Advanced Computing and Analysis Techniques in Physics Research

Advanced Computing and Analysis Techniques in Physics Research

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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 architecturesDELPHI Collaboration, Physics Utters B 479, 89 (2000). ... Sj0strand, T., PYTHIA 5.7 and JETSET 7.4 Physics and Manual CERN-TH.71 12/93, (1993). ... DELPHI Collaboration, DELPHI Note 89-67 and 89- 68 PROG 142 and 143 (1989). ... and using the neural Table 2. cross section results with statistical errors for different center-of- mass energies (ECM) of the final particle and p, of the initial particle 82.

Title:Advanced Computing and Analysis Techniques in Physics Research
Author: Pushpalatha C. Bhat, Matthias Kasemann
Publisher:American Inst. of Physics - 2001-09-21

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