Test Beam 2003 Data Analysis and MonteCarlo Studies

1. Test Beam 2003Data Analysis and MonteCarlo Studies M.Barone Software and Analysis Meeting ATLAS/Frascati

2. Outline • H8 Test Beam 2003 • setup • data analysis • Results • MonteCarlo simulation • Garfield • Results • Work in progress • Conclusions M. Barone

3. 2003 H8 setup BML2 BOL2 BIL2 BIL1 BML1 BOL1 M. Barone

4. H8: data sample • 1 month of data taken with half “ATLAS like” gas fluxes • Runs collected in the period 19/7-22/8 (35 days – 830 hours) have been analyzed: corresponding to 14 Runs of ~100300 K events each. • Trigger Hodoscope • Runs taken under stable operating conditions: • Gas: Ar (93%) , CO2 (7%) at 3 bar absolute • Gas flow: 60 bar l/h BIL (~0.9 changes/day) 120 bar l/h BML (~1.2 changes/day) 180 bar l/h BOL (~1.0 changes/day) • HV : 3080 V • BML1 has the multilayer 2 with complete parallel gas distribution • Software: ATHENA version 6.6.0 used to get the MDT digits • PAW ntuples and ROOT trees available on lxcalc (and lxplus) • /scratch/nfs/data/athen/rootdata M. Barone

5. H8: analysis method – max tdrift • MDT spectra fitted with a double Fermi-Dirac function + constant to extract t0 and tmax • Drift time computed for the six barrel chamber (12 multilayers): tdrift = tmax – t0 • Typical statistical errors for runs with larger statistic (~300k evts): • error on t0 < 0.2 ns • error on tmax ~1 ns • error on tdrift ~ 1 ns max tdrift t0 = P5 tmax = P6 M. Barone

6. H8: analysis method 1 2 3 • Temperature correction • The drift times have been corrected to take into account changes in temperature T. The values of T were registered by temperature sensors • tdrift/ T = -2.4 ns/K (ATLAS 2003-001) Tubes grouped on the basis of their postion in the gas series (the gas flows from tube 1 to tube 3) Time spectra from tubes in different layers have been added together -> statistical uncertainty reduced Statistical errors on tdrift much larger for chambers of type 1 with respect to chambers of type 2 because of the different beam illumination Only tubes with SIGNAL/NOISE > 15 have been considered M. Barone

7. Exp. Results: Long Term Stability - BIL BIL1 BIL2 The values of the drift times for the 6 barrel chambers have been analyzed as a function of the data-taking time and fitted with a 1th order polynomial M. Barone

8. Exp. Results: Long Term Stability - BML BML1 BML2 M. Barone

9. Exp. Results: Long Term Stability - BOL BOL1 BOL2 M. Barone

10. Exp. Results: Drift Time and Serial Effect The average tdrift and RMS have been computed for each tube type, multilayer and chamber M. Barone

11. Experimental results Uniform response - in terms of drift time - from chamber to chamber within ±2÷3 ns Drift properties of the MDTs stable at the level of 0.04 ns/day on long term base and at the level of 1÷2 ns level on short term time base Dependence of the drift time on the tube series position clearly visible for all the multilayers, with the exception of multilayer 2 of the BML1 (parallel system): average drift time differences from 2 to 3.2 ns M. Barone

12. Explanation of the Serial Effect use the GARFIELD simulation to predict the impact of water vapor contamination on the MDT drift properties: tdrift/ H2O= 6.5ns/100ppm translate the measured water content into an equivalent water flux per end-plug (EHF/EP) estimate the impact of the serial effect on single tube space resolution The “serial effect” can be explained with a water contamination due to the NORYL end-plug permeability: water vapor accumulates in the gas mixture during its flow along the series. The estimated equivalent water flux is: EHP(bar l/day)/EP  0.0002 for all the chambers. The value is in good agreement with an approx. estimate based on NORYL-GFN3 characteristics: WF(bar·l/day)/EP = 0.000227 The impact of the “serial effect” on the single tube space resolution is negligible M. Barone

13. What’s next? The study on the stability and uniformity of the system is well documented in: M.Antonelli, M.Barone, F.Cerutti, M.Curatolo, B.Esposito, “Long term stability and uniformity studies of MDT chambers in the H8 2003 system test”, ATL-COM-MUON-2003-35, December 2003 Width of the TDC spectrum What about the shape of the spectrum? Are we able to reproduce the whole spectrum? MC simulation GARFIELD M. Barone

14. Garfield: parameters GAS • Garfield version 7.10 • Magboltz: simulation of the electron transport properties in a given gas mixture • Heed: simulation of the ionization of gas molecules by particles crossing the detector • signal calculation and processingMagboltz: Magboltz: CELL SIGNAL M. Barone

15. Garfield: drift velocity Computed from Magboltz 100 points in the E (or E/p) range M. Barone

16. Garfield: track and signal simulation 14600 tracks uniformely distribuited in the cell (from r=0 to r=1.46cm) For each track, the drift time of the first electron crossing the threshold is recorded M. Barone

17. Garfield: time spectrum Comparison between real data and simulated data (Ar-CO2 93-7% + H2O xppm; 14600 tracks uniformely distributed) black: Run 1559, BML2, ml2 red: H20 0ppm green: H20 50ppm blu: H20 100ppm purple: H20 200ppm In the tail : blue - black 20 ns - 83 ns  +1%Ar (Braccini, dec 2002) t = 0 is given by the primary muon M. Barone

18. Garfield: different gas mixture Different gas mixture (Ar-CO2 93.25-6.75% + H2O 100ppm; 14600 tracks uniformely distributed) M. Barone

19. Garfield: work in progress Magboltz: COLL = “number of collisions in multiplies of 960000, to be used to compute the transport properties. [...] The statistical accuracy of the drift velocity calculation improves with the square root of this parameter” Default: 10 x 960,000 collisions 80 coll  0.15% statistical error on vdrift 20 coll  0.25% statistical error on vdrift M. Barone

20. Garfield: work in progress • -rays • shorter drift time expected • Inefficiencies expected (for r  Rtube) What happens near the wire or for a track hitting the wire? … M. Barone

21. Goal Tune the MC simulation to obtain simulated spectra well reproducing the experimental data MC description matches the experimental data Y N • simulated spectra can give hints on chamber’s behavior, allowing to improve performance and to have a better understanding of the detector • r(t) relations can be automatically derived • one relation for each tube (instead of one per chamber) • no need of any hypothesis “ad hoc” (the effects of-rays, cluster position fluctuations, … , are already taken intoaccount by the simulation) appropriate corrections will be extracted from the data by means of proper algorithms M. Barone

22. Conclusions • We performed a systematic study of the drift behavior of the 6 barrel MDT chambers, using the H8 2003 test beam data. • The response of the chambers appears to be uniform and stable in time. • We deeply investigated the “serial effect”, that can be quantitatively explained in terms of water contamination. We are planning to tune the GARFIELD simulation in order to obtain simulated time spectra as similar as possible to real data. The following steps will depend on the success of the previous item. r(t) relations tracking M. Barone