22–27 Feb 2010
Jaipur, India
Europe/Zurich timezone

Session

Thursday, 25 February - Data Analysis - Algorithms and Tools

25 Feb 2010, 14:00
Jaipur, India

Jaipur, India

Jaipur, India

Presentation materials

There are no materials yet.

  1. Mr Eric LEITE (Federal University of Rio de Janeiro)
    25/02/2010, 14:00
    Data Analysis - Algorithms and Tools
    Parallel Talk
    The ATLAS online filtering (trigger) system comprises three sequential filtering levels and uses information from the three subdetectors (calorimeters, muon system and tracking). The electron/jet channel is very important for triggering system performance as interesting signatures (Higgs, SUSY, etc.) may be found efficiently through decays that produce electrons as final-state particles....
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  2. Dr David Lawrence (Jefferson Lab)
    25/02/2010, 14:25
    Data Analysis - Algorithms and Tools
    Parallel Talk
    The GlueX experiment will gather data at up to 3GB/s into a level-3 trigger farm, a rate unprecedented at Jefferson Lab. Monitoring will be done using the cMsg publish/subscribe system to transport ROOT objects over the network using the newly developed RootSpy package. RootSpy can be attached as a plugin to any monitoring program to "publish" its objects on the network without...
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  3. Prof. Massimo Di Pierro (DePaul University)
    25/02/2010, 14:50
    Data Analysis - Algorithms and Tools
    Parallel Talk
    mc4qcd is a web based collaboration for analysis of Lattice QCD data. Lattice QCD computations consists of a large scale Markov Chain Monte Carlo. Multiple measurements are performed at each MC step. Our system acquires the data by uploading log files, parses them for results of measurements, filters them, mines the data for required information by aggregating results in multiple forms,...
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  4. Dr Joerg Stelzer (DESY, Germany)
    25/02/2010, 15:15
    Data Analysis - Algorithms and Tools
    Parallel Talk
    At the dawn of LHC data taking, multivariate data analysis techniques have become the core of many physics analyses. TMVA provides easy access to sophisticated multivariate classifiers and is widely used to study and deploy these for data selection. Beyond classification, most multivariate methods in TMVA perform regression optimization which can be used to predict data corrections, e.g....
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  5. Mr Andrey Lebedev (GSI, Darmstadt / JINR, Dubna)
    25/02/2010, 16:10
    Data Analysis - Algorithms and Tools
    Parallel Talk
    Particle trajectory recognition is an important and challenging task in the Compressed Baryonic Matter (CBM) experiment at the future FAIR accelerator at Darmstadt. The tracking algorithms have to process terabytes of input data produced in particle collisions. Therefore, the speed of the tracking software is extremly important for data analysis. In this contribution, a fast parallel track...
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  6. Dr Gregory Schott (Karlsruhe Institute of Technology), Dr Lorenzo Moneta (CERN)
    25/02/2010, 16:35
    Data Analysis - Algorithms and Tools
    Parallel Talk
    RooStats is a project to create advanced statistical tools required for the analysis of LHC data, with emphasis on discoveries, confidence intervals, and combined measurements. The idea is to provide the major statistical techniques as a set of C++ classes with coherent interfaces, which can be used on arbitrary model and datasets in a common way. The classes are built on top of RooFit,...
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  7. Dr Michael D. McCool (Intel/University of Waterloo)
    25/02/2010, 17:00
    Data Analysis - Algorithms and Tools
    Parallel Talk
    A great portion of data mining in a high-energy detector experiment is spent in the complementary tasks of track finding and track fitting. These problems correspond, respectively, to associating a set of measurements to a single particle, and to determining the parameters of the track given a candidate path [Avery 1992]. These parameters usually correspond to the 5-tuple state of the model...
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