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Co-evolution of carbon cycle and air quality fluxes constrained by CMS-Flux and MOMO-Chem assimilation systems
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The Reaction Pi-p ---> Pi+Delta- at CMS Energies 1640-1760 MeV
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Pi-p Elastic Scattering in the CMS Energy Range 1400-2000 MeV
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CMS Services for Micros-Supporting the IBM PC/XT at SLAC
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Analysis of Reaction Products from e+e- at 6 GeV (CMS)
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Using Fullscreen CMS at CERN
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Development of a Lightweight Silicon Pixel Detector for CMS to Search for New Physics in the Top Quark Sector
The discovery of a Higgs boson at the Large Hadron Collider (LHC) is one of the greatest achievements of experimental particle physics and a triumph for theoretical physics, which culminates in the very successful standard model (SM). Currently the LHC collider provides particle collisions at highest possible energies of $\sqrt{s}=13$ TeV, opening a new energy domain. Little Higgs models predict a heavy top quark partner, T, which would cancel the aforementioned top quark loop contributions to the Higgs boson mass. This particle is predicted to have a mass near the TeV scale. We search for a "vector-like" top partner which is an electroweak singlet and has vector couplings to W and Z bosons.
Studies of the FBK Low-Gain Avalanche Detectors for the CMS Endcap Timing Layer
• A detection efficiency of almost 100 percent observed throughout the surface of UFSD2 FBK 2x8 sensor • CFD Fraction between 30 and 50 percent yielded best time resolution measurements • Time resolution between 30 - 50 ps observed for the W5 FBK 3x1 mm2 sensors for different radiation fluences and bias voltages • A functional LGAD characterization system has been setup in the Testbeam Facility and Silicon Detector Facility at Fermilab
Test Beam Analysis of Silicon Microstrip Module with Transverse Momentum Discrimination for CMS HL-LHC
The front end chip of the 2S modules (CBC) is capable of reconstructing short track segments correlating the hits of the two closely spaced silicon microstrip sensors constituting a module. These track segments can be used at the level 1 trigger to reconstruct complete tracks with a transverse momentum above 2 GeV/c keeping the trigger selection discrimination very efficient. A prototype mini-module was produced with the latest CBC version and tested before and after irradiation at the Fermilab Test Beam Facility (FTBF) during 3 test-beam campaigns.
Speeding up Particle Track Reconstruction in the CMS Detector using a Vectorized and Parallelized Kalman Filter Algorithm
Building particle tracks is the most computationally intense step of event reconstruction at the LHC. With the increased instantaneous luminosity and associated increase in pileup expected from the High-Luminosity LHC, the computational challenge of track finding and fitting requires novel solutions. The current track reconstruction algorithms used at the LHC are based on Kalman filter methods that achieve good physics performance. By adapting the Kalman filter techniques for use on many-core SIMD architectures such as the Intel Xeon and Intel Xeon Phi and (to a limited degree) NVIDIA GPUs, we are able to obtain significant speedups and comparable physics performance. New optimizations, including a dedicated post-processing step to remove duplicate tracks, have improved the algorithm's performance even further. Here we report on the current structure and performance of the code and future plans for the algorithm.
DAQ and Level-1 Track Finding for the CMS HL-LHC Upgrade
The LHC will be upgraded to the High Luminosity LHC (HL-LHC) in the late 2020s in order to reach an instantaneous luminosity as high as 71034 cm
GNN-based end-to-end reconstruction in the CMS Phase 2 High-Granularity Calorimeter
We present the current stage of research progress towards a one-pass, completely Machine Learning (ML) based imaging calorimeter reconstruction. The model used is based on Graph Neural Networks (GNNs) and directly analyzes the hits in each HGCAL endcap. The ML algorithm is trained to predict clusters of hits originating from the same incident particle by labeling the hits with the same cluster index. We impose simple criteria to assess whether the hits associated as a cluster by the prediction are matched to those hits resulting from any particular individual incident particles. The algorithm is studied by simulating two tau leptons in each of the two HGCAL endcaps, where each tau may decay according to its measured standard model branching probabilities. The simulation includes the material interaction of the tau decay products which may create additional particles incident upon the calorimeter. Using this varied multiparticle environment we can investigate the application of this reconstruction technique and begin to characterize energy containment and performance.