1. GLAST Calorimeter Crystal Position Measurement Zach Fewtrell, NRL/Praxis GLAST Integration & Test Workshop SLAC July 14, 2005

2. Data Set 4 TOWER DATA, ZERO SUPPRESSED ~600K events ~3K hits per cal xtal. -All values extracted from SVAC tuple files. - Runs 135002769 - 135002780

3. Software Environment TRACK EXTRAPOLATION & CUSTOM TUPLE GENERATION - Compiled C++ using ROOT libraries. - Based on David Smith's/Benoit Lott's anaMeritNtuple.C - More inclusive of partial xtal hits. TUPLE ANALYSIS & PLOT GENERATION - ROOT interactive.

4. Plan of action 1 – Retrieve main Tracker track position & vector at end of track. 2 – Using LAT & Cal geometry constants, extrapolate track into the Z-center of each Cal layer. 3 – extract cal xtal hit info for appropriate crystal. 4 – calculate longitudinal component of tkrPos – calPos. 5 – ‘diff’ is the main variable I study.

5. Initial cuts 1 – TkrNTracks > 1 2 – Track can cut tower boundary, i skip layers where track crosses the boundary. 3 – Partial hits allowed, but I only measured the hits which contain the middle of the track. - in any given layer, this should be the strongest hit. - mostly driven by lack of desire to write more code, plenty of partial track-hits already included. 4 – cal has to have a readout (ene > 0) duh!

6. Step 1: Xtal Ends

7. - Tracker extrapolated pos -vs- Cal Recon xtal pos - scatter plot of all xtal hits.. - Cal clips xtal pos to CsI length, you don’t see the matching tails. This adds bias to cal recon pos near xtal end. - - NOTE: This effect is probably less w/ high energy showers. - FIRST CUT: tkrPos > 23-28mm from xtal end - SECOND CUT: calPos > 3mm from xtal end Step 1: Xtal Ends

8. Step 2: CalTkr Diff –vs- energy

9. Step 2: Diff –vs- ene sigmas X X X Error from pedestal noise. (back-of-envelope)

10. Step 2: Diff –vs- ene 1 – Position sigmas at low energies < 10 MeV per xtal consistent w/ propagated pedestal sigmas. 2 – plots from now on are cut at xtal ene > 7 MeV.

11. All Crystals: Diff -vs- xtal index

12. Distribution of single channel mean difference

13. Distribution of single channel sigmas - consistent w/ other studies.

14. Distribution of reduced  2

15. Worst case channel T4 L7 X10

16. Best Case T1 L3 X10

17. Typical Channel – T0 L1 X10