Advanced Computing and Analysis Techniques in Physics Research: VII International Workship; Acat 2000
by Kasemann, M.; Bhat, Pushpalatha C.Format: Hardcover
Pub. Date: 2001-09-01
Publisher(s): Amer Inst of Physics
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Summary
Over the next decade or two, an impressive array of scientific instruments at the Tevatron, RHIC (Relativistic Heavy Ion Collider) and LHC (Large Hadron collider), LIGO (Laser Interferometer Gravitational Observatory) and SDSS (Sloan Digital Sky Survey), to name a few, will usher in the most comprehensive program of study of the fundamental forces of nature and the structure of the universe. Major discoveries are anticipated. But, it is our conviction that the pace of discoveries will be severely impeded unless a concerted effort is made to deploy and employ advanced computing techniques to handle, process and analyze the unprecedented amounts of data. The workshop followed four main tracks: Artificial Intelligence (neural networks and other adaptive multivariate methods); Innovative Software Algorithms and Tools; Symbolic Problem Solving; and Very Large Scale Computing. The workshop covered applications in high energy physics, astrophysics, accelerator physics and nuclear physics. Topics included are: uses of C++ in scientific computing, large scale simulations, advanced analysis environments, worldwide computing; artificial intelligence: online application of neural networks, applications in data analysis, theoretical aspects innovative software algorithms and tools: online monitoring and controls, physics analysis and reconstruction algorithms, pattern recognition techniques, common libraries, grid and distributed computing techniques; symbolic problem solving: Freynman diagram algorithms and tools, symbolic manipulation via function objects, symbolic techniques for Feynman diagrams, multi-loop calculations and results. very large scale computing: online monitoring and controls, analysis farms and DAQ systems, grid architectures
Table of Contents
| Preface | p. xi |
| Opening Remarks | p. xv |
| Committees | p. xvii |
| Plenary Sessions | |
| Information Technology Research: Transforming Our Future | p. 7 |
| Speaking C++ As a Native | p. 11 |
| Advanced Analysis Methods in High Energy Physics | p. 22 |
| Statistical Techniques in High Energy Physics | p. 31 |
| The H1 Neural Network Trigger Project | p. 36 |
| Feynman-Diagram Evaluation in the Electroweak Theory with Computer Algebra | p. 45 |
| Grid Computing | p. 51 |
| Large-Scale Molecular Dynamics Simulations of Materials on Parallel Computers | p. 57 |
| Parallel Sessions | |
| Artificial Intelligence | |
| Online Applications of Neural Networks | |
| Momentum Reconstruction and Triggering Suggested for the ATLAS Detector | p. 67 |
| Neural Network Real-Time Event Selection for the DIRAC Experiment | p. 70 |
| Intelligent Preprocessing for Neural Networks in the H1 Experiment | p. 73 |
| An Electronic System for Simulation of Neural Networks with a Microsecond Real-Time Constraint | p. 76 |
| Applications in Data Analysis I | |
| Selection of W-Pair-Production in DELPHI with Feed-Forward Neural Networks | p. 80 |
| Use of Neural Networks in a Search for Single Top Quark Production at DO | p. 83 |
| A Hybrid Training Method for Neural Energy Estimation in Calorimetry | p. 86 |
| Principal Component Analysis for Neural Electron/Jet Discrimination in Highly Segmented Calorimeters | p. 89 |
| Applications in Data Analysis II | |
| Particle Identification at DO Using Neural Networks | p. 92 |
| Vertex Reconstructing Neural Network at the ZEUS Central Tracking Detector | p. 95 |
| Neural Networks for Higgs Physics | p. 98 |
| Top Quark Mass Measurements Using Neural Networks | p. 101 |
| Theoretical Aspects and Other Topics | |
| Clopper-Pearson Bounds from HEP Data Cuts | p. 104 |
| Experimenting with Rule Induction Algorithms in HEP Data Analysis | p. 107 |
| Looking for Instanton-Induced Processes at HERA Using a Multivariate Technique Based on Range Searching | p. 110 |
| A Self-Organizing Neural Network for Job Scheduling in Distributed Systems | p. 113 |
| Innovative Software Algorithms and Tools | |
| Online Monitoring and Controls | |
| Tailorable Software Architectures in the Accelerator Control System Environment | p. 119 |
| Online Modeling of the Fermilab Accelerators | p. 122 |
| A Beamline Matching Application Based on Open Source Software | p. 125 |
| Physics Analysis and Reconstruction Algorithms | |
| Sleuth: A Quasi-Model-Independent Search Strategy for New High p[subscript T] Physics | p. 128 |
| Fast Tracking in Hadron Collider Experiments | p. 130 |
| More Performance Results and Implementation of an Object-Oriented Track Reconstruction Model in Different OO Frameworks | p. 133 |
| Pattern Recognition Techniques | |
| Simultaneous Tracking and Vertexing with Elastic Templates | p. 137 |
| Vertex Finding Prior to Tracking in Magnetic Field | p. 140 |
| Singular Value Decomposition to Simplify Features Recognition Analysis in Very Large Collection of Images | p. 143 |
| The Hermite Polynomials in Problem of the Searching for Position of the Global Maximum | p. 146 |
| Common Libraries | |
| Event Bookkeeping for CLEO-3 | p. 149 |
| KID-KLOE Intergrated Dataflow | p. 152 |
| A Component-Based Approach to Scientific Workflow Management | p. 155 |
| Grid and Distributed Computing Techniques | |
| Protocols and Services for Distributed Data-Intensive Science | p. 161 |
| Simulating Distributed Systems | p. 164 |
| Symbolic Problem Solving | |
| Feynman Diagram Algorithms and Tools | |
| HELAC-PHEGAS: Automatic Computation of Helicity Amplitudes and Cross Sections | p. 169 |
| O'Mega: An Optimizing Matrix Element Generator | p. 173 |
| A Feynman Graph Selection Tool in GRACE System | p. 176 |
| Symbolic Manipulation via Function Objects | |
| A Library of Function Classes | p. 179 |
| FunctionalObjects.h: Using Symbolic Syntax in C++ Programs | p. 182 |
| Large-Scale Symbolic Programming with GiNaC | p. 185 |
| Symbolic Techniques for Feynman Diagrams | |
| Optimization of Symbolic Evaluation of Helicity Amplitudes | p. 190 |
| A Feynman Diagram Analyser DIANA--Graphic Facilities | p. 193 |
| The Tensor Reduction and Master Integrals of the Two-Loop Massless Crossed Box | p. 196 |
| Multi-loop Calculations and Results | |
| Gauge Invariant Classes of Feynman Diagrams and Applications for Calculations | p. 199 |
| A Parallel Version of Form 3 | p. 202 |
| Two-Loop Calculations in the MSSM with FeynArts | p. 205 |
| Very Large Scale Computing | |
| Online Monitoring and Controls | |
| CompHEP-PYTHIA Interface: Integrated Package for the Collision Events Generation Based on Exact Matrix Elements | p. 211 |
| Integration of GRACE and PYTHIA | p. 214 |
| Algorithm for Computing Excited States in Quantum Theory | p. 217 |
| Simple Scaling for Faster Tracking Simulation in Accelerator Multiparticle Dynamics | p. 220 |
| Adaptive Mesh Simulations of Astrophysical Detonations Using the ASCI Flash Code | p. 223 |
| Analysis Farms and DAQ Systems | |
| Matrix Distributed Processing and FermiQCD | p. 226 |
| A Terabyte Analysis Machine for Sdss Data | p. 229 |
| A Large Linux-PC Farm for Online Event Reconstruction and Data Management at Hera-B | p. 232 |
| Client and Event Driven Data Hub System at CDF | p. 235 |
| The Compass Computing Farm Project | p. 238 |
| Grid Architectures | |
| A Data Grid Prototype for Distributed Data Production in CMS | p. 241 |
| Object Level Physics Data Replication in the Grid | p. 244 |
| SAM for D0--A Fully Distributed Data Access System | p. 247 |
| The Control Actions Framework | p. 250 |
| Poster Session | |
| EMS: A Framework for Data Acquisition and Analysis | p. 255 |
| Effects of Limited Resources in 3D Real-Time Simulation of an Extended ECHO Complex Adaptive System Model | p. 258 |
| High Performance Visual Display for HENP Detectors | p. 261 |
| Root OO Model to Render Multi-level 3-D Geometrical Objects via an OpenGL | p. 264 |
| A C++ Particle Data Table Interface | p. 267 |
| Parallel Computing on a PC Cluster | p. 270 |
| Some Advance Methods of Statistical Analysis for the Muon g-2 Experiment at BNL | p. 273 |
| Analytical Calculation of Heavy Baryon Correlators in NLO of Perturbative QCD | p. 277 |
| Summaries of Recent Computer-Assisted Feynman Diagram Calculations | p. 280 |
| Working Groups and Panel Discussions | |
| Use of C++ in Scientific Computing | |
| Experiences Reviewing Scientific C++ Code | p. 287 |
| Reflections on a Decade of Object-Oriented Programming in Accelerator Physics | p. 291 |
| C++ in Scientific Application: A Case Study | p. 294 |
| Advanced Analysis Environments | |
| The Development of the Root Data Analysis System | p. 297 |
| Analysis Environment Challenges | p. 301 |
| Large-Scale Simulations | |
| CDF Monte Carlo'2000 | p. 307 |
| Computational Challenges for Large-Scale Astrophysics Calculations | p. 310 |
| DZero Monte Carlo-Simulation | p. 313 |
| Large-Scale Simulations of Clusters of Galaxies | p. 316 |
| CMS Monte Carlo Status, Performance and Future Plans | p. 319 |
| Large-Scale Cluster Surveys and Distributed Computing | p. 323 |
| Simulation Packages in Accelerator Studies for the v Factory | p. 326 |
| Atlas Simulation: Status, Performance, and Future Plans | p. 329 |
| Rapporteur Talks | |
| Artificial Intelligence | p. 335 |
| Status of Neural Network Hardware in High Energy Physics | p. 338 |
| Innovative Software Algorithms and Tools Parallel Sessions Summary | p. 342 |
| Panel Discussion: C++ in Scientific Computing | p. 345 |
| Advanced Analysis Environments--Summary | p. 348 |
| Summary: Panel Discussion on Large-Scale Astrophysical Calculations | p. 351 |
| Summary of HEP and Accelerator Physics Part of Panel Discussion on Large-Scale Simulations | p. 355 |
| Worldwide Computing Working Group Summary | p. 357 |
| Perspectives on the Workshop Series | p. 360 |
| Technology Show | p. 367 |
| Participating Companies | p. 369 |
| More of ACAT 2000 in Pictures | p. 375 |
| Workshop Program | p. 389 |
| Workshop Participants | p. 399 |
| ACAT Participants Photograph | p. 403 |
| Author Index | p. 405 |
| Table of Contents provided by Syndetics. All Rights Reserved. |
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