December, 16 20081 Calibration of electromagnetic calorimeter of Hall A DVCS experiment Eric FUCHEY…

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




• 4- Conclusion

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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

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• 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

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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.

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• 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.

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• 4- Conclusion

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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

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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


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.


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


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).


Results (real)• Quick convergence from iteration 0 to 5-6• After, averaged MX

2 oscillates, RMS is stable.=> Converged


Results (real)• Ex: Iteration #11 Dispersion is low, Calibration has

converged

• Pion mass deviation less than 1 MeV


Outline• 1- Motivations of calibration

– Experimental layout• 2- Real data calibration



• 4- Conclusion


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


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


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


Results (simulated)• Averaged MX

2 converges until iteration 15, then stable• RMS does not stop decreasing: <0.001 since iteration

#30


Results (simulated)

• Since ~iteration #20, seems to be converged.• Check out for resolution to conclude


Results (simulated)• Quick convergence averaged (MX

2) of from iteration 0 to 6-7, stable after.

• averaged (MX2) RMS stable since Iteration #15


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.


Outline• 1- Motivations of calibration

– Experimental layout– Consequences on measurements

• 2- Real data calibration– Method– Results


• 4- Conclusion


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.

December, 16 20081 Calibration of electromagnetic calorimeter of Hall A DVCS experiment Eric FUCHEY…

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