energy calibration with compton data
DESCRIPTION
Energy Calibration with Compton Data. June 23, 2006. Outline. Revisit “Z” using DA Compton calibration SA Compton calibration Using production on carbon, lead SA gains vs LMS How to improve LMS performance - PowerPoint PPT PresentationTRANSCRIPT
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Energy Calibration with Energy Calibration with Compton DataCompton Data
June 23, 2006June 23, 2006
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OutlineOutline
Revisit “Z” using DA Compton Revisit “Z” using DA Compton calibrationcalibration
SA Compton calibrationSA Compton calibration Using production on carbon, leadUsing production on carbon, lead SA gains vs LMSSA gains vs LMS How to improve LMS performance How to improve LMS performance Need a consistent normalization scheme for Need a consistent normalization scheme for
the LMS gains during the production period.the LMS gains during the production period.
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Target-Hycal DistanceTarget-Hycal Distancefrom Double Arm Calibrationfrom Double Arm Calibration
Mean=1.017 Mean=1.001
before after
Calibration procedure:
Gain correction factors are found through cluster coordinates and Z
(E(el)=Eb/[1+2*Eb/me*sin2((el)/2)])
Incorrect value of Z will result in elasticity distribution not centered
exactly at 1 ! try to vary z, recalibrate, check elasticity
(e1+e2)/Eb (e1+e2)/Eb
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Target-Hycal Distance Target-Hycal Distance from Double Arm Calibration (cont)from Double Arm Calibration (cont)
731.4 < Z < 732.1 cm
Resolution does not change with z
Mean of the elasticity distribution vs hycal-target distance (Z) used in calibrationfor 5 groups of runs
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Target-Hycal DistanceTarget-Hycal Distancefrom Compton kinematicsfrom Compton kinematics
Could obtain Z from Could obtain Z from Compton kinematics, Compton kinematics, setting zsetting z11=z=z22::
z=(Eb*rz=(Eb*r11*r*r22/m/mee/2)/2)0.50.5
Not so sensitive to the Not so sensitive to the gainsgains
Sensitive to beam Sensitive to beam misalignment: misalignment: changing x by 1 mm changing x by 1 mm changes z by ~6-7 cmchanges z by ~6-7 cm
Run 4871, Be target
Z (cm)
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Target-Hycal DistanceTarget-Hycal Distancerun by runrun by run
Difference between the first group of carbon runs andthe rest of the runs should be: 7.62 cm We see: ~6.52
9Be : Z=732.08 cm12C (ave): Z ~733 cm
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Single Arm Compton Single Arm Compton CalibrationCalibration
Objectives:Objectives: Monitor gain change during Monitor gain change during
the production data takingthe production data taking Compare with the LMS Compare with the LMS
behaviorbehavior Use LMS gains in the part of Use LMS gains in the part of
HyCal where no Compton HyCal where no Compton gains are availablegains are available
ProcedureProcedure:: 320 production runs with 320 production runs with
carbon target and 70 runs carbon target and 70 runs with the lead targetwith the lead target
Look for events for one neutral Look for events for one neutral cluster and fill the following cluster and fill the following distribution:distribution:eeclcl/e/eCC,,
eeCC=Eb/(1+Eb/m=Eb/(1+Eb/mee*sin*sin22((/2))/2)) Fit Fit !! gain corr=1/mean gain corr=1/mean
carbon
lead
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SA Calibration: PSSA Calibration: PSCarbonCarbon
~ 30 % eff.
Require1 hit in the PSwithin the physicstime window <5% eff
PS cut
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SA Calibration: PS (cont)SA Calibration: PS (cont)LeadLead
~ 8% eff.
Very low PS efficiency for lead runs! lose most of events
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Life and times of module Life and times of module 14941494
SA Lead
LMS
SA carbon
Gain correction factors relative to the snake calibrations vs run #
Reference pmt
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2 parts to life of module 2 parts to life of module 14941494
Relative to snake #1 Relative to snake #2
LMS data is not properly normalized for this time period
Looks good
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Look closerLook closer
LMS and SA gains are consistent but LMS is more “scattered”
SA gains: stat. errors are small (for carbon)Systematic uncertainty comes mostly from possible beam misalignment: shift of 1 mm in X results in ~1% change of the gain value
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SA gains vs LMSSA gains vs LMS
Could find correlation between the LMS and SA gains
lead
carbon
carbonlead
carbon carbon
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Tri-modal behavior of LMSTri-modal behavior of LMS
What are we going to do about this?
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SummarySummary
~~120 modules can be calibrated with the SA gains120 modules can be calibrated with the SA gains Good agreement with the Double Arm gainsGood agreement with the Double Arm gains Reasonable agreement is observed between the SA and Reasonable agreement is observed between the SA and
LMS gains for both the carbon and lead targetsLMS gains for both the carbon and lead targets Can/Will find the correlation between LMS and SA gains for Can/Will find the correlation between LMS and SA gains for
every moduleevery module LMS gains look reasonable but are scattered and sometime LMS gains look reasonable but are scattered and sometime
“tri-modal”“tri-modal”!! what to do about it? what to do about it? Parameterize LMS with SA gains?Parameterize LMS with SA gains? How to correct for “tri-modality”?How to correct for “tri-modality”? Need to use a consistent scheme for LMS normalization Need to use a consistent scheme for LMS normalization
throughout the run throughout the run !! currently it is wrong for runs <4838 currently it is wrong for runs <4838