SCIPP R&D on Time-Over-Threshold Electronics and Long-Ladder Readout

Beijing Linear Collider WorkshopBeijing, ChinaFebruary 4-8 2007

Bruce Schumm

BRIEF SUMMARY OF STATUS

Testing of 8-channel (LSTFE-1) prototype fairly advanced:

•Reproducible operation (4 operating boards)•Most features working, with needed refinements understood•A number of “subtleties” (e.g. channel matching, environmental sensitivity) under control•Starting to make progress on fundamental issues confronting long-ladder/high-resolution limit.

Design of 128-channel prototype (LSTFE-2) well underway (April submission)

Now for the details…

Noise vs. Capacitance (at shape = 1.2 s)

Measured dependence is roughly(noise in equivalent electrons)

noise = 375 + 8.9*C

with C in pF.

Experience at 0.5 m had suggested that model noise parameters needed to be boosted by 20% or so; these results suggest 0.25 m model parameters are accurate

Noise performance somewhat better than anticipated.

Observed

Expected

1 meter

EQUIVALENT CAPACITANCE STUDY

Channel-to-Channel Matching

Offset: 10 mV rms

Gain: 150 mV/fC <1% rms

Occupancy threshold of 1.2 fC (1875 e-) 180 mV

± 2 mV (20 e-) from gain variation± 10 mV (100 e-) from offset variation

Power CyclingIdea: Latch operating bias points and isolate chip from outside world.

• Per-channel power consumption reduces from ~1 mW to ~1 W.

• Restoration to operating point should take ~ 1 msec.

Current status:

• Internal leakage (protection diodes + ?)degrades latched operating point

• Restoration takes ~40 msec (x5 power savings)

• Injection of small current (< 1 nA) to counter leakage allows for 1 msec restoration.

Future (LSTFE-2)

• Low-current feedback will maintain bias points; solution already incorporated in LSTFE-2 design

Preamp Response

Power Control

Shaper Response

Power Cycling with Small Injected Current

Solution in hand to maintain bias levels in “off” state with low-power feedback; will eliminate need for external trickle current

Measured Noise vs. Sum of Estimated Contributions

Estimated strip noise actual 60 m

strip (part of estimate)

Projected strip noise for 20 m strip (not part of

estimate)

Measured noise

Sum of estimates

Simulation Results from the Santa Cruz Linear Collider Group

Beijing Linear Collider WorkshopBeijing, ChinaFebruary 4-8 2007

Bruce Schumm

RECONSTRUCTING NON-PROMPT TRACKS

• Snowmass ‘05: Tim Nelson wrote axial-only algorithm to reconstruct tracks in absence of Vertex Detector

• UCSC idea: use this to “clean up” after vertex-stub based reconstruction (VXDBasedReco)

• About 5% of tracks originate beyond the VXD inner layers

• For now: study Z-pole qq events

Cheater• VXDBasedReco had not yet been ported to

org.lcsim framework, so…

• Wrote “cheater” to emulate perfectly efficient VXDBasedReco; assume anything that can be found by VXDBasedReco is found and the hits flagged as used

• Loops over TkrBarrHits and MCParticles, finds particles with rOrigin < 20mm and hits from those particles, removes them from collections

• rOrigin defined as sqrt(particle.getOriginX()^2 + particle.getOriginY()^2)

Total Momentum (GeV)

Number of hits per track

5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 105 110 115 120 125 130 135 140 145 150

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

6.5

7.0

7.5

8.0

8.5

9.0

9.5

10.0

10.5

11.0

11.5

12.0

12.5

13.0

13.5

Entries : 6712 XMean : 4.5455 XRms : 11.547 YMean : 0.28509 YRms : 0.85769

Hit count vs. Total Momentum

Number of hits on track

Tra

ck M

omen

tum

What’s Left after “Cheating”? (258 events, no backgrounds)

“Good”

“Other” “Knock-on” (less than 10 MeV)“Looper”

Total hits: 30510 100%Good hits: 1754 5.7%Looper hits: 13546 44.4%Knock-on hits: 10821 35.5%Other hits: 4389 14.4%

Total tracks: 6712 100%Good tracks: 445 6.6%Looper tracks: 459 6.8%Knock-on tracks: 3303 49.2%Other tracks: 2505 37.3%

Radius of Origin (mm) Of Tracks

And where do these tracks originate?

Hit Count

0 200 400 600 800 1,000 1,200 1,4000

100

200

300

400

500

600

700

Entries : 2505 Mean : 863.47 Rms : 394.27

rOrg other tracks

Hit Count

0 200 400 600 800 1,000 1,2000

200

400

600

800

1,000

1,200

Entries : 3303 Mean : 935.72 Rms : 290.46

rOrg knock on tracks

Hit Count

Radius (mm)

0 200 400 600 800 1,000 1,2000

10

20

30

40

50

60

70

80

90

Entries : 459 Mean : 602.79 Rms : 358.51

rOrg looper tracks

Hit Count

Radius (mm)

0 200 400 600 800 1,000 1,200 1,40005

101520253035404550

Entries : 445 Mean : 369.71 Rms : 358.00

rOrg good tracks

“Good” “Looper”

“Knock-on” “Other”

AxialBarrelTrackFinder PerformanceDefine “findable” particle as

• Pt > 0.75

• Radius of origin < 400 mm (require four layers)

• Path Length > 500 mm

• |cos| < 0.8

Number of “findable” particles per event

Particle is “found” if it is associated with a track with four or more hits, with at most one hits coming from a different track. All non-associated tracks with pt>0.75 and DCA < 100mm are labeled “fake”.

Particles Fakes

Not Found 175 (46.4%) --------

Found 4 Hits 88 (23.3%) 270

Found 5 Hits 114 (30.2%) 1

Total 377 (100%)

Particles can be found more than once… (but there’s only one entry per particle in the previous table)

Number of times each foundparticle is found

But there’s really no reason why the algorithm should be this inefficient for these non-prompt particles

Radius of origin of missed particles

We have a few ideas as to why these are being missed, and are looking into it.