LAr TPC: Status and progress in
data analysis efforts
Y. Ramachers
(University of Warwick)
IDS-NF, RAL 22/09/2010
Y. Ramachers
IDS-NF, RAL 22/09/2010
Y. Ramachers
IDS-NF, RAL 22/09/2010
Y. Ramachers
Update: A. Rubbia@EuroNu2010
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The Data Analysis Challenge
Liquid argon TPC’s reconstruct events with bubble-chamber
quality
But, automatic
reconstruction in
software is still not
established
Why?
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2. It’s not so easy!
 Tracks and showers develop
side-by-side in the same
volume
 topologically complicated
 No well defined start point
for what initiated the event
 Very high density of
information: mm-scale energy
deposits, delta-rays,
vertices, kinks etc
 Multiple scattering occurring
continuously throughout
volume
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ICARUS, arxiv:0812:2373
Past Developments: ICARUS
ICARUS Collab., Phys. Rev. D74, 112001 (2006)
 Tools developed over
the years by the ICARUS
project: hit definition,
clustering, 2D and 3D
track fitting
 Low multiplicity neutrino
events reconstructed
from a 50L module
exposed to the CERN
WANF beam
 Some degree of visual
scanning/selection
involved before applying
algorithms
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Warwick work in progress
Experimental programme:
Purity control
➢ Measurements with SiPM arrays → spatial resolution
➢ Alternative: CMOS/CCD camera and optics
➢ Optical Fibre array readout
➢ Solid Argon test
➢ Cold electronics
➢
Computational programme:
Monte-Carlo event generation
➢ Novel high-granularity tracking analysis
➢ Charge transport simulation – signal generation
➢
D.Y.Stewart et al., acc. for publ. in JINST
➢
Informal collaboration with
LArsoft: ArgoNeuT, MicroBooNE, data analysis code
➢A. Rubbia's group on data analysis (travel grant)
➢
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What do we need to do?
 Classify
energy deposit
information into shower-like and
track-like objects
 Identify
tracks (µ,π,p) and
showers (e, γ) from topology,
kinematics and dE/dx in LAr
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J. Spitz
Clustering
 Aim to limit
contamination of cluster
with hits laid down by
other particles
 Develop a hierarchy of
clusters/super-clusters
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Density-Based Clustering
 Clusters: a density of points considerably higher than
outside the cluster
 DBSCAN* algorithm: the `density-neighbourhood’
(ε) around each point in the cluster must contain at
least Nmin other points
Kinga Partyka (Yale/ArgoNEUT)
 Implemented in ArgoNeuT data
 Issues with `over-clustering’
being addressed
Colours → Cluster found
by DBSCAN
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* Sander et al., Data Mining and knowledge Discovery 2, pp169-194 (1998)
Cellular Automata clustering
Next 'Warwick Tool' to be quantified and published
Toy-MC data
Raw hits
GENIE
Simulated
CCQE
events
Reconstructed
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OPTICS
 Ordering Points To Identify the
Clustering Structure*
 Extended DBSCAN clustering
 Reveals clusters on all scales
 Getting the scale correct helps in
associating disjoint clusters in EMag showers
 Extend to cluster in more than
spatial coordinates, e.g. dE/dx
Reachability Distance plot
3 clusters found
dE/dx used since
track density identical
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* M. Ankerst et al., ACM SIGMOD Int. Conf. on Management of Data pp49-60 (1999)
N data points
Track Finding: Hough Transform
Joshua Spitz ArgoNeuT/Yale
 Reasonable job of
reconstructing multiple tracks
in ArgoNeuT events
 Returns only gradient and
intercept of line – definition of
start/end-points of tracks
continuing:
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Track Finding: KDTREE
 KDTREE provides convenient data
structure from which to launch a
nearest-neighbour hit search
 Fit straight-line segments through
groups of nearest hits in 3D
 Currently testing on toy Monte
Carlo – observe change in direction
cosine of line segments to tag
kink/vertex with high efficiency
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Andrew Bennieston, Warwick
3D Track fitting
Implemented a modified ICARUS Kalman filter: ICARUS, Eur. Phys. J. C48 (2006) 667
● Momentum-measurement by multiple scattering!
●
Momentum reconstruction
ICARUS simulated tracks
Warwick simulated track,
Multiple scattering only
Track slope reconstruction
μ @ p=1.5 GeV/c
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Key Point Detection
Vertex IP 
corner in charge
density
Delta-electron 
corner in charge
density
 Prior knowledge of vertex points, kinks, track end-points etc is
useful in aiding reconstruction algorithms e.g. blank-off hits around a
vertex point from a cluster search
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Corner Finding
 GENIE generated
νµ CCQE events in 3T LAr TPC:
Ben Morgan, JINST 5 (2010) P07006
Vertex picked out
Delta Electron ID!
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Proton Stop
ArgoNeuT data update
Recently completed >5 months physics run in the NuMI beamline
ArgoNeuT, arXiv:1009.2515, implementing B. Morgan's corner finding
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T. Dealtry,
Warwick URSSProject 2009
New toolbox target
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Conclusion
• Great progress in expanding data analysis toolbox
• Work in progress@Warwick: Quantify performance
using GENIE simulated data for liquid argon
• Next steps:
– Model Analysis
• Obtain Globes input parameters from Monte-Carlo data
• Analyse the effect of (absence of) a magnetic field
– Collaborate more closely with running
experiments, testing analysis on real data
– Provide input to IDS on liquid argon detector
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