[PPT] - e identification in the NO A Near Detector events Ciro Riccio PowerPoint Presentation

SLIDE 1

νe identification in the NOνA Near Detector events

Ciro Riccio

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September 25th, 2014 Supervisors: Xuebing Bu and Pat Lukens

Thursday, September 25, 14

SLIDE 2

The NOνA experiment

NOvA NuMI Off-Axis νe Appearance is optimized

for the detection of νμ→νe and νμ→νe oscillations

NOvA includes:
Main Injector now @ 360 kW used to produce

the beam

A 14 kt “totally active” tracking liquid scintillator

calorimeter sited 14.6 mrad off the NuMI beam axis at a distance of 810 km (Far Detector, FD)

A 300 ton Near Detector (ND) identical to the

far detector sited 14.6 mrad off the NuMI beam axis at a distance of 1 km and 105 m

underground. It is used to study the background

compositions and contributions for oscillation analysis 6 cm 4 cm

20 40 60 80 2 4 6 8 10 Eν (GeV) ν CC events / kt / 1E21 POT / 0.2 GeV Medium Energy Tune

n-axis

7 mrad off-axis 14 mrad off-axis 21 mrad off-axis

μ

2

16 m 16 m 60 m

4 m 4 m 15 m

810 km

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SLIDE 3

APDs Quality Assurance Test

Visual test Pressure and flow test Electrical test

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SLIDE 4

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νe identification in the ND

In order to identify νe events I used Boosted Decision Trees (BDT):

BDT is a classifier implemented in TMVA;
The BDT was trained and tested using well known signal

and background samples;

The BDT was applied to 1779 MC files for a total of 8.9

x 1019 POT to identify νe events in ND

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SLIDE 5

Σ Ecells is the summed energy of all cells associated to the slice with the maximum number of associated cells;
Ncells is the number of cells associated to the slice with the maximum number of cells;
Ltrack is the lenght of the track;
The ratio of number of cells associated to the longest track over Ncells;
Number of MIP cells (Nmip defined requiring 100 < PECorr < 245, PECorr is corrected photo-electrons);
The ratio Ncells over Nmip;
Fraction of energy in first 20 planes;
Maximal fraction of energy in 2 planes. Reflects the condensity of the longitudinal shower;
Maximal fraction of energy in 6 planes;
Fraction of energy in 2σ (σ = 2 cm) road. The νe should have relatively narrower transverse shower than the π0 ;
Fraction of energy out 3σ road;
Number of 2D prongs;
Number of 3D prongs;
Energy balance between 2 most energetic 2D prongs;
Energy balance between 2 most energetic 3D prongs.

List of variables used to train and test BDT and for PID

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SLIDE 6

6

Input Variables

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SLIDE 7

7

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SLIDE 8

8

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SLIDE 9

9

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SLIDE 10

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Background rejection versus Signal efficiency

Overtraining check plot

TMVA Output

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SLIDE 11

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Correlation Matrices for signal and background

Some variables are correlated

100
80
60
40
20

20 40 60 80 100

N c e l l s E r e c

L

t r a c k r a t i

f

N c e l l s m i p f r a c t i

n

#

f

m i p c e l l s E f r a c

f

2 E f r a c

f

2 s l i d e s E f r a c

f

6 s l i d e s E f r a c

f

2 s i g m a E i s

f

3 s i g m a #

f

3 D p r

n

g s e n e r g y b a l a n c e f

r

3 D p r

n

g s #

f

2 D p r

n

g s e n e r g y b a l a n c e f

r

2 D Ncells Ereco Ltrack ratio of Ncells mip fraction # of mip cells Efrac of 20 Efrac of 2 slides Efrac of 6 slides Efrac of 2 sigma Eiso of 3 sigma # of 3D prongs energy balance for 3D prongs # of 2D prongs energy balance for 2D prongs

Correlation Matrix (background)

100 94 28 -66 -43 91 -32 -47 -40 -60 38 55 -17 26 11 94100 20 -63 -52 78 -31 -40 -32 -51 27 50 -9 25 14 28 20100 33 37 44 -36 -41-49 8 -2 -9 18 -10 23

66 -63 33100 69 -52 5 10 -2 76 -41-65 44 -41 16
43 -52 37 69 100 -9 -6 -5 -18 45 -16 -41 20 -34 9

91 78 44 -52 -9 100-36 -49 -46-55 40 49 -20 19 10

32 -31-36 5 -6 -36100 41 52 -7 10 -5 -14 -13 -16
47 -40 -41 10 -5 -49 41100 86 7 -8 -10 -16
28
40 -32 -49 -2 -18 -46 52 86100 -6 1 -1 -23
28
60 -51 8 76 45 -55 -7 7 -6 100-69 -60 58 -29 17

38 27 -2 -41 -16 40 10 -8 1 -69100 38 -38 7 -10 55 50 -9 -65 -41 49 -5 -10 -1 -60 38 100-46 16 -3

17 -9 18 44 20 -20-14 -16 -23 58 -38 -46100 -11 25

26 25 -10 -41-34 19 -13

29 7 16 -11100-32

11 14 23 16 9 10 -16 -28 -28 17 -10 -3 25 -32100

Linear correlation coefficients in %

100
80
60
40
20

20 40 60 80 100

Ncells Ereco Ltrack ratio of Ncells mip fraction # of mip cells Efrac of 20 Efrac of 2 slides Efrac of 6 slides Efrac of 2 sigma Eiso of 3 sigma # of 3D prongs energy balance for 3D prongs # of 2D prongs energy balance for 2D pro Ncells Ereco Ltrack ratio of Ncells mip fraction # of mip cells Efrac of 20 Efrac of 2 slides Efrac of 6 slides Efrac of 2 sigma Eiso of 3 sigma # of 3D prongs energy balance for 3D prongs # of 2D prongs energy balance for 2D prongs

Correlation Matrix (signal)

100 82 53 -49 -16 85 -33 -50 -46 -33 22 29 -5 10 16 82 100 55 -25 -47 50 -41 -55 -50 4 -6 3 26 6 33 53 55 100 26 -19 39 -48 -61 -65 22 -18 -16 36 36

49 -25 26100 -11 -54 -8 -11 -15 62 -43 -50 50 -15 24
16 -47 -19 -11100 32 14 31 21 -40 31 22 -45
33

85 50 39 -54 32 100-24 -32 -33 -53 39 40 -29 9 -1

33 -41 -48 -8 14 -24100 45 56 -15 17 8 -18 -8 -20
50 -55 -61 -11 31 -32 45 100 89 -23 18 16 -38
41
46 -50 -65 -15 21 -33 56 89 100-22 19 13 -33 -3 -34
33 4 22 62 -40 -53 -15 -23 -22100-74 -56 71 -13 36

22 -6 -18 -43 31 39 17 18 19 -74100 36 -55

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29 3 -16 -50 22 40 8 16 13 -56 36 100-52 5 -18

5 26 36 50 -45 -29 -18 -38 -33 71 -55 -52100 -5 47

10 6

15

9 -8

3 -13

5 -5 100-26 16 33 36 24 -33 -1 -20 -41 -34 36 -28 -18 47 -26100

Linear correlation coefficients in %

Some variable are correlated

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SLIDE 12

BDT Output

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SLIDE 13

S √ B

S √S+B

= 26 % = 39 %

S √S+B

S √ B

Significance Vs BDT Output

Requiring BDT Output larger than 0 and 11 variables Requiring BDT Output larger than 0 and 11 variables

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SLIDE 14

14

11 Variables

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SLIDE 15

15

Reducing the number of correlated variables we can reduce sources of systematic errors

Correlation Matrix

11 Variables

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SLIDE 16

Conclusions

BDT was been trained, tested and then it are applied

to MC files using 15 variables;

The number of variables are reduced;
and are evaluated varying the BDT

Output between -1 and 1;

Requiring BDT output > 0 and using 11 variable

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S √S+B

S √ B

= 26 % = 39 %

S √S+B

S √ B

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SLIDE 17

Thank you for your attention!

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