Cluster Threshold Optimization from TIF data

1. Cluster Threshold Optimization from TIF data David Stuart, UC Santa Barbara July 26, 2007

2. The TIF cosmic data allows a study of clustering thresholds. Optimizing the thresholds could be useful to: Reduce the impact of noise clusters on analyses. Understand noise effects, e.g., the TOB wings. Understand clustering effects. Understand low-level detector performance, to be compared to simulation. How low can we go without introducing noise effects, or how high can we cut without introducing inefficiency? Motivation

3. Method • General approach: • Study clusters on very well measured tracks. • Compare to all clusters. • Details: (Since my processing is non-standard. Define it here.) • Measure pedestals and noise and flag bad channels. • Do clustering and write clusters to ascii files. • Read cluster files on my mac and apply geometry and alignment. • Use alignment corrections that yield TOB = 50 m and TIB = 150 m. • Do tracking • Simple combinatoric seed finder with road search hit matching. • R- and R-Z done separately, ignore stereo hits.

4. Cluster charge with low thresholds Initially, run with low thresholds: 4*noise for seed, 3*noise for neighbor strips. Use zero-suppressed run 6505. Large noise contribution visible when looking at all found clusters.

5. Cluster charge with low thresholds Look only at hits on well measured tracks: At least 7 hits, P(c2)>0.001, nearly vertical tracks close to origin. Peak position: 82 counts Peak position: 126 counts There is very little noise.

6. Cluster charge with low thresholds Look only at hits on well measured tracks: At least 7 hits, P(2)>0.001, nearly vertical tracks close to origin. Here, I plot the cluster charge divided by average noise of clusters’ strips. Peak position: 25.6 Peak position: 28.4

7. Low charge hits on tracks Even with very tight track quality cuts, I find some low charge hits on tracks. E.g., below is the TOB charge in a high stats run with tighter cuts. What are the low Q hits? There is a hint that edge strips contribute some of them, but the dominant source is grazing tracks.

8. Low charge hits on tracks An example of a low charge hit on a clean track.

9. Low charge hits on tracks Track direction Zero charge strips because this is a zero-suppressed run. With pitch of 183 m, expect avg of 46 counts/strip. I don’t understand why <Qstrip> degrades toward the back of the sensor. These are not the sort of hits we care about for clustering. In collisions, only very low pT curlers will produce them (and we want to be blind to them).

10. Cluster charge cut • So, I conclude that the following are fully efficient cluster charge cuts: • For TIB, Q>40 • For TOB, Q>70 Peak position: 82 counts Peak position: 126 counts

11. Seed strip threshold (max charge strip) Next, I look at the maximum charge strip within clusters (excluding 1-strip clusters). • Different shape for off-track TOB hits due to high angles, xy on the low end, rz on the high. • Presence of hits with MaxQ/Noise<4 due to using a 1-strip, 2-strip algorithm rather than seed, neighbor algorithm. • For TIB, Q/Noise > 6 is fully efficient. For TOB, Q/Noise > 8 is fully efficient. • Use Q/Noise > 6 for both; to keep it simple.

12. Neighbor strip threshold (minQ) • Next, I look at the minimum charge strip within clusters. For this, redo clustering with: • 1-strip thr = 6*noise, 2-strip thr = 2*noise, Qtotal > 40 or 70. There is no obvious minimum cut.

13. Neighbor strip threshold (minQ) • There is no obviously preferred minimum cut. That is not surprising, since hits can easily • have small charge neighbor strips from capacitive coupling or delta-rays or noise. • The minimum charge cut will not change the efficiency of finding the cluster, • but it will change the correctness of its position. • Adding one noise (or -ray) strip at 2*noise will bias the hit by about 10 m. • Failing to add a strip will cause a similar bias. • These effects cannot be measured in cosmics with the current alignment precision. • However, the wing noise in the TOB is more likely to add many noise strips, • so I think a higher neighbor threshold is more robust. • This can be quantified by comparing how much the wings cause hits to move • as a function of the neighbor threshold. I’m still processing that check. • For now, 3*noise seems to be a reasonable choice.

14. Seed strips and TOB wings As an interesting side note, I noticed that the seed strip threshold is the dominant rejector of TOB wing induced noise hits. Raising the neighbor threshold doesn’t matter much. If I cluster without a seed strip requirement, i.e., allow clusters with at least two neighbor strips above 2*noise, there is significant noise from the wings. That disappears with the 6*noise seed strip requirement. The FED’s zero-suppression does not require a seed strip. Adding such a requirement should efficiently reject wing occupancy at the readout level.

15. Summary • Looking at hits on very well measured tracks, I find the following cluster thresholds • to be broadly optimal: • Seed strip: 6*noise • Neighbor strip: 3*noise (to be optimized in collisions) • Total charge: 40 counts for TIB and 70 counts for TOB. • These are higher than commonly used values. • I plan to repeat this for runs taken at different times to confirm stability, then I’ll • compare to simulation.