1. LNF, 26 gennaio 2004 1 Test Beam 2003 Data Analysis and MonteCarlo Studies M. Barone Software and Analysis Meeting ATLAS/Frascati

2. LNF, 26 gennaio 2004M. Barone 2 Outline H8 Test Beam 2003  setup  data analysis  Results MonteCarlo simulation  Garfield  Results Work in progress Conclusions

3. LNF, 26 gennaio 2004M. Barone 3 2003 H8 setup BIL2 BIL1 BOL1 BML1 BOL2 BML2

4. LNF, 26 gennaio 2004M. 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%), CO 2 (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

5. LNF, 26 gennaio 2004M. 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 t0 = P 5 tmax = P 6 max tdrift

6. LNF, 26 gennaio 2004M. Barone 6 Tubes grouped on the basis of their postion in the gas series (the gas flows from tube 1 to tube 3) H8: analysis method 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) 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) Time spectra from tubes in different layers have been added together -> statistical uncertainty reduced Only tubes with SIGNAL/NOISE > 15 have been considered 123 Statistical errors on tdrift much larger for chambers of type 1 with respect to chambers of type 2 because of the different beam illumination

7. LNF, 26 gennaio 2004M. 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 1 th order polynomial

8. LNF, 26 gennaio 2004M. Barone 8 Exp. Results: Long Term Stability - BML BML1 BML2

9. LNF, 26 gennaio 2004M. Barone 9 Exp. Results: Long Term Stability - BOL BOL1 BOL2

10. LNF, 26 gennaio 2004M. Barone 10 Exp. Results: Drift Time and Serial Effect The average tdrift and RMS have been computed for each tube type, multilayer and chamber

11. LNF, 26 gennaio 2004M. Barone 11 Experimental results Uniform response - in terms of drift time - from chamber to chamber within ±2÷3 ns 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 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

12. LNF, 26 gennaio 2004M. Barone 12 Explanation of the Serial Effect 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 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 Chamber type 1,2-2,3 (ns) 1,2-2,3 EHF(bar·l/day)/EP BIL3.249.10.000209 BML2.030.20.000192 BOL1.929.30.000211 1) use the GARFIELD simulation to predict the impact of water vapor contamination on the MDT drift properties:  t drift /  H 2 O= 6.5ns/100ppm 2) translate the measured water content into an equivalent water flux per end-plug (EHF/EP) 3) estimate the impact of the serial effect on single tube space resolution 1) use the GARFIELD simulation to predict the impact of water vapor contamination on the MDT drift properties:  t drift /  H 2 O= 6.5ns/100ppm 2) translate the measured water content into an equivalent water flux per end-plug (EHF/EP) 3) estimate the impact of the serial effect on single tube space resolution

13. LNF, 26 gennaio 2004M. 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 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 What about the shape of the spectrum? Are we able to reproduce the whole spectrum? What about the shape of the spectrum? Are we able to reproduce the whole spectrum? Width of the TDC spectrum MC simulation GARFIELD

14. LNF, 26 gennaio 2004M. Barone 14 Garfield: parameters pressure3 bar temperature300 K Ar93.0 % CO 2 7.0 % GAS high voltage3080 V n_electrons25 gain20000 muon energy180 GeV transfer function (t/  ) 2 e - t/   6 ns electronic noiseENC = 4200 SIGNAL 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 processing Magboltz: Magboltz: geometrytube radius1.46 cm CELL

15. LNF, 26 gennaio 2004M. Barone 15 Garfield: drift velocity Computed from Magboltz 100 points in the E (or E/p) range

16. LNF, 26 gennaio 2004M. 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

17. LNF, 26 gennaio 2004M. Barone 17 Garfield: time spectrum Comparison between real data and simulated data (Ar-CO 2 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 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

18. LNF, 26 gennaio 2004M. Barone 18 Garfield: different gas mixture Different gas mixture (Ar-CO 2 93.25-6.75% + H2O 100ppm; 14600 tracks uniformely distributed)

19. LNF, 26 gennaio 2004M. 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 20 coll  0.25% statistical error on vdrift 80 coll  0.15% statistical error on vdrift

20. LNF, 26 gennaio 2004M. Barone 20 Garfield: work in progress  -rays  shorter drift time expected  Inefficiencies expected (for r  R tube ) What happens near the wire or for a track hitting the wire? …

21. LNF, 26 gennaio 2004M. Barone 21 Goal MC description matches the experimental data MC description matches the experimental data 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 into account by the simulation) 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 into account by the simulation) appropriate corrections will be extracted from the data by means of proper algorithms Y N Tune the MC simulation to obtain simulated spectra well reproducing the experimental data

22. LNF, 26 gennaio 2004M. 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 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 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