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Alan Barr University of Oxford

LHC (ATLAS) Dark Matter Searches : Uncertainties. Alan Barr University of Oxford. DMUH, July 2011. ?. WARNING. Theme is certainties and uncertainties Not a standard “ATLAS Searches” talk Some topical analysis highlights Concentrate on how uncertainties determined.

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Alan Barr University of Oxford

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  1. LHC (ATLAS) Dark Matter Searches:Uncertainties Alan BarrUniversity of Oxford DMUH, July 2011

  2. ? WARNING • Theme is certaintiesand uncertainties • Not a standard “ATLAS Searches” talk • Some topical analysis highlights • Concentrate on how uncertainties determined

  3. Dark Matter Highlights 1 TeV 100 GeV Jets [b-tag(s)]Leptons [electron(s), muon(s)]Missing transverse momentum PTmiss

  4. Example conference note ATLAS-CONF-2011-086

  5. ATLAS-CONF-2011-086 Example conference note • 7 Page note • 1 Page introduction • 1 Page definitions • 2.5 pages on uncertainties • 1.5 page results/interpretation • 10 public plots of control measurements • Dozens of others made internally >200 page internal document describes cross-checksand uncertainty determination for this one analysis (not public)

  6. 165 pb-1 Fiducial cuts ATLAS-CONF-2011-086

  7. 165 pb-1 Counts, expectations and uncertainties ATLAS-CONF-2011-086

  8. Observed Expected

  9. What we do NOT do… Do not boldly extrapolate taking “uncertainty” fromfit

  10. Uncertainties? Standard Model backgrounds Instrumental backgrounds Expected Signal?

  11. Momentum imbalance… • Mismeasurement? • Cosmics? • Noise? • Beam halo? • Neutrinos? • WIMPs? PATHOLOGIES PHYSICS

  12. JETS + MISSING MOMENTUM From collisions Jets Jets PTmiss

  13. JETS From collisions Jets: Had. CalorimeterE.M. CalorimeterTracks from vertexIn-time b,c quark jets can decayto neutrinos

  14. JETS + MISSING MOMENTUM Measurements Jets:  cut Reduce: Had. CalorimeterE.M. CalorimeterTracks from vertex Measure remainderat small 

  15. JETS + MISSING MOMENTUM From cosmics Reduce by: (a) requiring tracks with jets (b) look for muonhits Measure remainder: (a) no beam (b) timing

  16. JETS + MISSING MOMENTUM From beam halo Reduce by requiring tracks with jets Measure remainder with single beam / timing

  17. JETS + MISSING MOMENTUM Calorimeter noise Reduce by requiring tracks with jets Measure remainder (a) no beam (b) timing

  18. Neutrinos Z ( ) + jets (+ jets) W ( l) + jets Bjets

  19. Calibration, confirmations, cross-checks 108W bosons 2.5 107Z bosons > 105top quarks Multiple MEASUREMENTSof background processes(together with theoretical predictions)

  20. ATLAS-CONF-2011-060 W + Jets MEASUREMENTS test MC simulations Huge numbers of Ws Differential in many parameters

  21. Monte Carlo uncertainties • State of the art generators • LO  NLO  NNLO • Decreasing uncertainties from higher order corrections • Very non-Gaussian uncertainties • Somewhat arbitrary “uncertainty”  untrusted • Full GEANT detector simulations • Remarkably good description of detector response • Multiple cross checks

  22. Do we trust the Monte Carlo? Reduce use of Monte Carlo wherever possible Background determined from MEASUREMENTS where possible  uncertainties under experimental control

  23. Final results depend largely on measurements from control regions Jets Jets Z  + jets

  24. Final results depend largely on measurements from control regions Jets Zμμ + jets Jets

  25. Final results depend largely on measurements from control regions Jets Photon Jets  + jets

  26. A distribution we care about: Full SimulationMonte Carlo(Alpgen)Leading OrderMulti-leg

  27. What we DOdo Multijets  + Jets( Z+jets) W + Jets

  28. Other uncertainties include • Luminosity: • MEASURED in Van-der-Meer scans, … • Proton Structure: • MEASURED at HERA ep collider • Cross-checked/refined with LHC data • JET Energy Scale (detector response) • MEASURED in beam tests • Cross-checked/refined with LHC data Dependence on these effects (and on MC) greatly reduced by measuring background rates in LHC data

  29. JET ENERGY SCALE? H8 calorimeter beam test 1999

  30. Putting it together: Likelihood Poisson for control regions(fns of nuisance parameterssignal strength, …) Poisson for signal region Nuisance parameters largely uncorrelated Shifts due to nuisance parameter

  31. Sources of systematics considered • Jet energy scale • Jet energy resolution • Lepton efficiency • Lepton energy scale • B-tag efficiency • Pile-up/multiple pp interactions • Out-of-jet energy • Monte Carlo stats • MC higher order corrections • Loss of electronics • PDFs • Signal cross section higher order corrections

  32. CAVEAT • I have emphasised that multiple measurements give good confidence in size of uncertainties • RMS of measurements/discrepancies often used to define 1-sigma [~fine] • Anyone who believes in Gaussian uncertainties in such contexts is naive • One should be correspondingly wary about literal interpretations of multi-sigma effects

  33. Add additional uncertainties in predicted signal (PDF, higher orders) Results from EPS-2011 on Saturday Full talk Simplified model

  34. I can’t resist showing…

  35. “Intriguing” Higgs results Consistency with BG-only hypothesis

  36. Getting the results? • ATLAS public results • EPS 2011, 21-27 July; link • Supersymmetry searches summary

  37. Most recent results being presented

  38. LHC PHYSICS Extra slides

  39. 2011 Plans…

  40. Software Operations Hardware Grid Detector & Upgrade Computing

  41. Further search papers • Others • Monojets • e-mu resonances • Dilepton resonances • Leptoquarks • CHAMPS • Dimuons (contact) • W' l  • Z'  ll • Supersymmetry: • Squarksor gluinos • Lepton + jet + invis • Dilepton + invis • Same sign leptons + invis • Z + invis • b-jet(s) + invis • R-hadrons

  42. Supersymmetry • Partner particles • Spin differ by ½ • Stabilise mH • Dark Matter candidates • “Missing” momentum • Big reach at LHC

  43. Supersymmetry searches 25 Feb 2011 ATLAS-CONF-2011-086 “Missing” momentum Scalar sum of momentum

  44. Wider interpretation... ATLAS 0/1 leptonATLAS-CONF-2011-086 H  CMS αT June’11 h Jan’11 Cassel, Ghilencea, Kraml, Lessa, Ross http://arxiv.org/abs/1101.4664 Allanach, Khoo, Lester, Williams http://arxiv.org/abs/1103.0969 Regions with low fine tuning Points sampled from fits to global data Global CMSSM fits

  45. Example Simplified Model OtherParticles Squarks: 2 Jets Jet Neutralino

  46. Example Simplified Model Gluinos: 4 Jets Jets Neutralino

  47. Example Simplified Model Gluinos: Jet Squarks: 4 Jets Jet Neutralino

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