1. Energy Calibration with Compton Data
June 23, 2006

2. Outline Revisit “Z” using DA Compton calibration
SA Compton calibration
Using production on carbon, lead
SA gains vs LMS
How to improve LMS performance
Need a consistent normalization scheme for the LMS gains during the production period.

3. Target-Hycal Distance from Double Arm Calibration
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
after
before
Mean=1.001
Mean=1.017
(e1+e2)/Eb
(e1+e2)/Eb

4. Target-Hycal Distance from Double Arm Calibration (cont)
Mean of the elasticity
distribution vs hycal-target
distance (Z) used in calibration
for 5 groups of runs
731.4 < Z < cm
Resolution
does not change with z

5. Target-Hycal Distance from Compton kinematics
Could obtain Z from Compton kinematics, setting z1=z2:
z=(Eb*r1*r2/me/2)0.5
Not so sensitive to the gains
Sensitive to beam misalignment: changing x by 1 mm changes z by ~6-7 cm
Z (cm)
Run 4871, Be target

6. Target-Hycal Distance run by run
Difference between the
first group of carbon runs and
the rest of the runs should
be: 7.62 cm We see: ~6.52
9Be : Z= cm
12C (ave): Z ~733 cm

7. Single Arm Compton Calibration
Objectives:
Monitor gain change during the production data taking
Compare with the LMS behavior
Use LMS gains in the part of HyCal where no Compton gains are available
Procedure:
320 production runs with carbon target and 70 runs with the lead target
Look for events for one neutral cluster and fill the following distribution:ecl/eC,
eC=Eb/(1+Eb/me*sin2(/2))
Fit ! gain corr=1/mean
carbon
lead

8. SA Calibration: PS Carbon
~ 30 % eff.
PS cut
Require
1 hit in
the PS
within
the physics
time
window
<5% eff

9. SA Calibration: PS (cont) Lead
~ 8% eff.
Very low PS efficiency for lead runs! lose most of events

10. Life and times of module 1494
SA Lead
SA carbon
LMS
Reference pmt
Gain correction factors relative to the snake calibrations vs run #

11. 2 parts to life of module 1494 Relative to snake #1
LMS data is not properly normalized
for this time period
Looks good

12. Look closer LMS and SA gains are consistent
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
LMS and SA gains are consistent
but LMS is more “scattered”

13. SA gains vs LMS carbon lead lead carbon carbon carbon
Could find correlation between the LMS and SA gains

14. Tri-modal behavior of LMS
What are we going to do about this?

15. Summary ~120 modules can be calibrated with the SA gains
Good agreement with the Double Arm gains
Reasonable agreement is observed between the SA and LMS gains for both the carbon and lead targets
Can/Will find the correlation between LMS and SA gains for every module
LMS gains look reasonable but are scattered and sometime “tri-modal”! what to do about it?
Parameterize LMS with SA gains?
How to correct for “tri-modality”?
Need to use a consistent scheme for LMS normalization throughout the run ! currently it is wrong for runs <4838