Luminosity Measurement in the Helsinki, November 2000 Reminder what is LHCb ? First studies for lumi  pile-up vertex detector Summary Massimiliano Ferro-Luzzi, CERN Massimiliano Ferro-Luzzi, CERN

CP violation and rare decays A Large Hadron Collider beauty experiment for precision measurements of CP violation and rare decays (LHCbepmCPvrd… or just LHCb) Measure asymmetries: Af (t) = e.g. (semi)leptonic FCNC B-decays. …always possible to measure rates relative to other channels Rf (t) + Rf (t) Rf (t) - Rf (t) from four rates Rf (t) = initial B decaying to final state f (a bar stands for “CP conjugate”) Massimiliano Ferro-Luzzi, CERN

Typical B event at LHCb B0  - D*+  D0 + B0  +- Primary vertex Generated polar angles of b and b hadrons (with PYTHIA) B0  +- 10 mm Aims for offline: decay distance resolution  120 m proper decay time resolution  0.04 ps Massimiliano Ferro-Luzzi, CERN

LHCb Detector Acceptance: q  [10, 300] mrad h  [5.3, 1.9] Massimiliano Ferro-Luzzi, CERN

LHCb Trigger total  100 mb beauty  0.5 mb To tape: 1.0 0.8 0.6 0.4 0.2 0.0 Bd  J/ (+-)Ks + tag Bd  +- + tag Bd  D K* reconstructable events Efficiency for SICB monte-carlo (PYTHIA) total  100 mb beauty  0.5 mb To tape:  3 million Bd evts/yr  1 million Bs evts/yr Clock bunch crossing with n>0 collision(s) single collision 107 106 105 104 103 102 101 total charm beauty Event rates [Hz] L0 L1 L2 L3 e/h calo, -ch ET , pT VErtex LOcator Impact param, vertices Trackers , Momentum Full reconstruction Massimiliano Ferro-Luzzi, CERN

LHCb Si Vertex Detector Modules etc. R|f -20 80 [cm] towards spectrometer Z f|R R|f retract by  3 cm during beam filling/tuning 0 8 40 mm R-detector prototype 220 mm thick Si single-side one module: R and f measuring planes total of 220 k channels, analog, S/N=15 Design work ongoing for front-end chip (DMILL and subm technologies) Massimiliano Ferro-Luzzi, CERN

LHCb Vertex Detector Design Exit window RF/Vacuum shield Take into account: static and dynamic vacuum effects, wake field effects, multiple scattering, alignement, etc. Silicon module (cooled) Massimiliano Ferro-Luzzi, CERN

Problem for trigger: n>1 collisions Level-1 is based on vertex finding and becomes problematic when there is more than 1 collision in a bunch crossing Level-0 (pT cut, output at 1 MHz) is less “beauty-selective” for events with n>1 collisions. Possible improvement: find and veto crossings with n>1 collisions ! Possible implementations: 1. Total energy in calorimeters 2. Time-of-flight clusters our choice !  3. Look for primary vertices Probability Pn to have n collisions in a bunch crossing: Luminosity Pn = e -m m n n! m = s L / f with Bunch crossing frequency  30 MHz Cross-section Massimiliano Ferro-Luzzi, CERN

Pile-Up Detector: principle N. Zaitsev’s PhD thesis Univ. van Amsterdam, 11/2000 ZB ZA RB RA ZPV Silicon R-detectors B A RB (cm) RB (cm) RA (cm) RA (cm) If hits are from the same track: peak P1 (peak size S1) RA ZPV - ZA RB ZPV - ZB = k  peak P2 (peak size S2) ZA - k ZB 1 - k or ZPV = ZPV (cm)  allows locating pp collisions Massimiliano Ferro-Luzzi, CERN

LHCb Pile-Up Detector: Implementation N. Zaitsev’s PhD thesis Univ. van Amsterdam, 11/2000 VD: add upstream two “R-only” modules Read out for trigger level 0 (Vertex Detector enters in level 1) Histogramming algorithm to distinguish single and multiple pp collisions. Performance multiple Schematically: (0) build a ZPV histogram (1) search highest peak P1 (peak size S1) (2) mask hits belonging to P1 (3) search next highest peak P2 (peak size S2) (4) classify: if S2<Slimit then single, else multiple Slimit sets efficiency and contamination. single True single True multiple Slimit peak size S2 Massimiliano Ferro-Luzzi, CERN

LHCb Pile-Up Veto: performance N. Zaitsev’s PhD thesis Univ. van Amsterdam, 11/2000 Occurrence rate of n-collision crossings as a function of luminosity Rate of “single-collision” B-events as a function of luminosity Before level-0 n = After level-0: without and with Pile-up veto  gain factor of at least 1.4 in B-event rate !! Massimiliano Ferro-Luzzi, CERN

Pile-Up Detector for Lumi Monitoring N. Zaitsev’s PhD thesis Univ. van Amsterdam, 11/2000 Most subsystems of LHCb are readout with highly biased trigger Pile-up: read out at level-0 (  unbiased ) large acceptance high and stable efficiency knows how many collisions in a bunch crossing (distinguishes bunch crossings with n=0, n=1 and n>1 collisions) Use of this feature increases statistical accuracy but systematics can arise from osmose between the various classes ( mostly between classes n=1 and n>1 !! Typical : (n=1)-efficiency  90% and (n>1)-fraction in (n=1)-class 12% ) Massimiliano Ferro-Luzzi, CERN

 - Estimators The following estimators were studied: (e0 , e1 , en>1= fractions of bunch crossings classified as having n= 0, n=1 and n>1 collisions) 1/0 ratio estimator m = e 1 / e 0 0-event estimator m = -ln(e 0) non-0-event estimator full sample estimator Does not need to know “osmotic pressure” between n=1 and n>1 !! Uses “either n=0 or n>0 ” logic  low systematic uncertainties e1 - P1 2 en>1 - Pn>1 2 De1 Den>1 c 2 = + e0 - P0 2 e1 - P1 2 en>1 - Pn>1 2 De0 De1 Den>1 c 2 = + + Massimiliano Ferro-Luzzi, CERN

0-event  - Estimator P0,meas = P0 + S an Pn “Osmotic flow” from class n>0 to class n=0 will cause a shift of m towards lower values. Monte-carlo: a1 = 0.094  0.002 an>1 negligible at LHCb luminosities mix event samples with 0, 1, …6 collisions (PYTHIA), in Poisson proportions add noise (to simulate beam-gas collisions, activity of detectors, etc.) fit distribution of largest peak size S1 to extract m P0,meas = P0 + S an Pn n>0 n=0 events 105 104 103 102 101 100 L [ 1032 cm-2 s-1 ] 5.0 2.5 0.5 Event Geometrical Cross type Acceptance section elastic 0.0 % 22 mb diffractive 46.7 % 25 mb inelastic 99.94 % 55 mb 0 10 20 30 40 50 60 70 80 90 peak size S1 Massimiliano Ferro-Luzzi, CERN

Summary LHCb is a forward-but-not-really experiment (10 mrad < q < 300 mrad) for studying CP-violation (asymmetries) and rare decays (relative to others) in the B-meson sector Preliminary studies for relative luminosity monitoring were carried out for the Pile-up detector - zero-event estimator is simplest, with lowest systematics - precision limited by knowledge of acceptance to diffractive events - we can expect a (systematic) uncertainty down to ~0.5 % for relative luminosity - statistics are  infinite … enough to measure individual bunch-bunch luminosities with ~0.5% statistical accuracy in about 20 seconds absolute normalization will be done by using calibrated processes and/or the TOTEM results (need monte-carlo in both cases) measure interaction spot shape with vertex detector ? Massimiliano Ferro-Luzzi, CERN