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1 AMY Detector (eighties) A rather compact detector.

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Presentation on theme: "1 AMY Detector (eighties) A rather compact detector."— Presentation transcript:

1 1 AMY Detector (eighties) A rather compact detector

2 2 LEP/LHC at CERN - Geneva Particle Accelerators usual types electron vs anti-electron proton vs proton proton vs anti-proton electron vs proton

3 3 L3

4 4 e + e - Cross Sections (for example, LEP experiments in 1989~2000) They represents the probability of producing specific scattering events Finding new physics largely depends on how well we distinguish signals from background processes

5 5 Branching Ratios m f 2 Decays to bb dominant Branching Ratios of Higgs (e.g.)

6 6 Higgs Signature (Expected) 4 jets Missing Energy 2 leptons(e, μ) +2 jets ν ν 2 taus(τ) +2 jets τ τ H bb H(Z)bb(qq) H bb Z qq Z νν Z(H)τ τ Z l + l -

7 7 Event Display

8 8

9 9 online system multi-level trigger filter out background reduce data volume level 1 - special hardware 40 MHz ( 40 TB/sec ) level 2 - embedded processors level 3 - PCs 75 KHz (75 GB/sec) 5 KHz (5 GB/sec) 100 Hz ( 100 MB/sec ) data recording & offline analysis One of the four LHC detectors: Experiments from 2007 Particle collisions in nanoseconds

10 10 Higgs Particle in CMS (imagination)

11 11 Why HEP Data Grid and e-Science? The Grid is rapidly being recognized as one of the most promising application of information technology. High Energy Physics (HEP), as one of the most immediate applications, needs, in its nature, - A new next-generation information technology in very high-speed networking, - massive data distribution and processing, - and intensive computing power and data storage. To meet these needs, "HEP Data Grid and we do e-Science

12 12 CERN Experiments: Example The LHC Detectors CMS ATLAS LHCb ~6-8 PetaBytes / year ~10 8 events / year

13 13 Courtesy P. Sphicas/ICHEP2002 and CMS CMS at LHC

14 14 Concepts of Linear Collider in 2010s another option

15 15 In the future Production of data ( > tens of PB/year) Processing of data and sharing with thousands of people for analysis Transferring data ( ~ Tera bit seconds ) Analysis becomes very complex but should be made easy for users GRID / High BW Networks/ Supercomputing In fact, related technologies and economic factors are in favor of us to make this scenario real

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