Automated reconstruction of LAr
events at Warwick
J.J. Back, G.J. Barker, S.B. Boyd, A.J. Bennieston, B.
Morgan, YR
IOP meeting Manchester 28/11/2012
Y. Ramachers
Challenges
Single electron, 2 GeV in LAr:
● Easy 'by-eye' in isolation
● Challenging for computer
IOP meeting Manchester 28/11/2012
Y. Ramachers
Challenges
Spot the electron!
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2 GeV e- as before
81 cosmic muons in
14x14x20 m3 volume
in 1.4 ms readout interval.
Analysis 'by-eye' becomes
interesting...
A big challenge for any
automated analysis.
IOP meeting Manchester 28/11/2012
Y. Ramachers
Automated reconstruction at Warwick
Raw data:
(x,y,z,charge)
Detector/Simulation
incl. charge quench
in Genie/Geant4
Simulation:
(x,y,z,charge,truth_Id)
Pre-processing
DBScan event noise filter, dEdx filter,
charge smoothing, masking structures,
feature finding, utilities
Being validated
Shower/Track
segmentation decision
Exists, tested
Track segmentation
Shower Segmentation
- Cellular automaton
- LPC algorithm
LPC shower
finder, total energy,
direction, extent
Physics Structure container
Clusters of hits, each a reconstructed particle
Vertex finder
Particle Identification
Six discrimination variables
and multi-variate analysis TMVA
Truth value validation, track length calculation, observables, ...
LPC – vertex finder
Post-recon analysis
Kinematics calculator
IOP meeting Manchester 28/11/2012
Kalman filter fit
Y. Ramachers
Current status
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Shower / Track decision code being validated
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Track analysis automated, validated for CA, LPC not yet
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Shower analysis exists, no validation yet
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Particle ID, finished
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Papers:
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“Interest point detection for reconstruction in high granularity tracking
detectors”, B. Morgan, JINST 5 (2010) P07006
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“Electron-Hadron shower discrimination in a LArTPC”, submitted
(arXiv:1210.2215)
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CA paper in preparation
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Local Principal Curves (LPC) paper in preparation
IOP meeting Manchester 28/11/2012
Y. Ramachers
Current status
Code structure:
Module catalogue:
● Hit filter:
● Number of hits
● dE/dx filter
● DBScan Noise
● DBScan clustering
● Boolean cuts on truth values (for simulated data)
● Charge smoothing (for sim. Data)
● Cluster merging and stitching
● Feature point finder
● Hit/Region masking
● PCA transformation
● Cluster range calculation
IOP meeting Manchester 28/11/2012
Y. Ramachers
Automated reconstruction at Warwick
Raw data:
(x,y,z,charge)
Detector/Simulation
incl. charge quench
in Genie/Geant4
Simulation:
(x,y,z,charge,truth_Id)
Pre-processing
DBScan event noise filter, dEdx filter,
charge smoothing, masking structures,
feature finding, utilities
Being validated
Shower/Track
segmentation decision
Exists, tested
Track segmentation
Shower Segmentation
- Cellular automaton
- LPC algorithm
LPC shower
finder, total energy,
direction, extent
Physics Structure container
Clusters of hits, each a reconstructed particle
Vertex finder
Particle Identification
Six discrimination variables
and multi-variate analysis TMVA
Truth value validation, track length calculation, observables, ...
LPC – vertex finder
Post-recon analysis
Kinematics calculator
IOP meeting Manchester 28/11/2012
Kalman filter fit
Y. Ramachers
Cellular Automaton (CA) for tracks
µ
µ
µ
IOP meeting Manchester 28/11/2012
Validation on low energy
CCQE muon + proton events and
CCQE muon + proton + pion events.
Y. Ramachers
Cellular Automaton (CA) for tracks
Muon efficiency
Muon purity
Combined muon, proton factors
Have two dominant parameters:
● CA-angle
● Stitching angle
Overall particle efficiency / purity is at:
Muon Proton
Eff. 95-97% 95-98%
Pur. 91-92% 95-96%
IOP meeting Manchester 28/11/2012
Y. Ramachers
Automated reconstruction at Warwick
Raw data:
(x,y,z,charge)
Detector/Simulation
incl. charge quench
in Genie/Geant4
Simulation:
(x,y,z,charge,truth_Id)
Pre-processing
DBScan event noise filter, dEdx filter,
charge smoothing, masking structures,
feature finding, utilities
Being validated
Shower/Track
segmentation decision
Exists, tested
Track segmentation
Shower Segmentation
- Cellular automaton
- LPC algorithm
LPC shower
finder, total energy,
direction, extent
Physics Structure container
Clusters of hits, each a reconstructed particle
Vertex finder
Particle Identification
Six discrimination variables
and multi-variate analysis TMVA
Truth value validation, track length calculation, observables, ...
LPC – vertex finder
Post-recon analysis
Kinematics calculator
IOP meeting Manchester 28/11/2012
Kalman filter fit
Y. Ramachers
Most versatile: LPC
LPC on low energy electron showers.
IOP meeting Manchester 28/11/2012
Y. Ramachers
LPC capabilities
On tracks: N-dimensional feature finder
● Track separation at feature points
● Vertex finder (Blue point, top left pict.)
On showers:
● Shower/Track discrimination decision
● Shower finder / analysis
IOP meeting Manchester 28/11/2012
Y. Ramachers
LPC on vertex finding
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IOP meeting Manchester 28/11/2012
Segment event structure at feature point
Fit line to segment ends
Calculate line intersection or closest
approach for vertex finding
Better than 1 cm resolution on low energy
muon + proton CCQE events here.
Y. Ramachers
Automated reconstruction at Warwick
Raw data:
(x,y,z,charge)
Detector/Simulation
incl. charge quench
in Genie/Geant4
Simulation:
(x,y,z,charge,truth_Id)
Pre-processing
DBScan event noise filter, dEdx filter,
charge smoothing, masking structures,
feature finding, utilities
Being validated
Shower/Track
segmentation decision
Exists, tested
Track segmentation
Shower Segmentation
- Cellular automaton
- LPC algorithm
LPC shower
finder, total energy,
direction, extent
Physics Structure container
Clusters of hits, each a reconstructed particle
Vertex finder
Particle Identification
Six discrimination variables
and multi-variate analysis TMVA
Truth value validation, track length calculation, observables, ...
LPC – vertex finder
Post-recon analysis
Kinematics calculator
IOP meeting Manchester 28/11/2012
Kalman filter fit
Y. Ramachers
Particle ID
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Assumption: Isolated hit structures obtained from a previous step, i.e.
assume to analyse single clusters!
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Step 1: Principal component transformation of hit cloud.
Step 2: Calculate 6 discrimination variables:
(1) Lateral structure – Core-to-Total ratio ('lat')
(2) Hit concentration – Coulomb energy of hits as a measure of concentration ('con')
(3) Initial dE/dx – slice cluster longitudinally, take starting part only, ('dedx')
(4) Spatial extent - Calculate convex hull, get spatial extent of structure in all
three principal axes, ('extx, exty, extz')
Step 3: Multivariate Analysis – run TMVA4 and pick best method
(typically boosted decision trees)
IOP meeting Manchester 28/11/2012
Y. Ramachers
Particle ID
Example low energy π0 shower and PCA transform
Core 9.61cm x 9.61cm
for 'lat' variable
Main p
rincipa
l axis
Lateral projection plane
Axes units in [mm]
IOP meeting Manchester 28/11/2012
Y. Ramachers
EM/(all pions+protons+muons)
Signal is an isolated EM shower; background all muons, protons, pions, other mesons
Signal/Background distribution
from CNGS neutrino beam
IOP meeting Manchester 28/11/2012
Signal/Background distribution uniform
between 10 MeV and 4.5GeV.
Y. Ramachers
Conclusion
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Fully automated reconstruction of LAr events is possible with this
software, how well is not known yet.
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Step-wise validation is ongoing.
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Most promising algorithm so far: local principal curves (LPC)
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All methods at Warwick are N-dimensional – can run on 2D images,
not only full 3D.
Two more publications in the pipeline: CA and LPC, particle ID is
submitted and on arXiv.
Final target would be to build a physics reconstruction study.
IOP meeting Manchester 28/11/2012
Y. Ramachers