Transcript ppt

A First DC2 Analysis with New Recons
• DC1 Recap
• Recon Re-write Review
– TkrRecon
– CalRecon
• Good Energy Analysis
• PSF Analysis
Bill Atwood, SCIPP/UCSC, June, 2005
1
GLAST
DC1 Recap
Cuts: 1/1
An extensive analysis was performed
to optimize PSF and energy resolution
while maintaining the maximum Aeff.
This was the first complete analysis
done using the Geant 4 Simulation
(previous Glast Analysis used the
Gismo simulation)
Ratio 95/68 > 3
Cuts: 2/1
Meets SR
Events Eff.: 94.5%
Cuts: 3/2
Cuts: 3/4
Events Eff.: 52.3%
Events Eff.: 19.1%
Eff. = 82%
Bad-Cal = 4.5%
Bill Atwood, SCIPP/UCSC, June, 2005
2
GLAST
Background Rejection in DC1
3 Classes of Background after selection
for good energy and direction
reconstruction
Prob. g > .5
Upward moving events
Earth Limb events
Downward moving events
Prob. g > .9
A Classification Tree analysis was constructed
allowing cutting on the probability that an event
was a g (vs. Background)
However – to meet the Science Req. for Background
contamination – the remaining Aeff was lower then
the goal (it did meet the Sci. Req.)
Bill Atwood, SCIPP/UCSC, June, 2005
3
GLAST
Conclusions from DC1
The Status of the Reconstruction in GLAST was marginal
1) The code had been patch, re-patched, etc. many times
2) The code had become needlessly complex and
essentially un-maintainable
3) The algorithms (particularly for the Calorimeter) were
undeveloped
Major Effort was Launched to completely re-write
the Tracker and Calorimeter Recon
1) Emphasis on uniformity and simplicity
2) Migrate related task to one area
3) Re-vamp and re-assess poorly functioning
algorithms (esp. Vertexing and Calorimeter)
Bill Atwood, SCIPP/UCSC, June, 2005
4
GLAST
Tracker Recon Re-write
TDS Classes Condensed and
Simplified:
–
–
–
–
–
–
–
–
–
–
–
TkrFitHit
TkrFitMatrix
TkrFitPar
TkrFitPlane
TkrFitTrackBase
TkrKalFitTrackBa
se
TkrKalFitTrack
TkrPatCand
TkrPatCandHit
TkrRecInfo
TkrTrackTab
– TkrTrackParams
– TkrTrackHit
– TkrTrack
Program architecture simplified
Bill Atwood, SCIPP/UCSC, June, 2005
5
External Controls
Control Name
Internal
Variable
Def.
Value
Description
MinEnergy
m_minEnergy
30.
Min. energy to use
for setting search
regions
SigmaCut
m_sigmaCut
9.0
Sigma cut for
picking up points
FirstTrkEnergyFr
ac
m_1stTkrEFrac
.8
First track energy
fraction
MinTermHitCount
m_termHitCnt
16
Min. no. of hits on
best track to
terminate search
MaxNoCandidates
m_maxCandidate
s
10
Max. allowed number
of candidate tracks
MaxChisq
m_maxChiSqCut
40.
Max allow Combo Pat.
Rec. Chisq. (1st
fit)
NumSharedFirstCl
usters
m_hitShares
6
Number of first
clusters which can
be shared
MaxNumberTrials
m_maxTrials
50
Max. number of trial
candidates to test
FoVLimit
m_PatRecFoV
.19
Minimum cos(theta)
for track trials
MinCosKink
m_minCosKink
.7
Minimum cos(theta)
for a track kink
MaxTripletRes
m_maxTripRes
30.
Max. un-normalized
residual for first 3
TkrPoints
GLAST
New Vertex Algorithm
Vertex Location
Put Vertex
at Radiator
Mid-Point
Combining Tracks
Preferred Solution
W RADIATOR If 2 Tracks share the same
first hit
SSD PLANE
SUPPORT PANEL
Found
Tracks
Next Best Solution
All Other Case
Put Vertex at Z location
of start of the 1st Track
Bill Atwood, SCIPP/UCSC, June, 2005
PPair  (C11  C 21 )1  (C11  P1  C 21  P2 )
C Pair  (C11  C 21 )1
Put Vertex SUPPORT PANEL
DOCA Point
If DOCA location of 2 tracks
lies before 1st Hit
Multivariate Averaging: PPair
C11  P1  C 21  P2

C11  C 21
W RADIATOR
SSD PLANE
where Pi are the parameter vectors of the
combination (Pair) and tracks (P1 and P2)
and Ci are the covariance matrices
1
T 1
 2  ( P1  PPair )T C Re
s 1 ( P1  PPair )  ( P2  PPair ) C Re s 2 ( P2  PPair )
where
C Re s1, 2  C1, 2  C Pair
Found
Tracks
The parameter vectors are (x, Sx, y, Sy)
6
GLAST
CalRecon Re-write
1) Put GLAST’s Fracture Energy Back Together
1 GeV
g
Thin Radiator
Hits
Gap Between
Tracker Towers
Thick Radiator
Hits
Blank Radiator
Hits
Gap Between
CAL. Towers
Calorimeter
Xtals
2) Better Background Rejection Cuts
Shower Shape parameters
3) Move code to where it belongs!
AnalysisNtuple
CalRecon
Bill Atwood, SCIPP/UCSC, June, 2005
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Leakage out
CAL. Back
GLAST
CalRecon Re-write (cont.)
A Major Change: Replace Layer-by-Layer Analysis with Energy-Moments
Energy Moments: Same as Classical Mech. Mass moments with energy
replacing mass (see Goldstein) (first used by S. Ritz in GLAST)
Long. Moment
Moments
LSQ Fit to Layers
CalDirErr  cos 1 ( tˆMC  tˆCal )
Bill Atwood, SCIPP/UCSC, June, 2005
Trans. Moment
8
GLAST
Good Energy Analysis
But First: The New Data Sets
- Major effort by many people
- Took a couple of shots to get right
- 1.5x106 All Gamma*
- 6
run 23-June-2005
x106 Orbit-Average
Background
Initial Cuts:
1) CalEnergyRaw > 5 MeV and
CalCsIRLn > 4 rad. len.
2) Tkr1ZDir < -.2 (FoV)
color range: 0 - 150
run 24-June-2005
- All data run on SLAC Batch Farm
available at GLAST ftp site
- These are the first large data sets
using new Recons
Pruning Selections:
1) TkrNumTracks > 0 standard mode
2) TkrNumTracks = 0 Cal-Only Events!
*All Gamma:
2p str. , 18 MeV – 180 GeV,
1/E Spectrum
Bill Atwood, SCIPP/UCSC, June, 2005
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GLAST
Energy Assessment
E
EvtDeltaEoE =
was EvtMcEnergySigma
E
Top plots show dep. on
MC parameters
Bottom plots show dep. on
Recon parameters
Bill Atwood, SCIPP/UCSC, June, 2005
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GLAST
Good Energy CT Analysis
Data divide into Energy Ranges using CalEnergyRaw
MedCal
LowCal
CalEnergyRaw < 350 MeV
Bill Atwood, SCIPP/UCSC, June, 2005
350 - 3500 MeV
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HiCal
CalEnergyRaw > 3500 MeV
GLAST
Energy CT Details
1) Produce a set of variables that are ~independent of cos(q) and E
Parametric function of Tkr1ZDir and EvtLogEnergy
2) Define Class "GoodEnergy" & "BadEnergy"
GoodEnergy:
E
 .35 (will explore dependence on this)
E
2) Derive a CT for each of the EvtEnergyRaw Bins
Low CAL
Bill Atwood, SCIPP/UCSC, June, 2005
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GLAST
more Energy CT Details
Med CAL
High CAL
Bill Atwood, SCIPP/UCSC, June, 2005
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GLAST
Energy CT Dependencies
Since the energy resolution is improved – try more restrictive
definition of "Good Energy"
E
 .20
E
Eff.
E
 .30
E
100
80
100
80
60
60
40
40
20
20
0
0
NOISE
Anomaly
E
 .35
E
100
80
60
DC1 Choice
Select this one
40
20
0
Expected Behavior
This is part of a problem at
High Energies .... more later
Use of
Tkr1TotTrAve
in Cal Low CT
What's happening here?
Bill Atwood, SCIPP/UCSC, June, 2005
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GLAST
Preliminary DC2 Energy Resolution
On Axis
Integrated Over FoV
DC1 Resolution
DC1 Resolution
DC2 Resolution
DC2 Resolution
High Energy
Deficit caused
by Pat. Rec.
Confusion!
Aeff x W = 4.02 m2-str
Bill Atwood, SCIPP/UCSC, June, 2005
Aeff x W = 2.76 m2-str
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GLAST
Root Cause of Hi E Deficit
Pictures and Words....
Incoming g
Event #6
Bad Cal Dir
100 GeV g
These events come from Old CalRecon
but effect remains.
First attempt to fix problem:
USE CAL DIRECTION
Event #9
Bad Cal Dir
Incoming g
100 GeV g
Missed Track
Event #6
Bad Cal Dir
Clearly there's more
work to do here!
Missed Track
Bill Atwood, SCIPP/UCSC, June, 2005
16
GLAST
A First PSF Analysis for DC2
Strategy: Divide and Conquer!
1) Split Events in Thin and Thick
Conversion locations
2) For Events with > 1 Tkr. Vertices
decide whether or not to use
vertexed solution
Example: Thin Radiator – Vertex CT
Bill Atwood, SCIPP/UCSC, June, 2005
17
GLAST
More PSF CT Details
Strategy: Divide and Conquer!
3) Find and tag (a la probability)
Events with large PSFs
4) Finally – add a knob to describe
quality of reconstruction
- Using a REGRESSION TREE
Bill Atwood, SCIPP/UCSC, June, 2005
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GLAST
Preliminary DC2 PSFs
Integrated over FoV
On Axis
DC2
DC1
Sel. 1
Sel. 2
Sel. 3
Sel. 4
Sel. 1
Sel. 2
Sel. 3
Sel. 4
PSF68(100MeV)
4.7
4.1
3.6
3.0
4.2
3.8
3.3
2.6
PSF95/PSF68
4.4
3.0
2.3
2.2
3.2
3.0
2.6
2.3
Rel. Eff. (%)
100
94.5
52.3
19.1
100
95.2
74.0
46.2
Bill Atwood, SCIPP/UCSC, June, 2005
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GLAST
DC2 Background Rejection
Nothing has been done with the recently run data.
(only became available late last Friday)
But – Here's is a peek –
Data: 5.1x106 Orbit Ave. Bkg.
Preemptory cuts:
.75x106 All Gamma
1) GoodEnergy.Prob > .25
2) AcdDOCA > 250
3) Only Thin Radiator Events Analyzed so far
15642 Events
CalXtalRatio 
Bill Atwood, SCIPP/UCSC, June, 2005
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942 Events (Good News)
No. Xtals  .01ETOTAL
No. Xtals
GLAST
more DC2 Background Rejection
CalXtalMaxEne  Max . SingleXtalEnergy
CalMIPRatio 
Bill Atwood, SCIPP/UCSC, June, 2005
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MIPEnergy Expected
ETOTAL
GLAST
more DC2 Background Rejection
EvtECalTransRms 
Energy & Angle Compensate CalTransRms
Note: In AnalysisNtuple all variables beginning with
EvtE..... are previously defined variables which
have been compensated for log(E) and cos(q)
dependencies.
Bill Atwood, SCIPP/UCSC, June, 2005
22
GLAST
Conclusions
The 1st DC2 Workshop has already accomplished 90+%
its goals! - look at all the work it stimulated!
The Recon re-writes show good improvements in
- Energy Reconstruction
- PSF
- New Variables to Reject Background
The (first) large data samples are providing the next
level of insight in the Recons
- TkrRecon need more work in the area of
very High Energy reconstructions
- CalRecon needs MIP finding and more work
to refine moments analysis (emphasis on directions)
Bill Atwood, SCIPP/UCSC, June, 2005
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GLAST