A5107143223- Particle physics theoretical and experimental studies
- High-Energy Particle Collisions Research
- Quantum Chromodynamics and Particle Interactions
- Particle Detector Development and Performance
- Dark Matter and Cosmic Phenomena
- Computational Physics and Python Applications
- Cosmology and Gravitation Theories
- Neutrino Physics Research
- Black Holes and Theoretical Physics
- Astrophysics and Cosmic Phenomena
- Distributed and Parallel Computing Systems
- Medical Imaging Techniques and Applications
- Particle Accelerators and Free-Electron Lasers
- Radiation Detection and Scintillator Technologies
- Superconducting Materials and Applications
- Advanced Data Storage Technologies
- Atomic and Subatomic Physics Research
- advanced mathematical theories
- Muon and positron interactions and applications
- International Science and Diplomacy
- Particle accelerators and beam dynamics
- Scientific Computing and Data Management
- Big Data Technologies and Applications
- Digital Radiography and Breast Imaging
- Advanced NMR Techniques and Applications
University of British Columbia
2016-2025
Okanagan University College
2024
The University of Adelaide
2015-2023
University of Bergen
2023
University of Geneva
2012-2022
Deutsches Elektronen-Synchrotron DESY
2022
Otsuka (Japan)
2020
Ochanomizu University
2020
University of Illinois Urbana-Champaign
2019
Oklahoma State University
2019
Based on the established task of identifying boosted, hadronically decaying top quarks, we compare a wide range modern machine learning approaches. Unlike most methods they rely low-level input, for instance calorimeter output. While their network architectures are vastly different, performance is comparatively similar. In general, find that these new approaches extremely powerful and great fun.
Recent literature on deep neural networks for tagging of highly energetic jets resulting from top quark decays has focused image based techniques or multivariate approaches using high-level jet substructure variables. Here, a sequential approach to this task is taken by an ordered sequence constituents as training inputs. Unlike the majority previous approaches, strategy does not result in loss information during pixelisation calculation high level features. The classification method...
Multivariate techniques based on engineered features have found wide adoption in the identification of jets resulting from hadronic top decays at Large Hadron Collider (LHC). Recent Deep Learning developments this area include treatment calorimeter activation as an image or supplying a list jet constituent momenta to fully connected network. This latter approach lends itself well use Recurrent Neural Networks. In work applicability architectures incorporating Long Short-Term Memory (LSTM)...
The CDF II level 1 track trigger system reconstructs charged tracks in the plane transverse to beam direction. electronics uses hit data from 4 axial layers of central outer tracking chamber, and has been recently upgraded include complementary information 3 stereo layers. Together with existing it provides improved fake rejection at 1. In addition, high resolution segment is delivered Level 2 processors, where software algorithms perform three-dimensional reconstruction. 3D-tracks are...
(2000). Indeterminate problems: exploring the potential of problem-based learning in conservation education. Studies Conservation: Vol. 45, Contributions to Melbourne Congress, 10-14 October 2000. Tradition and Innovation: Advances Conservation, pp. 114-117.
We present searches for pair-production of fourth generation tprime quarks in their decays to Wq. analyse 4.6 fb-1 and 4.3 data collected by the CDF D0 detectors, respectively, at Fermilab Tevatron collider a centre-of-mass energy sqrt s = 1.96 TeV. reconstruct mass heavy quark perform two-dimensional-fit observed (HT, Mreco) distributions discriminate new physics signal from standard model backgrounds. As no significant excess events is observed, we exclude fourth-generation with below 335...
We briefly present the eXtremely Fast Tracker stereo track upgrade for CDF Level 2 trigger system. This enabled full 3D reconstruction at of 3-Level online triggering Using information provided by layers Central Outer Tracker, we can decrease rate due to fake tracks requiring be consistent with a single vertex in all three dimensions but also using "point" various detector components. will discuss effectiveness algorithm achieving reduced rates high efficiencies during luminosity running.
<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <?Pub Dtl=""?>The CDF II detector uses dedicated hardware to identify charged tracks that are used in an important class of level 1 trigger decisions. Until now, this identified track segments based on patterns hits only the axial sense wires tracking chamber and determined transverse momentum candidates from segments. This identification is efficient but produces rates grow rapidly with...
We present recent results on top quark pair production cross section and forward-backward asymmetry at the Tevatron. Three new measurements from CDF one measurement DO are presented that utilize full dataset available. A combination gives a ttbar of sigma_ttbar = 7.83 + 0.46-0.45 (stat) 0.64-0.53 (syst) +-0.48 (lumi). The for is found to be 7.0 +- 0.3 0.4 (lumi) pb giving total uncertainty 9%, very close current best theoretical predictions. It important measure in as many different channels...
Measurements are presented from proton-proton collisions at centre-of-mass energies of √ s = 0.9, 2.36 and 7 TeV recorded with the ATLAS detector LHC.Events were collected using a single-arm minimum-bias trigger.The charged-particle multiplicity, its dependence on transverse momentum pseudorapidity relationship between mean multiplicity measured.Measurements in different regions phase-space shown, providing diffraction-reduced measurements as well more inclusive ones.The observed...