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Far Detector Fiducial Volume Study Andy Blake Cambridge University Thursday December 7 th 2006
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Far Detector Fiducial Volume Study Andy Blake Cambridge University Thursday December 7 th 2006.

Dec 22, 2015

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Page 1: Far Detector Fiducial Volume Study Andy Blake Cambridge University Thursday December 7 th 2006.

Far Detector Fiducial Volume Study

Andy BlakeCambridge University

Thursday December 7th 2006

Page 2: Far Detector Fiducial Volume Study Andy Blake Cambridge University Thursday December 7 th 2006.

Overview

Andy Blake, Cambridge University Fiducial Volume Study, slide 2

Fiducial volume optimization encompasses the following:

Page 3: Far Detector Fiducial Volume Study Andy Blake Cambridge University Thursday December 7 th 2006.

All Showers

Showers <2 GeV

• Previous study by Andy Culling (see, for example, doc-db #1136).

– Studied bias in reconstructed shower energy close to detector edges.

– Studied sensitivity to oscillation parameters as function of fiducial cuts.

Previous Study [A. Culling]

Andy Blake, Cambridge University Fiducial Volume Study, slide 3

Page 4: Far Detector Fiducial Volume Study Andy Blake Cambridge University Thursday December 7 th 2006.

Fiducial Volume Study

Andy Blake, Cambridge University Fiducial Volume Study, slide 4

• Study following four fiducial containment parameters:

– radial edge of detector. – front/back plane of detector – coil hole.

COIL HOLE

radial cut

coil cut

back Z cut forward Z cut

COIL HOLE

SM1 SM2

forward Z cut back Z cut

N.B: For purposes of this study, same fiducial cuts applied to both super-modules.

Page 5: Far Detector Fiducial Volume Study Andy Blake Cambridge University Thursday December 7 th 2006.

Fiducial Volume Study

Andy Blake, Cambridge University Fiducial Volume Study, slide 5

• Use “Cedar” beam MC ntuples for this study.

– contained interactions (approx. 800 x 1020 PoTs).

– rock interactions (approx. 100 x 1020 PoTs).

• Optimize fiducial cuts by studying the following:

Track containment – compare tracks from contained and rock CC interactions.

– study bias in reconstructed muon energy close to detector edges.

Shower containment – study bias in reconstructed shower energy close to detector edges. – measure visible energy escaping through detector edges.

Oscillation sensitivity – vary each of the fiducial parameters in turn. – calculate sensitivity in m2 and sin22.

Page 6: Far Detector Fiducial Volume Study Andy Blake Cambridge University Thursday December 7 th 2006.

Track Containment: Front Edge

Andy Blake, Cambridge University Fiducial Volume Study, slide 6

rock CC events

contained CC events.

• Rock muons can sneak into the detector:

– up to ~10 cm through the detector edge. – up to ~4 planes through the front plane.

Page 7: Far Detector Fiducial Volume Study Andy Blake Cambridge University Thursday December 7 th 2006.

Track Containment: Back Edge

Andy Blake, Cambridge University Fiducial Volume Study, slide 7

Bias in reconstructed muon momentum for tracks exiting through end of detector

Page 8: Far Detector Fiducial Volume Study Andy Blake Cambridge University Thursday December 7 th 2006.

Shower Extent : Transverse

Andy Blake, Cambridge University Fiducial Volume Study, slide 8

Transverse extent of showers:

Page 9: Far Detector Fiducial Volume Study Andy Blake Cambridge University Thursday December 7 th 2006.

Shower Extent: Longitudinal

Andy Blake, Cambridge University Fiducial Volume Study, slide 9

BACK FORWARD

Longitudinal extent of showers:

Page 10: Far Detector Fiducial Volume Study Andy Blake Cambridge University Thursday December 7 th 2006.

Shower Energy Bias

Andy Blake, Cambridge University Fiducial Volume Study, slide 10

• Calculate mean energy bias as function of radial vertex position.

– Only use events where vertex is >20 planes from front and back planes.

Distance to detector edge Distance to centre of coil hole

Page 11: Far Detector Fiducial Volume Study Andy Blake Cambridge University Thursday December 7 th 2006.

• Calculate mean energy bias as function of vertex Z position.

– Only use events where vertex is >50cm from edge and >40 cm from centre.

Distance to back face of detector Distance to forward face of detector

Shower Energy Bias

Andy Blake, Cambridge University Fiducial Volume Study, slide 11

Page 12: Far Detector Fiducial Volume Study Andy Blake Cambridge University Thursday December 7 th 2006.

Shower Energy Loss

Andy Blake, Cambridge University Fiducial Volume Study, slide 12

• Create a fake detector edge to study shower containment.

– Calculate the proportion of visible energy contained inside the fake detector volume as a function of the position of the visible shower edge.

Page 13: Far Detector Fiducial Volume Study Andy Blake Cambridge University Thursday December 7 th 2006.

Shower Energy Loss

Andy Blake, Cambridge University Fiducial Volume Study, slide 13

Distance to detector edge

Page 14: Far Detector Fiducial Volume Study Andy Blake Cambridge University Thursday December 7 th 2006.

Shower Energy Loss

Andy Blake, Cambridge University Fiducial Volume Study, slide 14

Distance to forward face of detectorDistance to back face of detector

Page 15: Far Detector Fiducial Volume Study Andy Blake Cambridge University Thursday December 7 th 2006.

Oscillation Sensitivity

Andy Blake, Cambridge University Fiducial Volume Study, slide 15

• Calculate sensitivity as function of fiducial cuts.

– Vary each cut in turn, holding the others constant.

• Initial Event Selection.

– Reconstructed muon track (must pass track fitter).

– Use standard PID with cut placed at PID>0.0.

• Mechanics of Oscillation Fit.

– Purely statistical (ignore all systematic errors).

– Fit to overall reconstructed neutrino energy spectrum. E (GeV) = [ 0, 30 ] (60 bins) + 1 bin overflow.

– Perform oscillation fit on 120 x 120 grid. m2 (10-3 eV2) = [ 1.5, 4.5 ] , Sin22 = [ 0.7, 1.0 ].

– True Oscillation Parameters: m2 = 3 x 10-3 eV2, Sin22 = 1.0.

– True Normalization: 2.5 x 1020 PoTs.

– Simulate 20 experiments at each grid point.

Page 16: Far Detector Fiducial Volume Study Andy Blake Cambridge University Thursday December 7 th 2006.

Oscillation Sensitivity

Andy Blake, Cambridge University Fiducial Volume Study, slide 16

• Input Data. – Use BOTH rock interactions AND contained events.

• Sensitivity Calculation. – Determine best fit m2 along line of sin22=1.0.

Calculate 99% confidence interval in m2.

– Determine best fit sin22 along line of best fit m2.

Calculate 99% confidence interval in sin22.

• Fiducial cut parameters.

Fiducial Cut Default Range

Radial Edge 0.3 m 0.0 - 1.0 m

Coil Hole 0.4 m 0.0 - 1.0 m

Back Face 0.5 m 0.1 - 1.5 m

Forward Face 1.5 m 0.5 - 5.0 m

Page 17: Far Detector Fiducial Volume Study Andy Blake Cambridge University Thursday December 7 th 2006.

Oscillation Sensitivity: Radial Cut

Andy Blake, Cambridge University Fiducial Volume Study, slide 17

m2 sensitivity (99% confidence) sin22 sensitivity (99% confidence)

Page 18: Far Detector Fiducial Volume Study Andy Blake Cambridge University Thursday December 7 th 2006.

Oscillation Sensitivity: Coil Cut

Andy Blake, Cambridge University Fiducial Volume Study, slide 18

m2 sensitivity (99% confidence) sin22 sensitivity (99% confidence)

Page 19: Far Detector Fiducial Volume Study Andy Blake Cambridge University Thursday December 7 th 2006.

Oscillation Sensitivity: Back Edge

Andy Blake, Cambridge University Fiducial Volume Study, slide 19

m2 sensitivity (99% confidence) sin22 sensitivity (99% confidence)

Page 20: Far Detector Fiducial Volume Study Andy Blake Cambridge University Thursday December 7 th 2006.

Oscillation Sensitivity: Forward Edge

Andy Blake, Cambridge University Fiducial Volume Study, slide 20

m2 sensitivity (99% confidence) sin22 sensitivity (99% confidence)

Page 21: Far Detector Fiducial Volume Study Andy Blake Cambridge University Thursday December 7 th 2006.

What are the optimal fiducial cuts ?

Andy Blake, Cambridge University Fiducial Volume Study, slide 21

Radial Edge Coil Hole Back Plane Forward Plane

Track

containment>10 cm > 25 cm > 100 cm

Shower

energy bias> 20 cm > 40 cm > 60 cm

Shower

energy loss> 20 cm > 10 cm > 80 cm

Oscillation sensitivity < 30 cm < 180 cm

• require minimal contamination from rock muons.• mean track momentum bias must be less than 500 MeV.• mean shower energy bias must be less than 100 MeV. • visible energy loss must be less than 10%.• require optimal sensitivity for oscillation parameters.

Criteria

Optimal? > 20 cm > 40 cm > 25 cm > 100 cm

i.e. must not be more than double the bias observed for highly contained events.

Page 22: Far Detector Fiducial Volume Study Andy Blake Cambridge University Thursday December 7 th 2006.

Energy-Dependent Fiducial Cuts

Andy Blake, Cambridge University Fiducial Volume Study, slide 22

reco shower energy

could relax fiducial cuts for lowest energy showers

Page 23: Far Detector Fiducial Volume Study Andy Blake Cambridge University Thursday December 7 th 2006.

Energy-Dependent Fiducial Cuts

Andy Blake, Cambridge University Fiducial Volume Study, slide 23

• Various schemes for energy-dependent fiducial cuts.

– Shower Edge Cuts Cut on position of shower edge relative to detector edge. Need to define position of shower edge, plus size of cut.

– Fiducial Activity Cuts Cut on amount of shower activity close to detector edge. Need to optimize size of edge region, plus allowed charge.

– Apply in addition to, or instead of, fixed fiducial cuts? Apply energy-dependent cuts to all events? Just use these cuts to recover events around detector edge?

• Example: shower edge cut.

– Find closest distance of shower to detector edges.

– apply cut at r > 10 cm and z > 15 cm.

Page 24: Far Detector Fiducial Volume Study Andy Blake Cambridge University Thursday December 7 th 2006.

Shower Edge Cut

Andy Blake, Cambridge University Fiducial Volume Study, slide 24

>10 cm (2 strips) >15 cm (2 planes)

Distance to forward face of detectorDistance to radial edge of detector

Page 25: Far Detector Fiducial Volume Study Andy Blake Cambridge University Thursday December 7 th 2006.

Shower Edge Cut

Andy Blake, Cambridge University Fiducial Volume Study, slide 25

Distance to forward face of detectorDistance to radial edge of detector

After edge cut

All showersAfter edge cut

All showers

Page 26: Far Detector Fiducial Volume Study Andy Blake Cambridge University Thursday December 7 th 2006.

Oscillation Sensitivity Plots

Andy Blake, Cambridge University Fiducial Volume Study, slide 26

Radial

Edge

Coil

Hole

Back

Face

Forward

Face

(1) Fixed Fiducial Cuts

det.edge - evt.vtx > 20 cm > 40 cm > 25 cm det.edge - evt.vtx > 100 cm

(2) Shower Edge Cuts

det.edge - evt.vtx > 10 cm

OR

det.edge - shw.edge > 10 cm

> 40 cm > 25 cm det.edge - shw.edge > 15 cm

(2a) = (1) || (2) (1) || (2)

(3) Fiducial Activity Cuts

det.edge - evt.vtx > 10 cm

OR

<10% shw.ph 10cm from edge

> 40 cm > 25 cm <10% shw.ph 15cm from edge

(3a) = (1) || (3) (1) || (3)

Page 27: Far Detector Fiducial Volume Study Andy Blake Cambridge University Thursday December 7 th 2006.

Oscillation Sensitivity Plots

Andy Blake, Cambridge University Fiducial Volume Study, slide 27

99% confidence limits

(1) Fixed fiducial cuts

(2) Shower edge cuts

(2a) = (1) || (2)

(3) Fiducial activity cuts

(3a) = (1) || (3)

• Confidence limits are Similar in all cases.

• Fixed fiducial cuts give best sensitivity contour. – but energy-dependent cuts aren’t optimized.

• Rescuing events around edge of detector makes sensitivity worse. – needs careful optimization to make sensitivity better.

• Energy-dependent cuts push contour down.

true oscillations

Page 28: Far Detector Fiducial Volume Study Andy Blake Cambridge University Thursday December 7 th 2006.

Summary

Andy Blake, Cambridge University Fiducial Volume Study, slide 28

• Homing in on optimal fiducial cuts. – studies of biases in reconstructed muon and shower energy.

– optimization of sensitivity to oscillation parameters.

• Current results in good agreement with previous study.

• Future work: – re-do oscillation fits with finer binning and higher statistics.

– study optimization of fiducial cuts at supermodule boundary.

– study optimization of energy-dependent fiducial cuts.