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HyCal Energy Calibration using dedicated Compton runs

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Presentation on theme: "HyCal Energy Calibration using dedicated Compton runs"— Presentation transcript:

1 HyCal Energy Calibration using dedicated Compton runs
Yelena Prok PrimEx Collaboration Meeting July 29, 2005

2 Objectives Check the quality of calibration
Monitor gain drift with time Comparison with LMS monitoring Obtain gains for every run (possibly) Compton runs first calibration second calibration 10/09 11/22

3 Compton Runs Carbon target, beam energy 4.9<E<5.5 GeV
7 groups of runs, in chronological order Data taken on the following dates: Oct 10, 2004 Oct 19, 2004 Nov 2, 2004 Nov 3, 2004 Nov 9, 2004 Nov 14, 2004 Nov 19, 2004 Radiation Incident Run 5050 1 2 3 4 5 6 7 Calibration constants change in the database

4 Selecting pairs of clusters
|((e1+e2)/ebeam-1.0)|<0.2 emin > 0.5 GeV Area around the central hole (§ 6 cm), and the area most affected by the pair contamination are cut out |Ebeam-EC|<0.4 GeV, EC=me*sin(/[2*sin2(/2)*tan(e)]-me Ebeam – EC (GeV)

5 Selecting electrons and photons
Detector Match package is used to select electrons/photons (based on the HyCal-VETO match in x) Some distributions for selected pairs: |1 - 2| (deg)

6 Calibration Procedure
“Expected” energy of the photons/electrons can be calculated from the Compton kinematics: E(el)=Ebeam/[1+2Ebeam/me*sin2((el)/2)] For each HyCal module, divide the measured cluster energy by the “expected” value: Gain_Corr is defined: EHyCal/E(el) Module 1498 Using photons Gain_Corr = 1.038  » 3.8 %

7 Results: Gain_Corr vs Modules
photons Following the outlined procedure, gain correction factors (Gain_Corr) are found for modules, using selected photons, electrons and a mixed sample of both. 7 colors correspond to 7 groups of Compton runs Depending on the module and the group #, Gain_Corr varies from 0.95 to 1.11 In order to apply this correction, gain factor from the calibration database would have to be DIVIDED by Gain_Corr electrons

8 Photons vs Electrons Group 2
Modules (lost files during first calib.) Group 7, closest to the second calib. Following the radiation incident Group 5 Gain_Corr factors, found with an electron sample are consistently higher (1-3%) that the ones found using photons

9 Photons vs Electrons Mean gain correction factors (+/- RMS) vs group number are plotted . Green: electrons Blue: photons Black: mixed sample Top plot: x >0 Bottom plot x<0 Electron gains are consistently higher Possible explanation: The shower depth correction was derived for the photons Group number

10 Left(x>0) vs Right (x<0)
A spatial asymmetry in the gain correction factors is observed between the left and right sides of the calorimeter Modules with x<0 have larger gain correction factors, with a larger gain drift in time Gain_Corr x<0 x>0 module

11 Left (x>0) vs Right (x<0)
Distributions of gain correction factors, plotted separately for each group of runs The asymmetry is particularly strong in group 5 (following the radiation incident); it is not seen in group 7 (closest to the last calibration) gr 2 gr 2 gr 3 gr 3 gr 5 gr 4 gr 6 gr 7

12 Left (x>0) vs Right (x<0)
Mean gain correction factors (+/- RMS) vs group number are plotted for the photon sample Gain correction factors are larger for the modules with x<0 by 1-5% Possible explanation: due to the initial beam angle, one side of the detector is more affected by the radiation damage than the other one x<0 x>0 group number

13 Beam position matters x variation Gain correction factors from two sides of the detector will converge into one value if the center of HyCal is moved artificially (in x or y) Evaluation of the gain correction factors is sensitive to the beam offset (position on the target) and the beam angle. The alignment procedure corrects for the beam offset in x and y, but gains remain sensitive to the beam angle Offset of 1 mm in x results in 1% change of the gain correction value Need to have information from the BPMs and the photon profiler x<0 Gain_corr x>0 Shift in x0 (in arb units) y variation y>0 Gain_corr y<0 Shift in y0 (arb units)

14 Gain drift with time Selected 5 modules on each side of the calorimeter x>0:1487,1488,1489,1490,1491 x<0:1496,1497,1498,1499,1500 Evaluated gain correction factors are with respect to the last calibration for all groups Colors correspond to different modules Due to the incident, gain factors of the modules with x<0, have changed by »15-20% x>0 x<0 group number radiation incident

15 Comparison with LMS Gain correction factors for the five selected modules with x<0 are plotted vs group number, along with the LMS gains for these modules The two gains follow the same pattern More work needs to be done to understand how to use the LMS gains along with the gain correction factors Gain_corr LMS gains Modules more spread out LMS_gain*Gain_corr

16 Calibration by Iteration
After the gain correction factors (gi) are found for the central modules of clusters, the corrections are applied, and the procedure is repeated: New gi=[ icluster members Ei/gi ]/Ec To check the effect of this procedure, the quantity (e1+e2)/ebeam is plotted, before and after the application of gain correction factors Results converge after 3-4 iterations Group 3 after before

17 More Results Group 4 Group 2 Group 7 Group 5

18 Summary of Results Group # Mean before Mean after  before  after
 (%) 1 (low stat) 1.018 1.011 0.0157 0.0147 6 2 0.989 1.002 0.0184 0.0151 18 3 1.029 1.001 0.0193 0.0154 20 4 1.028 0.0188 0.0153 19 5 0.983 0.0488 70 1.006 0.0168 0.0144 14 7 1.013 0.0148 3

19 Conclusions/Outlook What remains to be done What we learned
Gains drift with time We are sensitive to the beam position Gain correction factors found using the Compton data are compatible with LMS patterns Radiation incident has caused a dramatic change in the gain factors in some modules This calibration method has resulted in the energy resolution theoretically expected for the detector What remains to be done Include low energy events to increase the number of modules that can be analyzed Need to have beam position information from the beam line devices Check the linearity of energy response Understand how to use the LMS data Check results with the matrix inversion method Single arm Compton?


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