'Eta 0' diaporamas de présentation

WP8: ReteQuarkonii

407 views • 40 slides

Jet Energy Scale

Jet Energy Scale. March 31, 2009. Jet energy vs parton energy. Eta-dependent corrections : even calorimeter response Multiple interactions : garbage from extra ppbar events in the same BC Absolute energy scale : conversion from calo measurement to underlying jet

451 views • 30 slides

OUTLINE

First study of sensitivity of CMS detector to neutrinoless decay t ? m+m-m- Santinelli Roberto - INFN Perugia CERN ,1 February 2002. OUTLINE. The chanel t ?3m Tau lepton production at LHC Study of the signal Study of background Observability of the signal and exclusion limits.

410 views • 26 slides

Archana Sharma, Suman Beri Panjab University Chandigarh

Updates on the RPC trigger efficiency work with data driven method and Muon trigger efficiencies with Tag & Probe. Archana Sharma, Suman Beri Panjab University Chandigarh. Plan of talk. RPC trigger efficiencies with Data Driven method. Analysis features Brief description of method

415 views • 24 slides

Event Shape Analysis in minimum bias pp collisions in ALICE.

Event Shape Analysis in minimum bias pp collisions in ALICE. Antonio Ortiz Velasquez for the ALICE Collaboration. 5 th Workshop on High Pt Physics at LHC, 27.September.2010. ESA. Outline. 1. Introduction. 2. Event Shapes at Hadron Colliders.

205 views • 20 slides

MC vs Data comparison

MC vs Data comparison. Data (LHC09d - pass4) MC (LHC10a8). SPD vertex resolution - MC. run 104867. Vertex reconstuction. MC Data. run 104867. nb. TPC clusters / track. MC. Data. run 104867. |dcar| < 3 cm |dcaz| < 3 cm chi2 / clust < 4 pt > 0.15 GeV/c. |eta| < 0.8. |eta| < 0.8.

287 views • 17 slides

JET90 event displays run 198206 L ~120e30

JET90 event displays run 198206 L ~120e30. Mary Convery Run IIb Physics Priorities and Triggers 6/21/05. OK. Ntow=43 E T =91 eta=19, phi=22. Ntow=58 E T =111 eta=3, phi=11. *. OK. Ntow=42 E T =91 eta=2, phi=6. *. Ntow=62 E T =105 eta=3, phi=5. *. Ntow=51

274 views • 17 slides

18 orbits in Eastern Pacific 10-22 August reprocessed by ARGANS using : -EAFFOV -only AFFOV

212 views • 15 slides

Parameter Learning in Markov Nets

Parameter Learning in Markov Nets. Dhruv Batra , 10-708 Recitation 11/13/ 2008. Contents. MRFs Parameter learning in MRFs IPF Gradient Descent HW5 implementation. Semantics. Priors on edges Ising Prior / Potts Model Metric MRFs. Metric MRFs. Energies in pairwise MRFs. HW4.

239 views • 15 slides

ITTF Tracking Efficiency

ITTF Tracking Efficiency. 200GeV AuAu central, Minbias data run321,274. Lots of help from ITTF code developers and J. Lauret. Outline . Selection of track (cuts) in analysis Comparison between ITTF and TPT tracks Multiplicity (centrality cuts) Nftpnts distribution Global dca distribution

235 views • 11 slides

Barrel PreShower Detector (towards understanding)

Barrel PreShower Detector (towards understanding). Where Jaro left.. Some more info for completeness Back to Barrel-PSD correlation Fixing from observations Looking back how mapping is done Do we understand?. Plot for correlation of RefMultiplicity and PSDNhit. What is this straight band?.

182 views • 11 slides