Objective 5: To assess the risk factors associated with active HEV infection in pigs reared in different production systems. This study evaluated the risk factors
VIII. Publicación 3
7. Supplementary Materials
Driven by the prescription discussed in Chap. 2 on the necessity to be less dependent on the cross section model, the selection described before has been improved dividing the CC-Inclusive sample into three sub-samples, defined by the number of final state pions, taking into account also FGD-only tracks. A similar selection has been already used in past oscillation analysis performed with data taken in ν-mode [175].
The sample are defined in the following way:
CC-0π-like: events with no additional TPC tracks consistent with being a pion or elec-tron and with no additional FGD tracks consistent with being a pion, nor any time-delayed signal in the FGD which is consistent with a Michel electron.
CC-1π+-like: events with one positive pion candidate in a TPC and no additional neg-ative pions, electrons or positrons
CC-Other-like: CC-Inclusive events not in the CC-0π-like or CC-1π+-like samples.
The names for these samples have the “-like” suffix to distinguish them from the topolo-gies used for this selection that are based on truth information. They differ from the one defined above for the CC-Nπ topology which has been split in CC-1π+ and CC-Other.
Further selection criteria based on TPC or FGD informations are applied for pions identification in order to split the CC-Inclusive sample in the three sub-sample just de-fined. Therefore secondary tracks different from the muon candidate must be identified.
First they are required to be in the same time bunch as the muon candidate. Then they must start in the same FGD FV used for the muon candidate and if they enter one of the following TPCs they are also required to satisfy the TPC quality cut. For tracks that pass those criteria the TPC PID is performed. In case of positive tracks, three particle hypotheses are considered: pion, positron and proton. For negative tracks only the pion and electron hypotheses are considered. Thus in order to identify pions in TPC, pulls assuming particle hypotheses just mentioned are calculated, and the following cuts on the likelihoods are applied:
LM IP = Lµ+ Lπ 1− Lp
> 0.8 if p < 500M eV /c (4.6)
Lπ > 0.3 (4.7)
Neutral pions entering in TPCs are identified by the presence of positron and electron from their decay. On the other hand, if a particle does not enter the TPC, FGD informa-tions can be combined to identify whether the secondary track is a pion. It is important to stress that this is possible only for charged pions, since electrons and positrons are not distinguished in FGDs. Here two methods of pion identification are considered depending on the length, and therefore momentum of the pion track. For pion tracks too short to leave enough hits in FGD to be reconstructed as independent tracks, the Michel electron tagging is used, while for higher momentum pions, the FGD PID is performed.
Number of Michel electrons
Numer of Michel electrons
0 1 2 3 4
Number of Michel electrons
1 2 3 4
Number of Michel electrons
1 2 3 4
Figure 4.11. Number of Michel electron in CC-Inclusive sample for events with recon-structed vertex in FGD1 FV (top left) and FGD2 FV (top right). On the bottom the same figures zoomed to better display events with more than one Michel electron. Colors indicate different topologies. The MC is normalized to the POT in data.
Michel electrons come from the muons decay, which in turn have been produced by pi-ons decay. They are identified looking for delayed signals outside the beam window in FGD, according with the µ lifetime, with at least 7 hits in FGD1 or 6 hits in FGD2.
The distribution of Michel electrons associated to FGD-only tracks for events with recon-structed vertex in FGD1 FV and FGD2 FV are shown in Fig. 4.11. It is clear that most events with one reconstructed Michel electron are CC-1π+ events. To perform the FGD PID a pion pull is defined in order to identify charged pions based on the information of energy deposited by the particle as a function of track length. This method provides a discrimination between protons, muons and pions for tracks which start and stop inside an FGD detector and are in the same time bunch as the muon candidate. In this case, to be tagged as a pion, its pull must be −2 < δπ< 2.5.
Figs. 4.12 (4.15), 4.13 (4.16) and 4.14 (4.17) show distributions of events with recon-structed vertex in FGD1 FV (FGD2 FV) as function of the reconrecon-structed muon momen-tum and cosine of the scattering angle for the three sub-sample after the selection criteria are applied. The MC composition according to true topology is summarized in Tab. XIII while the true reaction content is reported in Tab. XIV.
The CC-0π-like samples have a good purity around 50%. To them contribute mainly CCQE, 2p2h and CC-RES (the pion is reabsorbed in the nucleus) interactions. The largest background is due to CC-1π+ and CC-Other events in which the π−are mis-reconstructed
as µ− and the other particles are undetected or reabsorbed in the nucleus. The events induced by ¯νµ, NC, νe and ¯νe have the same possibility described in the multiple track analysis to be a background. Also in this selection the out FV events constitute a sizeable background, distributed at low momentum (less that 0.6 GeV /c), and are due to positive tracks mis-reconstructed as negative coming from SMRD and Br-ECal. The sand µ con-tribute with the same level of contamination observed in the previous selection, since the way they mimic a CC-0π or CC-1-Track events is the same.
The CC-1π+-like and CC-Other-like samples have a purity around 42% and 68%
respectively. Most of the contamination in the CC1π+-like sample comes from DIS events for which only one pion is detected and any other hadrons have escaped or have been lost to interactions in the surrounding material. Furthermore, positive pions can be mis-identified as muons and the event tagged as ¯νµ CC-1π events. In the CC-Other-like samples the out FV events contribute less since is not likely to have an out FV events with more than one track since they are distributed at low momentum. The sand µ are negligible in both. As for the CC-Nπ, the composition in terms of reactions (Tab. XIV) for the CC-Other-like samples explains the broader momentum distributions and the nar-rower distributions for the reconstructed cosine of the scattering angle.
The selection efficiency is defined as the number of selected true events in a given topology divided by the total number of generated events in the FGD FV. For both CC-0π-like samples almost 60% of the interactions which have no pion in final state end up in the CC-0π-like sub-sample. The CC-1π+-like samples is selected with an effi-ciency of almost 28% for interactions in FGD1 FV. The lower effieffi-ciency for the case of interaction in FGD2 FV is due to the presence of inactive water layers in FGD2, which cause the drop of the track finding efficiency for isolated FGD tracks (dominant effect) and of the Michel electron detection efficiency. The CC-Other-like samples are selected with almost the 23% of efficiency
[GeV/c]
Reconstructed pµ
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0
Events/(0.2 GeV/c)
0 20 40 60 80 100 120 140 160 180 200
θµ
Reconstructed cos
-1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0
Events
0 100 200 300 400 500 600 700 800 900
Data π CC-0
π+ CC-1 CC-other BKG out FV
µ sand Data π CC-0
π+ CC-1 CC-other BKG out FV
µ sand
Figure 4.12. Distribution of events with vertex in FGD1 FV as function of the recon-structed muon momentum (left) and scattering angle (right) for the CC-0π-like sample.
Different colours indicate different topologies. MC is scaled to POT in data.
[GeV/c]
Figure 4.13. Distribution of events with vertex in FGD1 FV as function of the re-constructed muon momentum (left) and scattering angle (right) for the CC-1π+-like sample. Different colours indicate different topologies. MC is scaled to POT in data.
[GeV/c]
Figure 4.14. Distribution of events with vertex in FGD1 FV as function of the re-constructed muon momentum (left) and scattering angle (right) for the CC-Other-like sample. Different colours indicate different topologies. MC is scaled to POT in data.
[GeV/c]
Figure 4.15. Distribution of events with vertex in FGD2 FV as function of the recon-structed muon momentum (left) and scattering angle (right) for the CC-0π-like sample.
Different colours indicate different topologies. MC is scaled to POT in data.
[GeV/c]
Reconstructed pµ
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0
Events/(0.25 GeV/c)
0 10 20 30 40 50 60
θµ
Reconstructed cos
-1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0
Events
0 50 100 150 200 250
Data π CC-0
π+
CC-1 CC-other BKG out FV Data
π CC-0
π+
CC-1 CC-other BKG out FV
Figure 4.16. Distribution of events with vertex in FGD2 FV as function of the re-constructed muon momentum (left) and scattering angle (right) for the CC-1π+-like sample. Different colours indicate different topologies. MC is scaled to POT in data.
[GeV/c]
Reconstructed pµ
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0
Events/(0.25 GeV/c)
0 20 40 60 80 100 120 140
θµ
Reconstructed cos
-1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0
Events
0 50 100 150 200 250 300 350 400
Data π CC-0
π+ CC-1 CC-other BKG out FV
µ sand Data π CC-0
π+ CC-1 CC-other BKG out FV
µ sand
Figure 4.17. Distribution of events with vertex in FGD2 FV as function of the re-constructed muon momentum (left) and scattering angle (right) for the CC-Other-like sample. Different colours indicate different topologies. MC is scaled to POT in data.
Sample Topology MC Composition (%) FGD1 FV FGD2 FV
CC-0π-like
CC-0π 52.2 47.8
CC-1π+ 11.7 13.6
CC-Other 16.2 16.0
BKG 8.4 8.6
out FV 10.3 13.5
sand µ 1.2 0.5
CC-1π+-like
CC-0π 3.2 3.4
CC-1π+ 42.4 42.2
CC-Other 27.4 29.0
BKG 15.5 16.5
out FV 10.6 8.9
sand µ 0.9 0.0
CC-Other-like
CC-0π 5.0 4.1
CC-1π+ 8.4 7.2
CC-Other 67.5 69.2
BKG 12.8 14.0
out FV 6.0 5.4
sand µ 0.3 0.1
TABLE XIII. MC composition (in %) in term of topologies for the νµ CC-0π-like, CC-1π+-like and CC-Other-like samples obtained selecting CC events with vertex in FGD1 FV and FGD2 FV.
Sample Reaction MC Composition (%) FGD1 FV FGD2 FV
CC-0π-like
CCQE 40.0 35.6
2p2h 7.7 7.7
RES 21.1 22.3
DIS 10.6 10.9
COH 0.8 0.9
NC 2.6 2.2
¯
νµ 5.2 5.9
νe, ¯νe 0.7 0.5
out FV 10.3 13.5
sand µ 1.2 0.5
CC-1π+-like
CCQE 3.1 3.3
2p2h 0.6 0.4
RES 36.0 35.4
DIS 28.3 30.4
COH 5.1 5.1
NC 3.2 2.8
¯
νµ 12.0 13.0
νe, ¯νe 0.2 0.6
out FV 10.6 9.0
Sand µ 0.9 0.0
CC-Other-like
CCQE 3.9 3.1
2p2h 0.7 0.7
RES 13.3 12.8
DIS 61.8 63.1
COH 1.2 0.7
NC 5.1 5.7
¯
νµ 6.1 6.1
νe, ¯νe 1.6 2.1
out FV 6.0 5.5
sand µ 0.3 0.1
TABLE XIV. MC composition (in %) in term of reactions for the νµ CC-0π-like, CC-1π+-like and CC-Other-like samples obtained selecting CC events with vertex in FGD1 FV and FGD2 FV.