Muon Reconstruction and Commissioning with Early Data

1. Muon Reconstruction and Commissioning with Early Data Kevin Black Harvard University

2. Outline • Overview of Muon Reconstruction Software • General Reconstruction • Moore + Muonboy (MuonSpectrometer) • MuIdCombined + Staco (combine with inner detector) • Low PT Muon Identification • MuTag, MuGirl • Calorimeter Information • Energy Loss, Muon Identificaiton • Comparison of Algorithms (see talk by David Adams) • Commissioning with early data • Cosmics • Beam Gas Events from single beam running • Collision Data (@900 GeV and then @14 TeV) • Muons from /K and heavy quark decay for alignment/calibration • J/, Z • Will not discuss test-beam, alignment and calibration, or electronic calibration (see talk by Ed Diehl)

3. Active Developers (and many others in the past…) • Moore & MuID • BNL - David Adams, Ketevi Assamagan : CERN - Alan Poppleton, Harvard – KB, Steve Cavanaugh, Ben Smith, Srivas Prisad : NIKHEF – Niels Van Eldic : SUNY Albany – Vivek Jain, Victoria : U Mass Amherst – Ed Moyse, Thomas Moore, Stephane Willocq • MuonBoy & STACO & MuTag • Saclay: Florian Baur, Laurent Chevalier, Jean Ernwein, Andrea Formica, Pierre-Francios Giraurd, Claud Guyot, Samira Hassani, Eric Lancon, Jean-Francois Laporte, Rosy Nicolaidou, Dainel Pomarde, Philippe, Schune, Marc Virchaux [SaMuSog] • MuGirl • CERN – Zvi Tarem : Technion - Natalia Panikashvili, Shlomit Tarem, Tel Aviv – Orfirt Belkind, David Primor • Muon Identification with Calorimeter • NIKHEF – Peter Kluit, G Ordenez, Wisconsin - L. R. Flores-Castillo, B. Mellado, Sau Lan Wu • dE/dX and Energy Loss in the Calorimeter • Athens - C. Kourkoumelis, D. Fassouliotis, K. Nikolopoulos : Saclay – SaMuSog, CERN – A. Poppleton • Material Treatment • CERN – A. Poppleton: Saclay – SaMuSog: Tufts – S. Todorova

4. EE chambers removed Barrel Chambers Half CSC ENDCAP TOROID FEET BARREL TOROID Big Wheel RIBS

5. Identify and Measure track parameters For B = 0.5 T, L = 5 m • p = 5 GeV/c R = 33 m s = 0.1 m • p = 1 TeV/c R = 6700 m s = 500 µm  need 50 µm resolution to achieve 10% momentum resolution

6. Moore PatternRecognition rpc barrel  projection rpc rpc Search for region of activity in the  projection and RZ projection barrel RZ projection MDT

7. Segment Finding,Track Fitting • Pattern recognition in individual MDT multilayer • the drift distance is calculated from the drift time, by applying various corrections on it (TOF, second coordinate, propagation along the wire, Lorenz effect). Among the 4 tangential lines the best one is found. • Track segment combination. MDT pattern recognition MDT multilayer • Track fit track parameters (a0, z0, , cot, 1/pT ) are expressed at the first measured point

8. First measured point Calorimeter correction Refit @ vertex Matching with the inner tracks and combined fit Package Muid Two steps: • 1. Track extrapolation at the I.P. • Multiple scattering parameterized by means of scattering planes in the calorimeters • Energy loss in calorimeters parameterized in function of (, ) or measured from calorimeter reconstruction • Re-fit: track parameters expressed at vertex • 2. Tracks from the muon spectrometer and from the inner detector are combined with a 2 < cut-off - 2 calculated from differences of track parameters and from covariance matrix • Final fit of the successfully combined track

9. Moore and MuId Performance and Development Rome Era (10.0.1) Recent Release (11.0.3) • Albany, BNL, CERN, Harvard, • UMass Amherst • EDM Migration • Improved CSC treatment • Improve pattern recognition • Improve material treatment • Develop tools to enhance efficiency and reduce fake rate

10. Muonboy Strategy • Similar Strategy –search for Regions of Interest • Form Segments • Combined Segments • Track Fit • Main Differences • 3d pattern recognition from the start • Start with segments in inner station and extrapolate the position out to next layer • Handles inert material differently • Core program written in early 90’s with F90, wrapped in C++ for use with athena

11. Principle of STACO • For two tracks on some reference location defined by their : Parameters vectors : P1 and P2 Covariance matrices : C1 and C2 • P: parameters vectors of combined track is the solution of the equation: C : covariance matrix of combined track is given by • The corresponding 2 • Track combination is tried only for pairs of tracks that show a reasonable matching in the (,) plane • Track combination is accepted only if the global 2 is below a maximal value • If different combinations are possible, the pair given the best 2 is retained • Uses Parameterization of Energy Loss in Inert Material

12. Developments Staco: try a full refit at Calorimeter surface Mutag: use of segments in middle layer Further Development of track extrapolation MuonBoy and Staco Performance Saclay

13. μ Low Pt Muons Low PT muons often do not reach the outer stations, Start with inner detector tracks and extrapolate out to the muon spectrometer RegionSelector RegionSelector

14. Different Approaches • All use inner detector extrapolated track • MuTag is run after Muonboy and extrapolates ID track and tries to match with unused segments • MuGirl extrapolates ID track and forms new segments using ID seeding – Extention and replacement of older package MuIdLowPt • Uses ANN to discriminate between true particles and fakes • Uses vertex constraint to discriminate between muons from IP and from in flight decay of /K • As of release 12, MuIdLowPt will be deprecated, MuTag and MuGirl available at AOD level • MuGirl is the newest package on the market, but is already showing great progress

15. In AODs in release 12 Working on rejection of muons from K/ decays Including segments from TGCs MuGirl Performance and Development BsJ/Ψ(μ6μ3) bbμ6X Wbμ6X Higgs4μ CERN, Tel Aviv, Technion 4 Working points evaluated on 4 samples

16. Muon Track (Backtracked to Calo Outer Scattering Plane) Energy Measurement Use New Mean Energy Loss Parametrization (with asymmetric errors) Yes No Is the measurement “feasible”? ( i.e. Isolated Muon?) Dead Material Correction (Mean Energy Loss Parametrization + X0map) Energy measurement “significant” w.r.t the most probable value? (EMeas> MOP+ 2*σMOP) Yes Use the Energy Measurement No Use the Energy Loss Parametrization Strategy for μ energy loss reconstruction Athens, CERN

17. Long Landau Tail.. A correction was found for this effect. Instead of using the MPV as is, use a weighted mean in the region where Athens, CERN

18. Using the Calorimeter to tag muons Wisconsin • Hardware-related inefficiencies for turn-on • Tracking efficiency: ~100% • 4-2-0 topo clusters: • ~100% efficient for muons • Many samplings available • Longitudinal and transverse shape information Staco+MuTag Staco+MuTag+CaloLR H->4 µ • From single muons and pions select 11 variables for Likelihood Ratio • For now, only for ||<1.4 • Efficiency: 94.2  97.7 %

19. Calorimetric Muon ID Wisconsin • Rejection of single  ~ 1000 at 90% efficiency • Plans: • Neural Network for µ/ separation • Make use of track to calorimeter extrapolation tools • Study fakes, efficiency, effects on significance with background and piluep etileb0/EHad eemb2/EEM+Had EtopoMax/Etopo etileb1/EEM+Had

20. Commissioning with Cosmics • Sector 13 without trigger chambers for about 9 months • Sector 13 with trigger chambers starting a few weeks ago • Apply Algorithms to real data • Beginning of Alignment and Calibration with Cosmics • Analysis of Cosmics: • CERN, Harvard, Nihkev, Saclay, U Mass Amherst

21. Challenges with Early Data • Very non-uniform magnetic field (introduces complications to calibration, track extrapolation and hence alignment, and resolutions) • Very complicated large area detector (alignment, calibration) • What is the real inert material? • How will the real cavern background and pile up affect muon reconstruction and identification? How realistic is the simulation? • How severe will punch-through be? Will it be as expected from simulation? • What is the Standard Model at 14 TeV?

22. Plans with first Data • Cosmics • Analysis of sector 13 data with trigger chambers, as the detector is assembled take more cosmic runs • Initial Calibration, alignment with tracks, debug/improve software with the clean and simple tracks, alignment with inner detector • Initial Run with only injection energy, 900 GeV low luminosity (although not as exciting, benchmark point for understanding) • Alignment and Calibration with any muon tracks • Handful of Z events, focus on J/ (and other resonances) for studies of efficiency, resolution, fake rates with data – tag and probe, comparison with inner detector • Alignment with inner detector, study material effects, energy loss • Initial run at full energy • Focus on Z events: tag and probe to study eff, res, fake, comparison with inner detector

23. Cosmic Ray Commissioning • Rates are substantial • 2.3 KHz • for a hit anywhere in • detector • 0.5 Hz • for |Z| < 60 cm,R < 20 cm • Trigger in barrel or end-cap • 40 Day Atlas Global Run before beam From R.McPherson and J. Pilcher Talks

24.  pT > 1 GeV inside  3m 1.0x103 Hz 1.5x109 events in 2 months assuming 30% efficiency Beam Halo events Especially usefull for end cap Beam Gas and Beam Halo Events Beam-gas collisions are essentially boosted minimum-bias events  low-pT particles Rate : ~ 2500 interactions/m/s From J. Pilcher

25. B physics group Heavy Quarkonium 2006 Talk Collider Data at 900 GeV • Initial Commissioning Run • C.M. energy 900 GeV (injection energy to LHC ring) • Luminosity between L ~ 1027 - 1030cm–2s–1 • Integrated Luminosity between 1 nb-1 to 10 pb-1 • Only a handful of Z events at best focus on J/ and other resonances  for resolution and scale • Use all muons for alignment and calibration Mass resolution σ(M2μ)=43MeV Stable beams Preparation …First collisions……. Shutdown 3 to 4 months? July Nov. Feb. Mar Aug. Sept. Oct. Dec. Jan.

26. Collider data at 14 TeV @1033 cm-2 s-1 With 100 pb-1 0.1 Million Z  µµ, recall ~10 Million events recorded at Tevatron after ~20 years

27. Simplistic View of Strategy • 1st understand and calibrate detector and trigger in situ • Use all muons • Calibration and alignment • Alignment with inner detector • Use well known “standard candles” (dimuon resonances) • Study Resolution, efficiency, material description, realism of monte carlo simulations • Understand the SM at 14 TeV (first measurements of cross-section, rapidity distributions, etc) • 2nd • Prepare for the road for discovery • Measure backgrounds and obtain control samples • 3rd • Real excitement phase, first time to substantially probe physics at the few TeV scale

28. Summary and Conclusions • Muon Reconstruction Algorithms performing well (see D. Adams on performance) • Lots of active interest in North America, many recent and continuing developments • Several Stages to commissioning • Muon standalone cosmics • Global Atlas Cosmic runs • Beam Gas and Beam Halo events for single beam runs • Early focus for 900 GeV Run • Multistage process with 14 TeV collisions • Much accomplished, but still much to do • Primarily, shift focus to preparing for first data (more cosmic data) • Develop tools to evaluate performance without the help of “truth information” (e.g. tag and probe) • Difficult challenge for alignment and calibration because of the size and complexity of the Muon Spectrometer and Toroid magnets (See E. Deihl’s talk on calibration and alignment)