Update on Multivariate Discriminant Analysis applied to Classification of ne CC Events in MINOS

1
Update on Multivariate Discriminant
Analysisapplied to Classification of ne CC
Events in MINOS

• Alex Sousa
• Tufts University
• MINOS Week-in-the-Woods Meeting_at_ Ely
• ne Analysis Working Group
• 06/14/2005

2
MDA Update

• First results with
• Analysis code fully migrated from old NueAnalysis
  to Minossofts NueAna.
• Angular Clustering and Angular Cluster Fitting
  working
• Running on Far and Near Mock Data files
• New nue and numu files
• Mock Data Challenge completed

3
Variable Selection

• Variable selection is performed using SAS
  Stepwise discriminant procedure
• Preliminary selection from 350 available
  variables
• 140 sorted by discriminating power
• Running classification method for the 19
  variables with highest discriminating power.

4
Samples and Cuts

• Far samples
• Test sample composed of 19 nue, 19 numu and 19
  nutau MDC Far MC files processed with R1.12 (each
  file corresponds to 6.5x1020 POT)
• Training sample with identical size and
  proportions, no overlapping events.
• Test on MDC Far Mock Data file also processed
  with R1.12 (7.4x1020 POT)
• Near samples for testing
• 229 MDC Near MC files (1.33x1016 POT each)
• 246 MDC Near Mock Data files (1.33x1016 POT)
• Using cuts from Josh and Mayly analysis
• Fiducial and containment cuts
• Vertex contained in fiducial volume
• Full event containment in Far Det
• Full Z containment in Near Det
• Prong cut individual track or shower pulseheight
  gt 5000 sigcor (300 MeV)
• High energy Cut Total reconstructed event energy
  lt 150 MEU (6 GeV)
• Track Length Cut Events with track length lt 18
  planes.

5
Results on Far Detector MC

• Note Using MDC CC params (sin2(2q23)0.925,
  Dm2322.175x10-3 eV2,Ue320.01)
• Training on QE Nue CC Events only. Used in all
  the results shown.

6
Osc. probability comparison

• Expect considerable depletion (50) of signal
  with new oscillation parameters in comparison
  with previous result.

7
Reweighted Results (testing on Far MC )
8
Running on Near MC and Mock Data
9
Some variables (Tingjun)
10
Some variables (Mayly)
11
Some variables (Trish)
12
Some variables (AS)
13
Far Det Selection Distro (Type)
QE
RES
DIS
CPP
14
Far Det Selection Distro (Energy)
15
Far Det Selection (EMShwFrac)
16
Far Det Selection (hadronic Y)
17
Summary

• Ran the Multivariate Discriminant Analysis on the
  complete MDC sample (see Trishs talks for
  sensitivities and fits)
• Migration to new framework and incorporation of
  new MC files did not affect overall quality of
  results.
• Performance plots show some room for optimization
  (need to look closely at events to confirm this).
  
• Need to produce Near/Far comparison plots and run
  on existing near data sample.