Automated reconstruction of LAr events at Warwick. J.J. Back, G.J. Barker, S.B. Boyd, A.J. Bennieston, B. Morgan, YR

Transcription

1 Automated reconstruction of LAr events at Warwick J.J. Back, G.J. Barker, S.B. Boyd, A.J. Bennieston, B. Morgan, YR

2 Challenges Single electron, 2 GeV in LAr: Easy 'by-eye' in isolation Challenging for computer

3 Challenges Spot the electron! 2 GeV e- as before 81 cosmic muons in 14x14x20 m 3 volume in 1.4 ms readout interval. Analysis 'by-eye' becomes interesting... A big challenge for any automated analysis.

4 Automated reconstruction at Warwick Detector/Simulation incl. charge quench in Genie/Geant4 Being validated Exists, tested Raw data: (x,y,z,charge) Simulation: (x,y,z,charge,truth_id) Pre-processing Shower/Track segmentation decision DBScan event noise filter, dedx filter, charge smoothing, masking structures, feature finding, utilities Shower Segmentation Track segmentation LPC shower finder, total energy, direction, extent Physics Structure container Clusters of hits, each a reconstructed particle - Cellular automaton - LPC algorithm Vertex finder Kinematics calculator Particle Identification LPC vertex finder Kalman filter fit Six discrimination variables and multi-variate analysis TMVA Post-recon analysis Truth value validation, track length calculation, observables,...

5 Current status Shower / Track decision code being validated Track analysis automated, validated for CA, LPC not yet Shower analysis exists, no validation yet Particle ID, finished Papers: Interest point detection for reconstruction in high granularity tracking detectors, B. Morgan, JINST 5 (2010) P07006 Electron-Hadron shower discrimination in a LArTPC, submitted (arxiv: ) CA paper in preparation Local Principal Curves (LPC) paper in preparation

6 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

7 Automated reconstruction at Warwick Detector/Simulation incl. charge quench in Genie/Geant4 Being validated Exists, tested Raw data: (x,y,z,charge) Simulation: (x,y,z,charge,truth_id) Pre-processing Shower/Track segmentation decision DBScan event noise filter, dedx filter, charge smoothing, masking structures, feature finding, utilities Shower Segmentation Track segmentation LPC shower finder, total energy, direction, extent Physics Structure container Clusters of hits, each a reconstructed particle - Cellular automaton - LPC algorithm Vertex finder Kinematics calculator Particle Identification LPC vertex finder Kalman filter fit Six discrimination variables and multi-variate analysis TMVA Post-recon analysis Truth value validation, track length calculation, observables,...

8 Cellular Automaton (CA) for tracks µ µ µ Validation on low energy CCQE muon + proton events and CCQE muon + proton + pion events.

9 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 % 95-98% Pur % 95-96%

10 Automated reconstruction at Warwick Detector/Simulation incl. charge quench in Genie/Geant4 Being validated Exists, tested Raw data: (x,y,z,charge) Simulation: (x,y,z,charge,truth_id) Pre-processing Shower/Track segmentation decision DBScan event noise filter, dedx filter, charge smoothing, masking structures, feature finding, utilities Shower Segmentation Track segmentation LPC shower finder, total energy, direction, extent Physics Structure container Clusters of hits, each a reconstructed particle - Cellular automaton - LPC algorithm Vertex finder Kinematics calculator Particle Identification LPC vertex finder Kalman filter fit Six discrimination variables and multi-variate analysis TMVA Post-recon analysis Truth value validation, track length calculation, observables,...

11 Most versatile: LPC LPC on low energy electron showers.

12 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

13 LPC on vertex finding 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.

14 Automated reconstruction at Warwick Detector/Simulation incl. charge quench in Genie/Geant4 Being validated Exists, tested Raw data: (x,y,z,charge) Simulation: (x,y,z,charge,truth_id) Pre-processing Shower/Track segmentation decision DBScan event noise filter, dedx filter, charge smoothing, masking structures, feature finding, utilities Shower Segmentation Track segmentation LPC shower finder, total energy, direction, extent Physics Structure container Clusters of hits, each a reconstructed particle - Cellular automaton - LPC algorithm Vertex finder Kinematics calculator Particle Identification LPC vertex finder Kalman filter fit Six discrimination variables and multi-variate analysis TMVA Post-recon analysis Truth value validation, track length calculation, observables,...

15 Particle ID Assumption: Isolated hit structures obtained from a previous step, i.e. assume to analyse single clusters! 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)

16 Particle ID Example low energy π 0 shower and PCA transform Core 9.61cm x 9.61cm for 'lat' variable Main principal axis Lateral projection plane Axes units in [mm]

17 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 Signal/Background distribution uniform between 10 MeV and 4.5GeV.

18 Conclusion Fully automated reconstruction of LAr events is possible with this software, how well is not known yet. Step-wise validation is ongoing. Most promising algorithm so far: local principal curves (LPC) 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.