This is a presentation describing the commissioning of the ATLAS detector using photons. Expected performances are presented, together with recent results from cosmics data taken in 2008

Koffas, T

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ATL-PHYS-SLIDE-2009-36623November2009Photon Commissioning in ATLAS Thomas Koﬀas CERN (on behalf of the ATLAS Collabora7on) Hadron Collider Physics Symposium Evian, France, November 2009 Photons at the LHC •  Main sources of high pT isolated γ at the LHC: QCD processes. •  Main background:  jets The search for new phenomena with photons requires: •  efficient photon reconstruction •  accurate photon energy and direction measurement •  particle identification: jets rejection 105 photons for 100 pb-1 100 photons for 100 pb-1 Prompt photon statistics not a problem at the LHC: •  Hundreds of thousands of single prompt photons •  Thousands of di-photons  jj ATLAS sub-detectors used for photon reconstruction 2T Solenoid 2.5 Photon Reconstruction in ATLAS Clustering algorithm for photons:  •  slide a window ΔηxΔφ = 5x5 in a calorimeter tower (over 4 samplings); find local max  •  track/vertex matching distinguishes electrons from unconverted and converted photons  •  re-build the cluster:  ΔηxΔφ = 3x5 cells for unconverted photons                                    ΔηxΔφ = 3x7 cells for converted photons (wider phi to account for                                                                                                       B-field opening) Energy and position reconstruction:   •  cells in the clusters are summed  •  position dependent energy corrections are applied.  Photon energy resolution E =100 GeV single photons MC All Photons |η| = 1.075 H(120GeV)->γγ, converted photons |η| < 2.0 Photon Reconstruction in ATLAS II Photon Identification in ATLAS   Rφ = 3x3 / 3x7 Rη = 3x7 / 7x7  Plots shown for: |η|<0.7  20<ET<30GeV Photon Identification in ATLAS II  Ratio of energy outside core of 3 strips but within 7 strips Fside =(E±3 -E±1 )/E±1 sideF0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5-310-210-1101SignalBackgroundATLASFside Hottest  cell Photon Reconstruction Performance  Example: photons ET > 25 GeV from H→γγ  Photons Fakes After all cuts 70% of the remaining fake photons are high momentum π0 Main background from tight jets faking photon showers. A rejection factor of ~103-104 for quark/gluon jets respectively, is achieved. φ>0 (top) φ<0 (bo6om) Validation of Photon Identification with Cosmic Events  •  Would like to validate as much as possible the γ identification before collision data    using cosmic events: •  Confirm robustness of γ initial selection by comparing shower shapes to MC expectations  Limitations of cosmics validation   Average energy of EM objects in cosmics fairly low   Most cosmic events are not projective!   Shower shapes mostly not like what we will see in ATLAS due to cosmics direction   In the barrel:   φ>0 (coming in through the top of the detector) have showers starting in the back of the calorimeter (or before)   φ<0 is more like what we expect to see in ATLAS   Important to compare cosmics data with cosmics MC  Data Sets and Event Selection  EM shower-shape studies  with photons   Cosmic dataset:   Barrel: 3.5M events with high-level trigger (L2) track candidate reconstructed in barrel inner detector (IDCosmics trigger stream)   Endcap: 270k events, at least one sliding-window cluster in EM (L1CaloEM trigger stream)   Cosmic simulation:   11.7M cosmic-muons required to go through the ID geometrical volume   Barrel event selection:   Ecluster>5GeV (sliding-window cluster)   Loose projectivity: at least one Si track |d0| < 220 mm and pT > 5 GeV   “collision-like” photon candidates: Estrips /Ecluster > 0.1   1200 candidates for the data and 2161 for simulation  Work in progress for the endcaps Measured Calorimeter Response  ID track EM Calo “Muon road” EM Cluster Middle : 1x3 Front : 2x1 At least 2 cells in φEvent selection: •  From DPD stream : Projective ID track  (1 hit in Si, |z0|,|d0| < 300 mm) •  Addional cut based on geometry of LAr cells •  No effect of misalignments ! •  Cuts effects of leakage •  After cuts, about 75 000 events left  Middle layer Front layer        Projectivity and centrality of muons are not trivial => tight selection Middle Layer Calorimeter Variables  At the heart of electron/photon identification!   The lateral shower containment in the middle layer (ΔηxΔφ ≅ 0.025x0.025)   Along η : Ratio of energy in a ΔηxΔφ =3x7 cells cluster size with respect to a 7x7 cells cluster size   Along Φ : Ratio of energy in a ΔηxΔφ =3x3 cells cluster size with respect to a 3x7 cells cluster size   Agreement between cosmics data and simulation gives confidence that these are reasonably robust variables to use with early data. 3x7 7x7 (η) 3x3 3x7 (φ)   The lateral shower containment in strip layer    Ratio of energy outside core of 3 strips but within 7 strips    Fside =(E±3 -E±1 )/E±1   φ>0 (top): shower profile is wider   more likely to be initiated in middle or back calorimeter layers   φ<0 (bottom): shower profile is narrower    showers initiated in ID or cryostat wall First Layer (strips) Calorimeter Variables  φ>0  φ<0 φ>0 (top) φ<0 (bo6om) Calorimeter Strip Variable  Dependence on Projectivity    Δθ = shower direction – direction from  centre of detector to centre of cluster    Plots of average lateral profiles in the strips   Data, simulated cosmic-rays, simulated projective single photon showers (ET=5GeV)    projective (|Δθ| <0.10) and non-projective (0.10<|Δθ| <0.20) showers    widening of the showers as they become less projective  Projec7ve  Non‐projec7ve Material Mapping with Converted Photons I  LHC trackers: heavier than any previous one (LEP, TeVatron): ATLAS Inner Detector ~ 4.5 ton Large amount of material in front of the EM calorimeter means:  -  large energy losses of electrons through bremsstrahlung  -  high photon conversion probability -  a complex calibration procedure for the EM calorimeter Beam pipe Pixel SCT TRT The conversion probability ranges from 40 % (η =0) up to 80% (η =1.8) Knowing the exact amount and position of the upstream material is of paramount importance !  Use conversions as a tool to reconstruct the 3D material map of the detector Radial resolution (3mm) with low pT photons. Material Mapping with Converted Photons II  Precise 3D mapping of the material with low‐energy conversions from minimum bias data Enough sta7s7cs for a 1% material map in a few months of data taking Conversion ingredients: Tracking + Vertexing Tracking Efficiency Photons ET = 5GeV Conversion Reconstruction Efficiency Photons Material Mapping with Converted Photons III  Converted photons already used to map the Inner Detector material in the 2004 Combined Test Beam (CTB) conversion e+ e‐ CTB Data •  Events with two TRT track segments pointing back to the Si tracker are selected. •  Concentrate on conversion vertices reconstructed in the pixel tracker. •  Count reconstructed conversions within each pixel layer: •  Use the simulation to correct for efficiency variations on each layer •  Use the well measured Cu foil in front of the pixel as a material reference. Cu Foil Material Mapping with Converted Photons IV (Preliminary ) Estimated amount of material per pixel layer with respect to the Cu foil Good qualitative agreement between data and simulation. Absolute value restricted by large systematic error on the incoming photon flux. Copper  PixelB  Pixel1  Pixel2 X/X0(%) with stat. error  0.21±0.02±0.04  1.68±0.19±0.35  1.95±0.23±0.40  1.98±0.24±0.41 Ra7o  −  8.16±1.28±1.97  9.47±1.51±2.29  9.62±1.56±2.26 X/X0(%) in MC  0.25  2.6  2.6  2.6 Ra7o in MC  −  10.4  10.4  10.4 Summary  •  Photons constitute an important tool for commissioning the ATLAS detector: •  Plenty of signal already with early data •  Dedicated software for photon reconstruction already in place •  Utilization of few simple variables to validate quantities for photon identification •  Initial performance based on MC data well established •  Cosmics data of great importance for validating the photon reconstruction: •  Significant amount of available statistics •  Contain both the tracker and the EM calorimeter inputs •  Comparison with the cosmics data MC confirms the robustness of the reconstruction •  Converted photons an important tool for accurate detector description •  Conversions in minimum bias data can be used to determine the tracker material •  Initial implementation in the Combined Test Beam gave consistent results. •  Enough statistics within a few months to map the tracker material down to 1% accuracy •  Initial source of clean electron sample for PID commissioning in the TRT.   Looking forward to see the first photons from collisions into the ATLAS detector! Backup Slides Photons at the LHC •  Main sources of high pT isolated γ at the LHC: QCD processes. •  Main background:  jets The search for new phenomena with photons requires: •  efficient photon reconstruction •  accurate photon energy and direction measurement •  particle identification: jets rejection Photon Identification in ATLAS II   Example of a variable built with the strips (first layer) of the electromagnetic calorimeter: Track Isolation  After shower shape cuts the remaining background is dominated by low track  multiplicity jets containing a high pT π0 Track Isolation = sum of the pT of all tracks with pT>1 GeV within ΔR<0.3                     (tracks from conversions are excluded) 

Photon Commissioning in ATLAS

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