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Inclusive SUSY Searches with E T miss -Jet at CMS

Inclusive SUSY Searches with E T miss -Jet at CMS. Taylan Yetkin Çukurova University (on behalf of CMS Collaboration) Physics at LHC Conference, Kraków July 2006. OUTLINE SUSY Signal Signature Event Simulation and Event Reconstruction Data Cleanup QCD Data and Cleanup

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Inclusive SUSY Searches with E T miss -Jet at CMS

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  1. Inclusive SUSY Searches with ETmiss-Jet at CMS Taylan Yetkin Çukurova University (on behalf of CMS Collaboration) Physics at LHC Conference, Kraków July 2006 OUTLINE SUSY Signal Signature Event Simulation and Event Reconstruction Data Cleanup QCD Data and Cleanup W/Z + multi-jets Background Indirect Lepton Veto Analysis Path and Results Systematic Uncertainties SUSY Reach with 5 Sigma Conclusions T.Yetkin, Phys.@LHC Conference, Krakow

  2. SUSY Signal Signature • Squarks/gluinos are expected to have large production rates at LHC[1]. • CMS agreed on fourteen benchmark points [2] . • Test point LM1 (same as post-WMAP benchmark B’) is used [ m(gluino) > m(squark)] • Signal signature is chosen as multiple jets and large missing transverse energy (ETmiss). LM1 Production Cross-Section (%) (~50% of  comes from pp~g~qL,R process) T.Yetkin, Phys.@LHC Conference, Krakow

  3. Event Simulation and Reconstruction Event Generation: • Signal (mSUGRA LM1) with ISASUGRA (7.69) and PYTHIA(6.225). [x-sec is ~50 pb] • Backgrounds (w/ PYHTIA, some for validation/comparison w/ ALPGEN) • top-antitop pair • single top • QCD di-jet • W(ℓ)+ jets • Z(ℓ ℓ,  ) + jets • WW/ZZ/WZ + jets Detector Simulation and Event Reconstruction: • CMS Software Tools • Geant4 Based Detector Simulation Software-OSCAR [3] • Detailed Reconstruction software-ORCA [4] • Jets and ETmiss are defined and calculated by using calorimeter towers and clustering algorithms [5]. • Fast simulation software-FAMOS [6] (for the scan study) T.Yetkin, Phys.@LHC Conference, Krakow

  4. Data Cleanup(Developing Method for Real Data) Real data will have fake jets and high missing transverse energy due to: • Beam halo particles • Data acquisition problems • Detector problems (dead channels, hot channels, cracks etc.) • … Pile-Up Not Included CDF, Tevatron CMS Beam Halo Simulation for CMS Detector We apply cleanup on data by requiring [7] Fem  0.1 (Event electromagnetic fraction) Fch  0.175 (Event charged fraction) CMS CMS Pile-Up Included Pile-Up Included Effect of Data Cleanup on SUSY Sample (Acceptance Efficiency) Full ttbar simulation T.Yetkin, Phys.@LHC Conference, Krakow

  5. QCD Data and Cleanup CMS QCD jets  2 + ETmiss > 93 GeV CMS CMS SUSY LM1 QCD 2) (j(2), (ETmiss)) > 20 deg CMS CMS QCD jets  2 + ETmiss > 93 GeV SUSY LM1 QCD • QCD jet production cross-section is very large at LHC. Suppression with angular requirements 1) • Missing transverse energy in QCD jet production mostly due to jet mis-measurements and detector resolution. R1,2 > 0.5 rad Effect of QCD Topological Reqs. (Acceptance Efficiency) Multi jets and large missing transverse energy data sample is dominated by QCD! 3) min(j, (ETmiss)) > 0.3 rad T.Yetkin, Phys.@LHC Conference, Krakow

  6. W/Z+jets Backgrounds: Candle Normalization with the Z(μμ) Boson • Z()+ N jets can be estimated from Z(μ μ (ee))+ N jets • ETmiss and  3 jets are expected from • Z()+  3 jets • W(μ(e))+  3 jets • W( )+  2 jets (+1 jet from the -had decay) CMS CMS (ppZ+N jets)  SN • Z+ multi-jets can be used to estimate W+multi-jets background • MC to Data normalization avoids the systematic effects due to QCD scale, choice of PDFs, ISR/FSR, jet energy scale etc. Theory • First measure from the  2 jets data • Z(ee)+  2 jets • Z(μ μ)+  2 jets 5% precision is expected to be achieved by using ~1.5 fb-1 events [5]. T.Yetkin, Phys.@LHC Conference, Krakow

  7. ttbar Candle Normalization A similar candle normalization extraction of ttbar with data is in progress! T.Yetkin, Phys.@LHC Conference, Krakow

  8. Vetoing Leptons Loosely: Indirect Lepton Veto 1st Jet 2nd Jet CMS CMS W(e)+  2 jets W(e)+  2 jets 1st Jet 2nd Jet CMS CMS SUSY LM1 SUSY LM1 Leptons exist in the final states in signal and background. No explicit lepton identification. Indirect Lepton Veto (ILV) is introduced. It uses two parts of the detector: Calorimeter and Tracker In the calorimeter Fem,j(1)< 0.9 and Fem,j(2)< 0.9 In the tracker by using tracking isolation. R=0.35 Leading Track (PT 15 GeV/c) When both requirements are applied as ILV: • ~80% signal efficiency • ~50% to ~90% rejection efficiency in W/Z + jets depending on lepton flavour. The tracking is very robust for both PYTHIA and ALPGEN T.Yetkin, Phys.@LHC Conference, Krakow

  9. Analysis Path Inclusive SUSY Search with multi-jets and large ETmiss has the following analysis path: • Level-1 Trigger efficiency parameterization (was measured in a di-jet sample and parameterization was found) • HLT value for signal signature (ETmiss > 200 GeV, full efficient HLT) • Primary cleanup (1 prim. vert., Fem0.175, Fch0.1) • Signal signature (Nj3, |j(1)|<1.7, ET,j> 30 GeV, |j|<3.0) • QCD rejection (combined topological requirements) • W/Z/ttbar rejection (Indirect Lepton Veto) • Signal/Background optimization (ET,j(1) >180 GeV, ET,j(2) > 110 GeV, HT(ET(2) + ET(3) + ET(4) + ETmiss) > 500 GeV, No requirement on Meff  ET(1) + ET(2) + ET(3) + ET(4) + ETmiss ) T.Yetkin, Phys.@LHC Conference, Krakow

  10. A Candidate Event Multiple jets + ETmiss ETmiss T.Yetkin, Phys.@LHC Conference, Krakow

  11. Analysis Results CMS CMS CMS Selected SUSY and Standard Model background events for 1 fb-1. * (S) is ~13% with S/B ratio ~26. The 5 discovery can be reached by using ~6 pb-1 data collection (w/ sys+stat uncertainties in the significance estimation) ETmiss HT Meff *Due to limited Monte Carlo event generation the analysis path on QCD data is carried out without topological cuts and ILV. The estimate is conservative and based on the parameterization of the efficiency for cleanup and ILV requirements for ETmiss > 700 GeV T.Yetkin, Phys.@LHC Conference, Krakow

  12. Systematic Uncertainties • ETmiss Shape Systematic Uncertainty The effect of non-Gaussian tails in the jet ET resolution to ETmiss due to the energy mismeasurements by using a bootstrap method [8] -Repeat this for three scenario a) 3 jets are under measured simultaneously b) 2 jets are under measured simultaneously c) 1 jet is under measured The overall ETmiss shape systematic uncertainty is ~7%. CMS • Jet Energy Scale (JES) Systematic Uncertainty includes -absolute jet energy corrections -calorimeter stability -underlying event -relative jet energy corrections. 7% JES uncertainty is taken into account for 1 fb-1. • Luminosity Systematic Uncertainty ±5% uncertainty on the background estimates is taken into account for luminosity. • ALPGEN-PYTHIA Systematic Uncertainty A 5% positive systematic uncertainty on the background estimate is taken due to the variation in efficiency of the ILV requirement between ALPGEN and PYTHIA. • Total Background Systematic Uncertainty T.Yetkin, Phys.@LHC Conference, Krakow

  13. Analysis with a High Mass Point Analysis is repeated on high mass test point 1 (by using fast simulation FAMOS for signal) which has the parameters: CMS CMS ETmiss HT The overall signal efficiency is ~28% and claiming excess signal events is not easy for 1 fb-1. T.Yetkin, Phys.@LHC Conference, Krakow

  14. 5 SigmaReach Study a SUSY reach scan over the mSUGRA parameter space for 1 fb-1 and 10 fb-1. High mass test point 1 is used as optimization reference. The requirements on ETmiss and HT are raised as 600 GeV and 1500 GeV respectively (signal efficiency drops to ~12% from ~28%). T.Yetkin, Phys.@LHC Conference, Krakow

  15. Conclusions • 5 sigma observation of low mass SUSY at LM1 is achievable with ~6 pb-1 (not the first) events by using multi-jets and ETmiss. • W/Z+jets (including Z) can be normalized by using Z(μμ(ee)) + multi-jets with ~1.5 fb-1 events. (Z(μμ) + multi-jets can also be used to calibrate missing transverse energy if tracking and muon system are used together. • Indirect Lepton Veto makes possible the ttbar and W/Z+multi-jets rejection while preserving the inclusive nature of the search. • QCD jets can be suppressed with topological requirements but QCD background tails in the ETmiss still needs to be understood from real data. • After using the optimized analysis on mSUGRA plane it was shown that low mass SUSY is in the 5 sigma reach of LHC. T.Yetkin, Phys.@LHC Conference, Krakow

  16. References 1- http://cmsdoc.cern.ch/cms/PRS/results/susybsm/susybsm.html 2-“CMS Physics Technical Design Report, Vol. I”, CERN-LHC-2006-001, 2006, CERN. 3- http://cmsdoc.cern.ch/oscar/ 4- http://cmsdoc.cern.ch/orca/ 5- “CMS Physics Technical Design Report, Vol. II”, CERN-LHC-2006-026, 2006, CERN. 6- http://cmsdoc.cern.ch/famos/ 7- “Jet and Event Electromagnetic and Charged Fraction in CMS”, CMS Note/2006-010, 2006, CERN. 8- “Evaluation of the PTmiss Shape Systematic Uncertainty Due To Tails in the Jet Resolution at CMS”, CMS Note-2006/015, 2006, CERN. T.Yetkin, Phys.@LHC Conference, Krakow

  17. BACKUP SLIDES T.Yetkin, Phys.@LHC Conference, Krakow

  18. CMS Detector T.Yetkin, Phys.@LHC Conference, Krakow

  19. CMS Detector T.Yetkin, Phys.@LHC Conference, Krakow

  20. LM1 Properties T.Yetkin, Phys.@LHC Conference, Krakow

  21. Event Generation T.Yetkin, Phys.@LHC Conference, Krakow

  22. ILV Leading Track Isolation-I Tracking isolation is used at CMS as a powerful criterion in  selection (PTDR-Vol1). We developed a tracking isolation strategy in order to reject electrons, muons and taus from W and Z decays while retaining the SUSY signal efficiency. The highest PT track is found among the tracks that are associated to primary vertex in each event where the tracks have the requirements: • PT > 1.2 GeV/c • Nhits 5 • transverse impact parameter |d0|  600 µm • |zPV − ztrk| < 1 mm • |trk| < 2.4 T.Yetkin, Phys.@LHC Conference, Krakow

  23. ILV Summary and Results ILV works well for rejecting backgrounds from W/Z and also from ttbar when the final state has high energy electrons and muons. Table 1: Rejection efficiency of Indirect Lepton Veto in LM1. Table 2: Rejection efficiency of Indirect Lepton Veto in W/Z (PYTHIA)Samples T.Yetkin, Phys.@LHC Conference, Krakow

  24. EEMF Event EMF is defined to be the PT weighted jet EMF sum over the electromagnetic calorimeter acceptance, |d| < 3.0: where: • NJet is the number of IC jets of cone 0.5 with PT > 30 GeV and | d|<3.0 • PTj is the uncorrected PT of the jth jet • EMFj is the EMF of the jth jet T.Yetkin, Phys.@LHC Conference, Krakow

  25. ECHF Event Charged Fraction The event charged fraction is calculated by finding all the tracks pointing to each jet within a cone of 0.75 of the - centroid of the jet. A jet enters into the event charged fraction variable if its absolute pseudorapidity is less than 1.7. T.Yetkin, Phys.@LHC Conference, Krakow

  26. EEMF and ECHF Summary Summary and Results Clean-up efficiency for LM1 and ttbar. (Percentage of kept events) The pre-selection requirements that will be effective against a number of spurious and instrumental backgrounds in analyses with high PT multijet plus large missing transverse energy. T.Yetkin, Phys.@LHC Conference, Krakow

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