Atlas Physics studies

Transcription

1 Atlas Physics studies M. Saleem (university of Oklahoma) (DOE Review) Feb. 01, /01/2010 M. Saleem (University of Oklahoma) 1

2 Outline Introduction Top Cross-section study Atlas Data arrival and Study Performace Study Fake rates for Btagging validation Cosmic ray & MinBias study 02/01/2010 M. Saleem (University of Oklahoma) 2

3 Introduction The focus of my talk is on the Physics/software activities and involvement of the Oklahoma group based in CERN. Including Myself (+ 2 GS), there are 3 people based in CERN for this effort. Focus of our activities during the year 2009 was as follow: Finished ttbar cross-section studies on MC ATLAS INTERNAL Note approved. Started our activities to be ready on expected ATLAS data (spring 10) for the C.o.M 7 TeV. Activity on Atlas Data in (Nov.- Dec) Work on the Btagging performance Mistag rate measurements Btag Perfromance Mangement Board involvement. (Saleem) MC validation work (Dilip) MiniBias Study (Razzak) Future Plans. 02/01/2010 M. Saleem M. (University Saleem, OU of Oklahoma) 3

4 Why top pair cross-section: σ(tŧ) is an inclusive quantity that allows: Test the SM at the LHC energies (LHC is a top factory), Compare the experimental measurement with the QCD NLO predictions, Extract the top quark mass and compare with theory measurements. Probe new Physics, like anomalous ttbar production rate, compare cross-section in different decay channels, Well understood ttbar selection can be used to study the top properties. Background for Higgs, SUSY and new phenomena searches.. Top Decay in the SM: BR(t->wb)~100% Final state driven by the w decay modes. 02/01/2010 M. Saleem M. (University Saleem, OU of Oklahoma) 4

5 Analysis strategy: At C.o.M = 10TeV Selection: Lepton:e or µ (only one lepton: Pt > 20 GeV ; η <2.5 MET > 20 GeV At least 4 jets > 20 GeV 3 out of 4 jets> 40 GeV; η <2.5 : e + jets channel: 6.01±0.04% S/B (after preselection) = 1.6 µ + jets channel:7.23±0.04% S/B (after preselection) = 1.5 (at 50 pb -1 ) 1. Number of signal events is fitted to a Likelihood distribution build out of 8 variables: chosen so that there distribution data is expected to be accurately re -produced by MC, They have either minimal or no dependence on JES (biggest systematic error) And they are not highly corelated. These variables are optimized for best statistical error with 50 pb -1 µ + jets channel e + jets channel 02/01/2010 M. Saleem (University of Oklahoma) 5

6 Analysis Results and Approval: For µ + jets channel at 50 pb 1 Analysis is Approved as Atlas Internal Note For e + jets channel at 50 pb 1 02/01/2010 M. Saleem (University of Oklahoma) 6

7 Plans on Data : Now we are getting ready For this analysis to be published as one of the early papers. We expect to have enough data this year at 7 TeV C.o.M Work already been started for tunning up our tools on 7 TeV MC samples. 02/01/2010 M. Saleem (University of Oklahoma) 7

8 Btagging: Mistag Rate Measurement People involved:, A. Khanov(OSU) Major sources that lead to tagging of the light jets: finite resolution of the reconstructed track/vertex parameters Tracks/vertices from the long-lived particles that decay in jets We cannot measure the mis-tagging rate directly on data -- need 100 % pure light jet sample, which is not possible due to the presence of heavy flavor (b, c jets) in inclusive sample. Two different approaches to deal with this issue: : To a good approximation the resolution of the track impact parameter significance or secondary vertex significance (DLS) is perfectly symmetric arround zero, and the contribution from long-lived particles can be effectively suppressed, the negative tagging rate should be close to the positive tagging rate. By looking at tracks with negative DCAS or vertices with negative DLS, we can estimate the mis-tag rate on a sample with heavy flavor admixture. 02/01/2010 M. Saleem M. (University Saleem, OU of Oklahoma) 8

9 Btagging: Mistag Rate Measurement is a distribution of tag weights w for a given flavor of jets, put in a histogram of N bins and normalized to 1. Split the sample into a pair of samples with different heavy flavor composition. Assume that distributions of tag weights for b-, c- jets are known (e.g; b from a measurement in data and c from b+c/b evaluated on MC). The light tag weight distribution is unknown, but assumed to be same in in both samplesif tag weight distributions consists of N bin, have 2N equations for the number of events in each bin for each of the 2 samples and N+3 unknowns (b-, c-fractions in each of the 2 samples and N bins of the light tag weight) If enough bins, can resolve this system and find the b-, c fraction and mistag rate at once by assuming that heavy flavor fraction is already known with infinite accuracy. 02/01/2010 M. Saleem M. (University Saleem, OU of Oklahoma) 9

10 Btagging: Mistag Rate Measurement Measuement True 02/01/2010 M. Saleem M. (University Saleem, OU of Oklahoma) 10

11 Road towards Real Data: End of Nov. and early Dec Atlas collected some data on 900 GeV and 2.36 TeV (for short time). 02/01/2010 M. Saleem (University of Oklahoma) 11

12 Road towards Real Data: End of Nov. and early Dec Atlas collected some data on 900 GeV and 2.36 TeV (for short time). Data: , MC: events. (with cone4 Jet algorithm) 6595 jets in data (~2.4 %) ; jets in MC (~2.0%) Lifetime signed IP Lifetime IP significance Entries/1.6µm Entries/ 0.1 d0(/pv) signed w.r.t jet axis d0/σ(/pv) signed w.r.t jet axis 02/01/2010 M. Saleem (University of Oklahoma) 12

13 SoftwarePerfomance Management Board Saleem is memeber of the Performance Management Board (PMB), representing the Combined Reconstruction for the Flavor tagging working group. (Since 2009 Summer). The PMB is responsible for ensuring that the cpu and memory usage of ATLAS jobs is compatible with the processing requirements and the production system constraints. This compatibility will be maintained throughout ATLAS detector commissioning, initial collisions, and design luminosity involving pile-up and cavern backgrounds. This responsibility includes: The development of, and the incorporation of existing, monitoring and diagnostic tools into the ATLAS software development and production environments (In conjunction with b-tagging specific algorithms, tools..). Memory(MB) CPU(ms) Btag ON Btag OFF Delta Fraction of Off Btag was ON Btag was Off One special busy event 02/01/2010 M. Saleem (University of Oklahoma) 13

14 Validation effort One of GS (Dilip) is involved in the top working group Software release Validation work (Since 2009 September). Physics Validation is part of the new ATLAS software Release Validation scheme which was started in March 2007 with the aim of greatly improving the speed and thoroughness of ATLAS software validation. Results of Physics validation studies are presented in Physics Validation group meetings. This Dataset: valid t1_mcatnlo_jimmy.recon.aod.panda_e380_s593_r916 Reference Dataset: valid t1_mcatnlo_jimmy. recon.aod.panda_e380_s593_r896_test Electron Efficiency (Et) Muon Efficiency (Et) 02/01/2010 M. Saleem (University of Oklahoma) 14

15 MiniBias Study One of GS (Razzak) has recently started working on the MiniBias study using the 900 GeV data (taken during Nov Dec. 2009) This will be part of Ph.D. thesis Detection Efficiency of the Atlas pixel Detector using sensor overlap region with cosmics ray data MinBias studies in low pt regions Pt<500MeV. including efficiency measurements of silicon vs TRT. For tracks migrating from low Pt region to High Pt region due to the mis-reconstruction of tracks. 02/01/2010 M. Saleem M. (University Saleem, OU of Oklahoma) 15

16 The End 02/01/2010 M. Saleem (University of Oklahoma) 16

17 02/01/2010 M. Saleem (University of Oklahoma) 17

18 Mistag Rate: Negative Tag Method Use IP based (IP3D) and secondary vertex based (SV1). Signed DCA/DLS significance for light and b-jets & weights distribution Negative tail is for tracks from b-decay due to wrong IP Sign for tracks Close to jet axis positive tail is due to Tracks from b-decays, used to identify b-jets. DLS IP3D SV1 Tracks from light jets: almost symmetric, positive tail is due to long-lived particles M. Saleem (University of Tag weight Oklahoma) 18 01/27/2010

19 Correction Factors (K ll ) Misreco Conversions Interactions Hyperons K-short Residual HF We assign systematic uncertainty on the value of K ll due to material and V0 s by removing the jets with tracks which are known to originate due to above mentioned sources and then re-evaluating the correction factor. Misreco Conversions Interactions Hyperons K-short Residual HF M. Saleem (University of Oklahoma) 19 01/27/2010

20 Measured and True Mistag rate M. Saleem (University of Oklahoma) 20 01/27/2010

21 Measured and True Mistag rate M. Saleem (University of Oklahoma) 21 01/27/2010

22 Systematic Error for the Method I For IP3D taggers with two different Operating points. For SV1 taggers with two different Operating points. M. Saleem (University of Oklahoma) 22 01/27/2010

23 Statistical and Systematic uncertainty (II) M. Saleem (University of Oklahoma) 23 01/27/2010

24 Statistical and Systematic uncertainty (II) M. Saleem (University of Oklahoma) 24 01/27/2010