understanding of the standard model by measuring ttH production at the CMS detector. Measuring ttH production is the only direct method for measuring the top-Higgs coupling which could provide both a reach into new physics and constrain extensions to the standard model such as Little Higgs, composite Higgs and Extra Dimensions. The direct probe of the top-Higgs coupling through ttH will be able to shed light on extensions to the SM by comparisons to theoretical cross-sections and the method of electroweak symmetry breaking with the most massive fermion found to date. In this talk I'll present results from Runs I and II and our current outlook as the LHC now moves into higher luminosities. [Preview Abstract] |
Thursday, November 10, 2016 4:21PM - 4:33PM |
D1.00004: Muonic Dark Boson Search at the BABAR Experiment Romulus Godang We report searches for a muonic dark boson coupling only to the second and third lepton families. The existence of the dark boson is probed in e$+$e- events using the full data sample collected by the BABAR experiment. No significant signal is observed. We set a limit on dark-sector coupling parameter, leading to improvements in the current bounds and further constrain the allowed parameter space. [Preview Abstract] |
Thursday, November 10, 2016 4:33PM - 4:45PM |
D1.00005: Soft-gluon Corrections for tZ Production Via Anomalous Couplings Jordon Tyler Campbell, Nikolaos Kidonakis We present calculations for tZ production via an anomalous tqZ coupling. We provide results for the total hadronic cross section for the process pp -$>$ tZ at LHC energies. Included in our calculations are next-to-leading order (NLO) soft gluon corrections, as well as next-to-next-to-leading order (NNLO) soft gluon corrections. We show the size of these NLO and NNLO corrections and their effect on the scale dependence of the cross sections relative to the leading-order results. [Preview Abstract] |
Thursday, November 10, 2016 4:45PM - 4:57PM |
D1.00006: Anomalous Signal Reduction in the CMS ECAL Trigger Gage DeZoort, Tutanon Sinthuprasith, Chris Neu Of the millions of collisions/s produced by the Large Hadron Collider (LHC), only around 1000 events/s can be stored offline. The proper classification of events within the Compact Muon Solenoid (CMS) Experiment's trigger system is therefore crucial in performing standard model measurements and searching for new physics. Occasionally, hadrons produced in the LHC's p-p collisions strike the CMS Electromagnetic Calorimeter (ECAL) barrel APDs, directly ionizing the silicon within them. This process is observed to cause false isolated signals, or spikes, that correspond to a high apparent energy in the detector. The rate of ECAL spike occurrence is proportional to the current LHC luminosity, as well as the number of charged tracks. Therefore, as the LHC pushes into more energetic regimes, these anomalous signals must be removed from the trigger decision. In order to identify and mitigate spikes, a full emulation of the ECAL L1 Trigger was constructed. In our studies, we tuned specific parameters of this L1 emulation in order to study the identification and reduction of anomalous signals, as well as their impact on the trigger rate. [Preview Abstract] |
Thursday, November 10, 2016 4:57PM - 5:09PM |
D1.00007: Description of the Fermilab Mu2e CRV QA/QC Hardware Database Charles Jenkins The Mu2e Experiment, at the Fermi National Accelerator Laboratory, will measure the ratio of the decay of the coherent, neutrinoless conversion of stopped muons into electrons in the field of nucleus to the muon nuclear capture rate. This decay is possible at an undetectable level within the Standard Model; however, many scenarios for physics beyond the Standard Model predict very small but observable rates. The sensitivity of this experiment is a factor of 10$^{4}$ improvement over the current limit. One source of background is Cosmic Rays. A Cosmic Ray Veto (CRV) will be constructed to provide an offline rejection of Cosmic Ray events. Part of the construction process is the cataloging and testing of components used to build the CRV. A Quality Assurance/Quality Control (QA/QC) database will store these results. A brief description of the CRV and a description of the QA/QC database and its interface under development will be presented. [Preview Abstract] |
Thursday, November 10, 2016 5:09PM - 5:21PM |
D1.00008: Multivariate Jet Calibration Using Neural Networks Dayton Grogan The nature of this project stems from a desire to increase the precision of modern large-radius (large-R) jet calibration methods. Currently, methods for calibrating large-R jets utilize, Monte-Carlo derived corrections as a function of jet transverse momentum and pseudorapidity. However, these methods miss the greater variations contained in the fat jet substructure, which can affect detector responses. As such, they may be improved by considering substructure characteristics. To achieve these improvements, this project utilizes Artificial Neural Networks to perform multivariate analysis where it is impractical to expand the current method to incorporate a greater number of variables. Using Google’s TensorFlow machine learning library and APIs to create a shallow, single layer, network we derive weights and biases through supervised learning to accommodate multivariate calibrations. Network training is performed on Monte Carlo data where back propagation allows the network to update its weights by calculating output error to a known truth value provided in the simulated data. Preliminary results with this technique using the same input as traditional calibrations have matched their performance. Moving forward, we are exploring modified networks and parameter optimizations to consider the calibration of other large-R jet properties – particularly jet mass. [Preview Abstract] |
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