FD Data vs MC Comparison

Because the beam events in FD is blinded, during the optimization of all analysis tools, the FD beam event prediction is based on the simulation. The data vs MC comparison is

also checked in the far detector using cosmic ray events from FD cosmic trigger data. Fig.5.12

Figure 5.8: The ND data(black) versus total mc(red) distributions of vertex in x coordi- nate for all events.

Figure 5.9: The ND data(black) versus total mc(red) distributions of vertex in z coordinate for all events.

Figure 5.10: The ND data(black) versus total mc(red) distributions of LID for pre-selected events.

Figure 5.11: The ND data(black) versus total mc(red) distributions of LEM for pre-selected events.

for events passing the data quality cuts (See Sec.6.3.1), which are designed to remove some

reconstruction failures. The agreement is good for the small angle range, |cosθ| > 0.5, where

the signal events are typically found. Fig.5.13 through Fig.5.17 show the distributions for

basic reconstructed variables, number of hits, calorimetric energy of slice and vertex position in x, y and z coordinates The data and MC agree well for these variables for the events with small angle with respect to the beam direction as well as with vertices contained in

the detector. Fig.5.18, Fig.5.19 and Fig.5.20 are showing the comparison for transverse and

longitudinal energy deposition rate as well as the number of planes in shower, the variables

Cosine of Angle to Beam

-1 -0.5 0 0.5 1

Events/1 year exposure

0 20000 40000

Far Detector Data

Cosmic Simulation

Figure 5.12: The FD data(black) versus

mc(blue) distributions of the angle of the lead- ing shower with respect to beam direction.

Vertex Z (cm)

0 500 1000 1500

Events/1 year exposure

10 2 10 10

Far Detector Data

Cosmic Simulation

Figure 5.13: The FD data(black) versus

mc(blue) distributions of vertex in z coordi- nate.

Vertex X (cm)

-500 0 500

Events/1 year exposure 103 4 10 5 10 A Preliminary ν NO

Far Detector Data

Cosmic Simulation

Figure 5.14: The FD data(black) versus

mc(blue) distributions of vertex in x coordi- nate.

Vertex Y (cm)

-500 0 500

Events/1 year exposure 103 4 10 5 10 A Preliminary ν NO

Far Detector Data

Cosmic Simulation

Figure 5.15: The FD data(black) versus

mc(blue) distributions of vertex in y coordi- nate.

Number of Hits per Slice

0 100 200 300 400 500

Events/1 year exposure

0 5000 10000 15000 A Preliminary ν NO

Far Detector Data

Cosmic Simulation

Figure 5.16: The FD data(black) versus

mc(blue) distributions of the number of hits in slice.

Calorimetric Energy (GeV)

0 2 4 6 8 10

Events/1 year exposure

0 5000 10000 15000 A Preliminary ν NO

Far Detector Data

Cosmic Simulation

Figure 5.17: The FD data(black) versus

mc(blue) distributions of total calorimetric energy of slice.

Longitudinal dE/dx (GeV/cm)

0 0.002 0.004 0.006 0.008 0.01

Events/1 year exposure

0 500 1000 1500

Far Detector Data Cosmic Simulation

A Preliminary ν

NO

Figure 5.18: The FD data(black) versus

mc(blue) distributions of longitudinal dE/dx.

Transverse dE/dx (GeV/cm)

0 0.002 0.004 0.006 0.008 0.01

Events/1 year exposure

0 2000 4000 6000 8000

Far Detector Data Cosmic Simulation

A Preliminary ν

NO

Figure 5.19: The FD data(black) versus

mc(blue) distributions of transverse dE/dx.

Since the signal of the analysis is νe CC interaction, for which the signature is an EM

shower induced by the outgoing electron, a more sophisticated comparison is performed to check specifically EM shower model using cosmic muon-induced EM showers. After high-energy cosmic muons enter the detector, they produce gammas through Bremsstrahlung radiation and also decay into electrons. Both the gammas and electrons undergo EM showers during the propagation. The study is divided into four steps: muon track selection, shower finding, muon removal and shower reconstruction and PID [103].

Muon track selection: The cosmic muon selected should fulfill three conditions: have both start and stop points outside the detector; present a not very large angle with respect to the beam direction so that the remaining prongs after the muon removal process will be close to the beam direction; penetrate at least 30 planes.

mc(blue) distributions of number of planes in

slice. mc(blue) distributions of LID.

select muon with showers attached. The search is done by checking the energy deposition in each plane. A consistant excess in the energy deposition rate beyond MIP rate suggests the existance of a EM shower, which is tagged for next step.

Muon removal: Muon track is removed from the events leaving only shower in the event at the raw hit level [104]. In the region where muon track and shower overlap, instead of removing the entire hit, the PE value of the hit is reweighted so that only the energy

deposition from muon is removed. Fig.5.22 and Fig.5.23 shows a cosmic muon event

before and after the muon removal algorithm. by which the EM shower is extracted.

Figure 5.22: Event display of a selected cosmic muon event in the FD cosmic trigger data before muon removal.

Figure 5.23: Event display of a selected cosmic muon event in the FD cosmic trigger data after muon removal.

Shower reconstruction and PID: The event after muon removal is processed by standard reconstruction and PID and data/MC comparison is performed for the resulting recon- struction and PID variables. Both the muon removed cosmic data and MC samples are reweighted based on shower energy and shower angle so that the muon removal sam-

ple has the same the leading shower energy and angle distributions as the νe CCsignal

sample (See Fig.5.24 for shower energy and Fig.5.25 for cosine of the angle between the

leading shower and the beam direction). Fig.5.26 through Fig.5.29 show the data/MC

comparison for some key reconstructed shower variables, including shower width, shower length, the number of planes in shower and the number of hits in shower. All these shower variables show generally good agreement that the difference between data and MC is con-

sistently lower than 5%. Fig.5.30is the distribution of LID variable, according to which,

for the examined EM showers, LID peaks near 1 and MC agrees with data well. Fig.5.31,

Fig.5.32and Fig.5.33present the reconstruction efficiency as a function of reconstructed

vertex position in X, Y and Z for showers passing LID > 0.7. The plots demonstrate a fairly stable reconstruction efficiency across the detector and a good agreement between data and MC in the efficiency.

Figure 5.24: The data (black) vs MC (red) comparison in the reconstructed shower en- ergy.

Figure 5.25: The data (black) vs MC (red) comparison in the cosine of the angle of the EM shower with respect to the beam direc- tion.

Figure 5.26: The data (black) vs MC (red) comparison in the reconstructed shower ra- dius.

Figure 5.27: The data (black) vs MC

(red) comparison in the reconstructed shower length.

Figure 5.28: The data (black) vs MC (red) comparison in the number of planes in shower.

Figure 5.29: The data (black) vs MC (red) comparison in the number of hits in shower.

Figure 5.30: The data (black) vs MC (red) comparison in the number of hits in shower.

Figure 5.31: The data (black) vs MC (red) comparison in the reconstruction efficiency as a function of vertex position in X for events passing LID > 0.7.

Figure 5.32: The data (black) vs MC (red) comparison in the reconstruction efficiency as a function of vertex position in Y for events passing LID > 0.7.

Figure 5.33: The data (black) vs MC (red) comparison in the reconstruction efficiency as a function of vertex position in Z for events passing LID > 0.7.