glast lat offline softwareworkshop - slac, jan. 16-19, 2001 tkr software review -- jan. 17, 20011...

GLAST LAT Offline Software Workshop - SLAC, Jan. 16-19, 2001

TKR Software Review -- Jan. 17, 2001 1

Topics for the TKR Software ReviewTopics for the TKR Software ReviewTracy Usher, Leon RochesterTracy Usher, Leon Rochester

• Progress in reconstruction• Reconstruction – short-term plans• Simulation • Calibration issues• Balloon-specific support• Personnel and Schedule



Tracker ReconTracker ReconWhere were we at the last workshop?Where were we at the last workshop?

• Status at last workshop– Pattern recognition & track

fit linked together within the context of the Kalman Filter.

– Tracker reconstruction incorporated within the Centella framework

– Tracker reconstruction used in the analysis of the Test Beam data and Monte Carlo.

Thanks Jose!

• Plan at that time– Separate the track fit from

the pattern recognition. – Create:

• Track Extrapolator• Pattern Recognition• Track Fit (Kalman Fit)

Standard HEP Solution

• Personnel changes– Jose departs– Tracy and Leon arriveTracker Recon “in the shop”



Tracker ReconTracker ReconWhat is the goal of the reconstruction?What is the goal of the reconstruction?

• To reconstruct the the direction and energy of gamma ray conversions in the tracker.– Must find and reconstruct the

trajectories of the e+ e- pair– Must determine the energy of the

e+ and the e- (individually)– Must find the common point of

origin of the e+ e- pair– From this information, determine

the energy and trajectory of the incident gamma ray

• Find and reject background



Tracker ReconTracker ReconNew kids have a few misconceptions…New kids have a few misconceptions…

– How hard can it be?– What happened to the magnetic field?– This lead stuff is not helping the

tracking!– What happened to the stereo layers?– Isn’t the Monte Carlo supposed to also

give you the answer?– Electrons don’t get along well with

others

– Learning c++ will be easy!

Ok, this is not your standard tracking problem…

Where/how do we get started?



Tracker ReconTracker ReconReality according to Tbsim…Reality according to Tbsim…



Tracker ReconTracker ReconHow do the new kids proceed?How do the new kids proceed?

Need to:– Learn (enough) c++ to be

able to understand and modify the code – ultimately write new code

– Learn the GLAST “system”– Learn how the existing code

works– Get the full appreciation for

the problem– Make progress along the

path set forth at the last workshop

Approach:– Take on the task of

separating the pattern recognition from the track fit

– Work within the Test Beam / Centella framework

– Implement a new pattern recognition (“link and tree”) which is independent of the Kalman Filter

– Attempt to perform a simple pointing resolution study comparing fit tracks to the first links



Tracker ReconTracker ReconPattern Recognition – Kalman Filter approachPattern Recognition – Kalman Filter approach

• Kalman Filter– Particle trajectories are straight lines– Changes in trajectory due to multiple

scattering are gaussian in nature– Pat Rec looks for gammas (vee’s),

then for particles• But…

– Multiple scattering is not entirely a gaussian process

– Bremsstrahlung results in many low(er) energy e+ and e- tracks along principal path

• Leading to large scattering angles for principle e+ or e-

• And confusing the pattern recon



Tracker ReconTracker ReconPattern Recognition – simple approachPattern Recognition – simple approach

• Implement a “Link and Tree” algorithm – Simplest algorithm to dive into the code– Allows one to follow pre-shower development– “Longest, Straightest” branch is trajectory of the primary e+ or e-

• Can be projected to calorimeter for initial clustering• Passed to Kalman Filter for track fit

– Other branches can (hopefully) give more information on energy of primary e+ or e- pair

– As with Kalman Filter, Pattern Recognition runs in 2-D• Association to 3-D done after initial 2-D tracking finding

– Strategy is to find individual tracks first• Then put tracks together to form/find gamma conversions




• Algorithm– Links formed between all

pairs of clusters in adjacent layers

– Beginning with the top most layer containing cluster hits, links are combined to form a tree structure

– Links are not allowed to be shared

– Clusters are allowed to be shared

– Trees sorted by longest and straightest for association to 3-D




• Current Status– “Link and Tree” algorithm

in 2-D operational– Rudimentary association of

2D tracks to 3D operational• Tracks start in same layer• Tracks have same length• Straightest tracks

associated– Longest, straightest tracks

are fit by Kalman Filter– Only looking at single

charged particles at this point

• Not quite ready for gammas



Tracker ReconTracker ReconSome initial resultsSome initial results

• Look at TBsim e+ runs– Positrons incident normal to the first tracker layer– Energies: 0.1, 0.25, 0.5, 1.0, 2.0, 5.0, 10.0, 20.0 GeV

• 3-D Track Reconstruction of e+ requirements:– Track must be 12 or more layers in length– Must start in first tracker layer

• Look at:– Track recon parameters

• Number reconstructed and passing above cuts• Length of tracks• Etc.

– Pointing at start of track comparing• Compare between fit parameters at first hit and first link




•Track Accounting = 951/1000 = 95.1%

•Number tracks/event<N> = 1.6

•Length of tracks<L> = 11.1




Track Recon Efficiency 3D(>12 Layer 3D tracks)

40

45

50

55

60

65

70

75

80

85

90

95

100

0 5 10 15 20

Track Energy (GeV)

Effi

cien

cy (%

)

Fraction 3Dfound/event

Average Number 3D TracksFound Per Event

0

0.5

1

1.5

2

2.5

3

0 5 10 15 20

Track Energy (GeV)A

vera

ge N

umbe

r Tr

acks

/Eve

nt

# 3D Tracks




•3-D Pointing Resolution•Take mean value

•2-D Pointing Resolution X•Fit Gaussian

•2-D Pointing Resolution Y•Fit Gaussian




Resolution in 3-D pointing

for Kalman Fit and for first link is approximately the same…

Track Pointing comparisonKalman Fit to First Link

0

5

10

15

20

25

30

35

40

45

50

0 5 10 15 20Track Energy (GeV)

Ang

le re

solu

tion

(mr)

Kalman Fit 3DpointingFirst Link pointing



Tracker ReconTracker ReconSome initial conclusionsSome initial conclusions

• “Link and Tree” Pattern Recognition– Simple algorithm implemented within the Centella context– Shows promise for:

• Finding primary e+ and e- tracks • Keeping track of pre-shower development – aid in helping to

keep track of energy loss of the primary tracks• Providing initial pointing into the calorimeter

– Don’t need to know the energy before getting the track– Track finding – calorimeter – track fit – calorimetry – track fit - …

– More careful studies needed before really saying anything about pointing resolution…

– Needs refinement (= rewrite) if really want to proceed…• New kids are getting to be conversant in c++• New kids have learned a (small) part of the GLAST system• New kids have a much greater “appreciation” of the problem



Tracker ReconTracker ReconShort term plansShort term plans

• Balloon flight needs tracking soon!– Tested tracking exists within the centella framework– Move the existing code

• The first goal is to move the existing TB_recon into the Gaudi framework

• Allows us to stop working on legacy code. – Connect to New Geometry

• This will allow us to develop code which can be used for all GLAST configurations.

– Write new data converters for • Test beam data and MC• Glastsim output• Cosmic data / Balloon flight

• Continue looking at Pattern Recognition alternatives



Calibration IssuesCalibration IssuesThere are three parts to each problem below: the calibration

algorithm, the database, and the automated production process

• Bad Strips– Hot/dead strips– Common mode failures: Chips, ladders, towers

• Alignment– Current status– What’s ultimately needed

• TOT (Time-over-Threshold)– Calibration signal?



Bad StripsBad Strips

• Currently, the bad strips are recorded in an ASCII file, by layer and strip number. These are used by the reconstruction to kill bad strips and to join clusters separated only by bad strips.

• For the full detector:

– The production database will record bad strips at different levels: for example, chips, detectors, ladders, layers, and (shudder!) towers.

– Since the state of the strips will need to be monitored regularly, we particularly need a reliable automatic system to detect bad elements and update the database.



TKR AlignmentTKR Alignment

An alignment was done on the BTEM using test beam data, first with entire layers, and then with individual ladders.



Finding ResidualsFinding Residuals

Fitting planes

Method: Find the a track. Fix a line through the clusters in planes 8 & 15. Calculate the residuals with respect to that line.

Residual



Layers and LaddersLayers and LaddersThe original residuals were as big

as 200 μm. (σ 40 μm)

Layers were shifted to minimize the residuals.

Two layers can be fixed (or the overall change of position and slope can be set to zero) because there are two degrees of freedom in the original problem

The resulting residual distribution has σ 25 μm.



Layers and Ladders (2)Layers and Ladders (2)

To improve resolution, the positions of individual ladders were adjusted with respect to ladders above and below, using normally-incident tracks, withthe final σ 15 μm.



Alignment: the New FrontierAlignment: the New Frontier

A complication:In the full detector, many tracks will cross ladders and towers.

Slanted tracks allow the alignment of adjacent ladders and towers. This is more complicated because now all the elements are tied together with springs, and there are six parameters per object:

x, y, z, and 3 rotations.

Solving this problem usually leads to big matrices!



Time-over-Threshold (TOT)Time-over-Threshold (TOT)For each layer, the TOT is measured by

combining all the fast-OR’s for each event.The TOT measures the width of the pulse at

some fixed pulse height, and is thus roughly proportional to the largest charge deposited on any strip in the layer.

t1

t2

Distribution of TOT values for a 20 GeV positron run (normal incidence) with a Landau fit overlaid. (Test beam data)



TOT (2)TOT (2)In the test beam, the TOT was sensitive to the photon conversion point. But this was at

normal incidence. Will this still work for angled tracks? We have test beam data to answer this question! (I think…)

•How do we calibrate the TOT?

•What is the correct level?

γ

e+

e-



Plans for SimulationPlans for Simulation• Glastsim/GEANT4 outputs MC truth• Digis produced from MC hits

– Digis and hits can be read by Recon• Upgrades to Generation

– Realistic Geometry– Fluctuations (for TOT)

• Upgrades to Digitization– Charge sharing– Dead strips/chips/SSDs– Overlay of background

• Model• Real data

– TOT• Common Geometry



Charge Sharing, Fluctuations and Charge Sharing, Fluctuations and all thatall that

Calculated TOT response is sensitive to details of the generation and digitization.

Low

Medium

High



Balloon-specific SupportBalloon-specific Support

Certain aspects of the balloon-flight data may require special support.

• Special reconstruction algorithms– Dealing with high backgrounds– Picking out photons in hadronic showers

• Analysis– Projecting to active targets– Finding interaction vertex

• Calibration– Dead/hot strip list– Probably no alignment required to

reconstruct tracks, but we may want to demonstrate that we can do it. A use for the expected 107 protons?

– Same for TOT



A Preliminary Personnel/Task A Preliminary Personnel/Task InventoryInventory

Institutions

Pisa

Santa Cruz

Santiago de Compostela

SLAC

People

2

3

1 (through mid-Feb)

2

Tasks

Port of Recon to Gaudi

Development of Recon

Simulation

Calibration



A Preliminary Personnel/Task A Preliminary Personnel/Task InventoryInventory

Institutions

Pisa

Santa Cruz

Santiago de Compostela

SLAC

People

2

3

1 (through Mid-Feb)

2

Tasks

Port of Recon to Gaudi

Development of Recon

Simulation

Calibration

And tentative set of matches...



TKR Software ScheduleTKR Software ScheduleNear-term (Feb—Mar)• Port recon to Gaudi• Read TB data/MC -- verify port• Refine recon algorithms• Implement digitization• Read/recon cosmic data• Specify calibration databases

Medium-term (Apr—May)• Refine digitization• Read/recon Glastsim/GEANT4 digis• Implement calibration databases• Implement single-tower alignment

algorithm• Test alignment code with cosmics• Implement hot/dead strip calibration• Write special code for balloon flight • Refine TKR-specific GEANT4 code

Long-term (June— )• Refine balloon recon• Perform balloon analysis• Connect new geometry • Implement full detector geometry • Develop multi-tower alignment

algorithm• Demonstrate full detector capability

– gamma detection and measurement– background rejection– optimized PSF– automated calibration



That’s All

Folks!

glast lat offline softwareworkshop - slac, jan. 16-19, 2001 tkr software review -- jan. 17, 20011...

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