Reconstruction and calibration strategies for the LHCb RICH detector R. Forty(1), C. Jones(2), C. Lazzeroni(2), R. Muresan(3), M. Patel (1), G.Wilkinson(3) (1)CERN, (2) University of Cambridge, (3) University of Oxford LHCb particle identification: The ability to distinguish between pions and kaons over a large range of momenta is essential to extract CP violation results in LHCb. Three radiators are used in the two RICH detectors: silica aerogel and C4F10 gas to identify particles in the range 2-50 GeV; CF4 for particles up to ~100 GeV. Rings are visualized by reflecting the cones of Cherenkov light onto arrays of hybrid photon detectors (HPDs). LHCb ring pattern recognition algorithm requirements: To reconstruct distorted, incomplete rings with variable radius and a variable number of finite resolution hits. To be robust in the presence of background. To process a large number of images, (~ 500 hits in RICH1, 300 in RICH2) fast enough not to reach the CPU limits for event reconstruction. LHCb Detector RICH pattern recognition: Likelihood: baseline offline method that has been shown to perform very well. Does not reconstruct rings but compares expectation based on track information to observed data. Its limitation comes from the associated track requirement and the CPU time necessary: ~100 ms per event, to be compared with the order 10 ms available to run the entire high level trigger. Trackless ring reconstruction: Hough transform and Markov chain methods, applied offline, perform ring finding using the information from the photodetectors alone and hence provide robustness against background which does not have associated track information. Online reconstruction: similar principle to offline likelihood but simplified for increased speed whilst maintaining acceptable performance, suitable for use in the high level trigger. particles with tracks background RICH1 Ring not predicted from tracking information Event display with the photodetector planes of RICH 1 drawn side by side (scale in cm) and the predicted Cherenkov rings superimposed (likelihood method). RICH1 RICH2 Cherenkov angle reconstruction online: Offline strategy of calculating Cherenkov angle for each photon from RICH hit, assumed track and knowledge of the detector optics, too slow online. Instead calculate approximate angles directly on the photodetector, applying local coordinate “stretch” to correct optical distortions. Hough transform: Reconstruct a given family of shapes from discrete data points, assuming all the members of the family can be described by the same kind of equation. To find the best fitting members of the family of shapes the image space (data points) is mapped back to parameter space. Work on going to resolve the near degenerate solutions. RICH2 Preliminary Online PID: “Local”: peak search in Cherenkov angle distribution to look for the maximum signal/background. Apply a momentum cut to determine if the track came from heavy/light particle. “Global”: similar to the offline likelihood method but faster since full reconstruction is not required. RICH2 cm hits, Hough centres, track impact points Metropolis- Hastings Markov chains: Sample possible ring distributions according to how likely they would appear to have been given the observed data points. The best proposed distribution is kept. Preliminary results are encouraging, work on going to assess the performance of the method True p in blue True K in pink Radius of the rings corresponding to the most significant peak in signal/background distribution (local PID). Markov rings *authors are grateful to A. Buckley for providing the picture and C. Lester for help in implementing the method Rich PID Callibration: D*  D0 (pK ) p events are selected in the high level trigger and then offline, using kinematic information alone. A very high statistics sample ( 108 events per year ) of pions and kaons available for evaluating PID information directly from data. PID efficiency Offline Online Kaon selection efficiency versus momentum , as evaluated with D* method D0peak min bias pure signal PID online: physics performances: The time to perform the reconstruction is ~3 ms/event. This allows the use of RICH PID in the trigger resulting in substantial gains in efficiency with comparable background rate. Two examples are BsDsh and Bsff where 25% gain is obtained. D0mass (GeV) PT distribution of the hadron, h, in B->Dh candidates in the trigger, for both signal and minimum bias (MB) events, before and after applying the particle identification. The background falls by an order of magnitude while the signal is unaffected. Initial sample Bd->D*p decays 21 D0s from 13M minimum bias events, ~ 0.8 seconds of data taking at L= 2 x 1032 cm-2s-1. 500 M such D0 will be selected by the high level trigger in one year of running. Bachelor pT (MeV) (GeV)