The Santa Cruz Linear Collider Group Simulation Effort

SiLC WorkshopPrague, Czech RepublicApril 26, 2007

Bruce Schumm

What are we working on?

• Tracker/Reconstruction/Fitter Validation Package

Working on making it platform-independent

• Pulse Development Simulation

Resolution, Efficiency vs. Strip pitch / Readout pitch

• Tracking with an All-Silicon Tracker

Non-prompt tracks

Performance vs. z segmentation

People

Myself, plus a number of very dedicated undergraduate physics majors:

Tyler Rice

Lori Stevens (summer: SLAC Pope Fellow)

Chris Meyer

Luke Kelley

We’re working on results for LCWS07; not too much news for this meeting

Tracking Efficiency and Momentum Resolution Analysis

Chris MeyerUCSC

ILC Simulation Reconstruction MeetingMarch 13, 2007

SODTrack Analyzer

• SODTrack reconstruction written by Fred Blanc; extends VXD stubs into central tracker. For now uses cheating for VXD stubs. Fitter: simple helix fit.

• Geared towards SiD detector concept

• Original tracking efficiency code written by Eric Wallace (UCSC Undergraduate, now at U of W) was implemented to create root output files

• The SID-01 files were used for ZPole bbbar events, and SID-AUG-05 for 500 GeV uds events.

Definition of findable track (filters)

• Cos() < 0.5• rOrg < 400 mm• Pathlength < 500mm• Final or Intermediate State Particle• Purity of hits on track > 0.79 from same MC Particle

Also: Events only accepted if cos(T) < 0.5 and thrust value > 0.94

Criteria developed by Bruce Schumm, Lori Stevens, and Tyler Rice after some study

ZPole bbbar

All tracks originating outside 1.4 cm aren’t found…

Total Efficiency for Prompt Tracks 500 GeV uds

Making a pT > 5 GeV cut increases efficiency about 0.3%

98.46% efficiency for pT >.75 GeV/c

98.77% efficiency for pT > 5 GeV/c

Efficiency vs pT-1 500 GeV uds

At higher pT-1 (lower pT) there is some inefficiency

Fake Rates vs. Momentum

Calculated from all SODTrack hits; “fake” is < 80% of hits from same MC Particle.

Range (GeV) Fake Tracks Total Tracks % Fake

0.5 – 1 42 1192 3.52349

1 - 2 70 3366 2.07962

2 - 5 60 4531 1.32421

5 – 10 35 2818 1.24202

10 – 20 34 1950 1.74359

20 – 40 12 1167 1.02828

40 – 75 5 494 1.01215

75 – 125 1 132 0.757576

125 – 200 0 25 0.0

200 – 500 0 0 0.0

Efficiency vs. 500 GeV uds

Let be the angle between a track and the thrust axisNo obvious effect as you go into the jet core (small )

pT > 0.75 GeV pT > 5.0 GeV

“Tri-plots”

Residuals

Error Matrix Expectation

Billior Calculation Expectation

Tracking Validation Package

Chris Meyer working on making package platform-independent – will run on ROOT output from any code framework. User would need to

• Apply selection algorithm to filter “findable” tracks (framework dependent, but our criteria are good guide)

• Do hit-by-hit MC Truth association

• Output track-by-track information in specified ROOT format

• Provide look-up table (in p and cos) ofexpected momentum resolution (can be gotten by running LCDTRK, or your favorite routine)

Pulse Development Studies

Have been exploring angle effects and strip/readout pitch for long (60 cm) ladders

Starting to get results now; expecting to have organized body of results for discussion in Hamburg

Preliminary (very) sense: Efficiency vs. entrance angle not a problem for L=60cm. Was a problem for L=167cm; exploring transition now

Resolution vs. Incidence Angle for 25 m Pitch SensorsRead Out with a 50 m Pitch (60 cm Ladder)

50/ 25 :: Phi vs. Resolution

0

2

4

6

8

10

12

14

-0.5 -0.4 -0.3 -0.2 -0.1 0

Phi angleR

MS

everyOther = 1 everyOther = 11 Net

50/ 25 :: Phi vs Resolution

2.5

2.7

2.9

3.1

3.3

3.5

3.7

3.9

4.1

4.3

-0.28 -0.23 -0.18 -0.13 -0.08

Phi angle

RM

S

everyOther = 1 everyOther = 11 Net

Track through read-out channel

Track through un-read-out channel

Average

75/ 37.5 :: Phi vs Resolution

0

10

20

30

40

50

60

70

80

90

-1 -0.8 -0.6 -0.4 -0.2 0

Phi angle

RM

S

everyOther = 1 everyOther = 11 Net

4

4.2

4.4

4.6

4.8

5

5.2

5.4

5.6

5.8

6

-0.3 -0.295 -0.29 -0.285 -0.28 -0.275 -0.27 -0.265 -0.26

everyOther = 1 everyOther = 11 Net

Resolution vs. Incidence Angle for 37.5 m Pitch SensorsRead Out with a 75 m Pitch (60 cm Ladder)

By way of comparison, for sensors w/ equal sense and readout pitch dd = 50 m = 4.6 m d = 75 m = 7.1 m

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

• Work done with Tyler Rice, Lori Stevens

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)

AxialBarrelTrackFinder (Tim Nelson, SLAC)

• Loops over all hits in each layer, from the outside in, and finds 3 “seed” hits, one per layer

• Performs CircleFit (alogrithm provided by Norman Graf) to seed hits

• If successful, looks for hits on the remaining layers that can be added to seed fit, refitting after each hit added.

• If at least 4 hits on track, and Chi^2 of fit reasonable, creates track object and adds to collection

• Only two (half-barrel) segments in z for now

AxialBarrelTrackFinder Performance

Define “findable” particle as

• Pt > 0.75

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

• Path Length > 500 mm

• |cos| < 0.8

Calculate efficiency for finding such non-prompt tracks

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

Found 5 Hits 131 (43%) 1

Found 4 Hits 100 (33%) 305

Not Found 73 (26%) --------

Total 304 (100%)

Further Exploration of AxialBarrelTracker (new)

Four-hit tracks very impure…

• Restrict to particles that have exactly one hit on each of the five layers five-hit track efficiency increases to 68%

• Additionally require that all hits on three-hit “seeds” come from same particle five-hit track efficiency increases to 87%

AxialBarrelTracker Modifications Under Development

• Require that of hits on track be at least within /2 of one another may reduce 4-hit fakes by up to 50%

• Project underway (Lori Stevens) to introduce z segmentation into pattern recognition (have only been requiring all hits have same sign in z up until now) may clean up three-hit seeds if segmentation is fine enough (?)

• Multiple passes through AxialBarrelTracker with initially pass having very stringent requirement on seed quality

The challenge now is to try to reconstruct particles with fewer than five hits!!

Some Other Studies (if Time Permits)?

Chris Meyer is beginning to look into jet energy resolution assuming perfect measurement of neutrals

• How low do we need to go in pt?

• What tracking efficiency is needed?

Wrap-up

UCSC undergrads working on basic but important studies – mostly, but not all, SiD-related. Tracker validation and pulse simulation more generic, but five-layer tracker studies clearly geared towards SiD. More results at Hamburg, and over summer.

RANDOM BACK-UP SLIDES

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”

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

Motivation

To explore the effects of limited detector resolution on our ability to measure SUSY parameters in the forward (|

cos()| > .8) region.