Post on 20-Jan-2018
description
December, 16 2008 1
Calibration of electromagnetic calorimeter of Hall A DVCS
experiment
Eric FUCHEYPh.D Student @ Laboratoire de Physique
CorpusculaireUMR 6533 CNRS/IN2P3Université Blaise Pascal
Clermont-Ferrand
December, 16 2008 2
Outline• 1- Motivations of calibration• 2- Real data calibration
– Method– Results
• 3- Simulated data calibration– Method– Results
• 4- Conclusion
December, 16 2008 3
Outline• 1- Motivations of calibration• 2- Real data calibration
– Method– Results
• 3- Simulated data calibration– Method– Results
• 4- Conclusion
December, 16 2008 4
Experimental layout• Calibration for ep->ep0
• Incident beam : E = 5.75 GeV during experiment– Scattered electron measured by HRS– 2 photons issued from 0 measured by 132 PbF2 blocks
calorimeter– Recoil proton detected by proton array -> not used
December, 16 2008 5
• Looking at real and simulated 0 data sets• We measure
• We can reconstruct for each event a missing mass:
with and
• We can either reconstruct for one block a missing mass distribution for all events with one photon hitting this block.
222XXX PEM
Xeep
2212 ' qqkMkE pX 221
2 ' qqkkPX
December, 16 2008 6
Mp2
• Reconstructed missing mass distribution in each block depends on block position in calorimeter.
• Effects assumed to come only from calorimeter. => necessity to calibrate calorimeter to correct these effects.
December, 16 2008 7
• For analysis, we need to fit 0 data set with 0 simulated set to extract cross section
• unconstistency of resolutions for real and simulated.=> necessity to calibrate and to smear simulated.
December, 16 2008 8
Outline• 1- Motivations of calibration• 2- Real data calibration
– Method– Results
• 3- Simulated data calibration– Method– Results
• 4- Conclusion
December, 16 2008 9
Method of calibration (real)• Goal of calibration: to find for each block of the
calorimeter a coefficient in order to reconstruct in each block a missing mass squared in accordance with Mp
2.
• Coefficient of the form: for block# ( = 0,…,89)
222pXX MMM
December, 16 2008 10
Method of calibration (real)• For an event i, a photon is in block #a, the other is in
block #b.
• Correcting each photon energy:
• Recomputing MX2 with these corrected energies, and
filling #a and #b blocks distributions.
iX
aX
i
a
E
Mq
2
2
iX
bX
i
b
E
Mq
2
2
December, 16 2008 11
Method of calibration (real)• Fit distributions by a gaussian
-> Mean of the gaussian => New missing mass squared value. New calibration coefficient
• Correct 2 photons to reconstruct missing mass -> calibration coefficients for each block are correlated. necessity to calibrate by steps. necessity to estimate calibration quality for each step.
December, 16 2008 12
Corrections• Before filling distributions, we apply some corrections:
– By effects of resolution, missing mass squared and invariant mass ( ) are correlated
– -> possibility to improve resolution. with R = 13 GeV
– Additional cuts:• 0.4 GeV2 < MX
2 < 1.4 GeV2 ; 0.105 GeV < m < 0.165 GeV.• k’ = pHRS +/- 4.5% ; r-function > 0.005• Each photon is in a calibrated block, and E > 1.0 GeV• -6.0 cm < zvtx < 7.5 cm
mmGeVRMMrawXcorrX )(22
2212
21 qqqqm
December, 16 2008 13
Quality calibration control
• Once iteration completed :– Plot reconstructed missing mass squared value for each
block over all blocks– Fit by a constant– Check for deviation from reference value, and dispersion
(RMS).
December, 16 2008 14
Results (real)• Quick convergence from iteration 0 to 5-6• After, averaged MX
2 oscillates, RMS is stable.=> Converged
December, 16 2008 15
Results (real)• Ex: Iteration #11 Dispersion is low, Calibration has
converged
• Pion mass deviation less than 1 MeV
December, 16 2008 16
Outline• 1- Motivations of calibration
– Experimental layout• 2- Real data calibration
– Method– Results
• 3- Simulated data calibration– Method– Results
• 4- Conclusion
December, 16 2008 17
Method of calibration (simulated)• Same principle, except we try to match simulated with
data:
– Searching for a calibration coefficient:
– Searching to bring each block simulated resolution ( of gaussian fit) to real block resolution.
=> also need for each block a « smearing » coefficient
realXsimuXX MMM,
2
,
22
222realsimu
December, 16 2008 18
Method of calibration (simulated)• For an event i, a photon is in block #a, the other is in block #b.
• Correcting each photon energy:
• Smearing each photon energy: picking a random variable in a gaussian distribution.
: corrected energy, :
• Recomputing MX2 with these corrected energies, and filling #a
and #b blocks distributions.
iX
aX
i
a
E
Mq
4
2
iX
bX
i
b
E
Mq
4
2
2
22
arealasimu
a
2
22
brealbsimu
b
December, 16 2008 19
Quality calibration control
• Once iteration completed :– Plot MX
2|simu - MX2|real for each block over all blocks and (MX
2|simu) - (MX
2|real) for each block over all blocks – Fit each plot by a constant
December, 16 2008 20
Results (simulated)• Averaged MX
2 converges until iteration 15, then stable• RMS does not stop decreasing: <0.001 since iteration
#30
December, 16 2008 21
Results (simulated)
• Since ~iteration #20, seems to be converged.• Check out for resolution to conclude
December, 16 2008 22
Results (simulated)• Quick convergence averaged (MX
2) of from iteration 0 to 6-7, stable after.
• averaged (MX2) RMS stable since Iteration #15
December, 16 2008 23
Results (simulated)
• Invariant mass deviation due to calibration is still less than 1 MeV
• Since ~iteration #20, dispersion is low, calibration has converged.• Only advantage to go further is to improve MX
2 dispersion.
December, 16 2008 24
Outline• 1- Motivations of calibration
– Experimental layout– Consequences on measurements
• 2- Real data calibration– Method– Results
• 3- Simulated data calibration– Method– Results
• 4- Conclusion
December, 16 2008 25
Conclusion• Our goal was to calibrate the calorimeter with our set of
Kin3 0 data and our set of Kin3 0 simulated to be able to make consistent fit for analysis.
• We have reached regime of stability for both real calibration and simulated calibration iteration processes=> Calibration has been succesfully completed.