arXiv:1403.2552v1 [hep-ex] 11 Mar 2014

Measurement of the intrinsic electron neutrino component in the T2K neutrino beamwith the ND280 detector
K. Abe,46 J. Adam,32 H. Aihara,45, 23 T. Akiri,9 C. Andreopoulos,44 S. Aoki,24 A. Ariga,2 T. Ariga,2 S. Assylbekov,8
D. Autiero,29 M. Barbi,39 G.J. Barker,54 G. Barr,35 M. Bass,8 M. Batkiewicz,13 F. Bay,11 S.W. Bentham,26
V. Berardi,18 B.E. Berger,8 S. Berkman,4 I. Bertram,26 S. Bhadra,58 F.d.M. Blaszczyk,28 A. Blondel,12
C. Bojechko,51 S. Bordoni,15 S.B. Boyd,54 D. Brailsford,17 A. Bravar,12 C. Bronner,25 N. Buchanan,8R.G. Calland,27 J. Caravaca Rodrı́guez,15 S.L. Cartwright,42 R. Castillo,15 M.G. Catanesi,18 A. Cervera,16
D. Cherdack,8 G. Christodoulou,27 A. Clifton,8 J. Coleman,27 S.J. Coleman,7 G. Collazuol,20 K. Connolly,55
L. Cremonesi,38 A. Dabrowska,13 I. Danko,37 R. Das,8 S. Davis,55 P. de Perio,49 G. De Rosa,19 T. Dealtry,44, 35
S.R. Dennis,54, 44 C. Densham,44 F. Di Lodovico,38 S. Di Luise,11 O. Drapier,10 T. Duboyski,38 K. Duffy,35
F. Dufour,12 J. Dumarchez,36 S. Dytman,37 M. Dziewiecki,53 S. Emery,6 A. Ereditato,2 L. Escudero,16 A.J. Finch,26
L. Floetotto,41 M. Friend,14, ∗ Y. Fujii,14, ∗ Y. Fukuda,30 A.P. Furmanski,54 V. Galymov,6 S. Giffin,39 C. Giganti,36
K. Gilje,32 D. Goeldi,2 T. Golan,57 J.J. Gomez-Cadenas,16 M. Gonin,10 N. Grant,26 D. Gudin,22 D.R. Hadley,54
A. Haesler,12 M.D. Haigh,54 P. Hamilton,17 D. Hansen,37 T. Hara,24 M. Hartz,23, 50 T. Hasegawa,14, ∗N.C. Hastings,39 Y. Hayato,46 C. Hearty,4, † R.L. Helmer,50 M. Hierholzer,2 J. Hignight,32 A. Hillairet,51
A. Himmel,9 T. Hiraki,25 S. Hirota,25 J. Holeczek,43 S. Horikawa,11 K. Huang,25 A.K. Ichikawa,25 K. Ieki,25
M. Ieva,15 M. Ikeda,46 J. Imber,32 J. Insler,28 T.J. Irvine,47 T. Ishida,14, ∗ T. Ishii,14, ∗ S.J. Ives,17 E. Iwai,14
K. Iyogi,46 A. Izmaylov,16, 22 A. Jacob,35 B. Jamieson,56 R.A. Johnson,7 J.H. Jo,32 P. Jonsson,17 C.K. Jung,32, ‡M. Kabirnezhad,31 A.C. Kaboth,17 T. Kajita,47, ‡ H. Kakuno,48 J. Kameda,46 Y. Kanazawa,45 D. Karlen,51, 50
I. Karpikov,22 E. Kearns,3, 23, ‡ M. Khabibullin,22 A. Khotjantsev,22 D. Kielczewska,52 T. Kikawa,25 A. Kilinski,31
J. Kim,4 J. Kisiel,43 P. Kitching,1 T. Kobayashi,14, ∗ L. Koch,41 A. Kolaceke,39 A. Konaka,50 L.L. Kormos,26
A. Korzenev,12 K. Koseki,14, ∗ Y. Koshio,33, ‡ I. Kreslo,2 W. Kropp,5 H. Kubo,25 Y. Kudenko,22, § S. Kumaratunga,50
R. Kurjata,53 T. Kutter,28 J. Lagoda,31 K. Laihem,41 I. Lamont,26 M. Laveder,20 M. Lawe,42 M. Lazos,27 K.P. Lee,47
T. Lindner,50 C. Lister,54 R.P. Litchfield,54 A. Longhin,20 L. Ludovici,21 M. Macaire,6 L. Magaletti,18 K. Mahn,50
M. Malek,17 S. Manly,40 A.D. Marino,7 J. Marteau,29 J.F. Martin,49 T. Maruyama,14, ∗ J. Marzec,53 E.L. Mathie,39
V. Matveev,22 K. Mavrokoridis,27 E. Mazzucato,6 M. McCarthy,4 N. McCauley,27 K.S. McFarland,40 C. McGrew,32
C. Metelko,27 M. Mezzetto,20 P. Mijakowski,31 C.A. Miller,50 A. Minamino,25 O. Mineev,22 S. Mine,5 A. Missert,7M. Miura,46, ‡ L. Monfregola,16 S. Moriyama,46, ‡ Th.A. Mueller,10 A. Murakami,25 M. Murdoch,27 S. Murphy,11J. Myslik,51 T. Nagasaki,25 T. Nakadaira,14, ∗ M. Nakahata,46, 23 T. Nakai,34 K. Nakamura,23, 14, ∗ S. Nakayama,46, ‡T. Nakaya,25, 23 K. Nakayoshi,14, ∗ D. Naples,37 C. Nielsen,4 M. Nirkko,2 K. Nishikawa,14, ∗ Y. Nishimura,47
H.M. O’Keeffe,26 R. Ohta,14, ∗ K. Okumura,47, 23 T. Okusawa,34 W. Oryszczak,52 S.M. Oser,4 R.A. Owen,38
Y. Oyama,14, ∗ V. Palladino,19 V. Paolone,37 D. Payne,27 O. Perevozchikov,28 J.D. Perkin,42 Y. Petrov,4 L. Pickard,42
E.S. Pinzon Guerra,58 C. Pistillo,2 P. Plonski,53 E. Poplawska,38 B. Popov,36, ¶ M. Posiadala,52 J.-M. Poutissou,50
R. Poutissou,50 P. Przewlocki,31 B. Quilain,10 E. Radicioni,18 P.N. Ratoff,26 M. Ravonel,12 M.A.M. Rayner,12
A. Redij,2 M. Reeves,26 E. Reinherz-Aronis,8 F. Retiere,50 A. Robert,36 P.A. Rodrigues,40 P. Rojas,8
E. Rondio,31 S. Roth,41 A. Rubbia,11 D. Ruterbories,8 R. Sacco,38 K. Sakashita,14, ∗ F. Sánchez,15 F. Sato,14
E. Scantamburlo,12 K. Scholberg,9, ‡ S. Schoppmann,41 J. Schwehr,8 M. Scott,50 Y. Seiya,34 T. Sekiguchi,14, ∗H. Sekiya,46, ‡ D. Sgalaberna,11 M. Shiozawa,46, 23 S. Short,17 Y. Shustrov,22 P. Sinclair,17 B. Smith,17 R.J. Smith,35
M. Smy,5 J.T. Sobczyk,57 H. Sobel,5, 23 M. Sorel,16 L. Southwell,26 P. Stamoulis,16 J. Steinmann,41 B. Still,38
Y. Suda,45 A. Suzuki,24 K. Suzuki,25 S.Y. Suzuki,14, ∗ Y. Suzuki,46, 23 T. Szeglowski,43 R. Tacik,39, 50 M. Tada,14, ∗S. Takahashi,25 A. Takeda,46 Y. Takeuchi,24, 23 H.K. Tanaka,46, ‡ H.A. Tanaka,4, † M.M. Tanaka,14, ∗ D. Terhorst,41
R. Terri,38 L.F. Thompson,42 A. Thorley,27 S. Tobayama,4 W. Toki,8 T. Tomura,46 Y. Totsuka,∗∗ C. Touramanis,27
T. Tsukamoto,14, ∗ M. Tzanov,28 Y. Uchida,17 K. Ueno,46 A. Vacheret,35 M. Vagins,23, 5 G. Vasseur,6 T. Wachala,13
A.V. Waldron,35 C.W. Walter,9, ‡ D. Wark,44, 17 M.O. Wascko,17 A. Weber,44, 35 R. Wendell,46, ‡ R.J. Wilkes,55
M.J. Wilking,50 C. Wilkinson,42 Z. Williamson,35 J.R. Wilson,38 R.J. Wilson,8 T. Wongjirad,9 Y. Yamada,14, ∗K. Yamamoto,34 C. Yanagisawa,32, †† S. Yen,50 N. Yershov,22 M. Yokoyama,45, ‡ T. Yuan,7 M. Yu,58 A. Zalewska,13J. Zalipska,31 L. Zambelli,36 K. Zaremba,53 M. Ziembicki,53 E.D. Zimmerman,7 M. Zito,6 and J. Żmuda57(The T2K Collaboration)
1

University of Alberta, Centre for Particle Physics, Department of Physics, Edmonton, Alberta, Canada
2
University of Bern, Albert Einstein Center for Fundamental Physics,
Laboratory for High Energy Physics (LHEP), Bern, Switzerland
3
Boston University, Department of Physics, Boston, Massachusetts, U.S.A.
4
University of British Columbia, Department of Physics and Astronomy, Vancouver, British Columbia, Canada

2
5

University of California, Irvine, Department of Physics and Astronomy, Irvine, California, U.S.A.
6
IRFU, CEA Saclay, Gif-sur-Yvette, France
7
University of Colorado at Boulder, Department of Physics, Boulder, Colorado, U.S.A.
8
Colorado State University, Department of Physics, Fort Collins, Colorado, U.S.A.
9
Duke University, Department of Physics, Durham, North Carolina, U.S.A.
10
Ecole Polytechnique, IN2P3-CNRS, Laboratoire Leprince-Ringuet, Palaiseau, France
11
ETH Zurich, Institute for Particle Physics, Zurich, Switzerland
12
University of Geneva, Section de Physique, DPNC, Geneva, Switzerland
13
H. Niewodniczanski Institute of Nuclear Physics PAN, Cracow, Poland
14
High Energy Accelerator Research Organization (KEK), Tsukuba, Ibaraki, Japan
15
Institut de Fisica d’Altes Energies (IFAE), Bellaterra (Barcelona), Spain
16
IFIC (CSIC & University of Valencia), Valencia, Spain
17
Imperial College London, Department of Physics, London, United Kingdom
18
INFN Sezione di Bari and Università e Politecnico di Bari, Dipartimento Interuniversitario di Fisica, Bari, Italy
19
INFN Sezione di Napoli and Università di Napoli, Dipartimento di Fisica, Napoli, Italy
20
INFN Sezione di Padova and Università di Padova, Dipartimento di Fisica, Padova, Italy
21
INFN Sezione di Roma and Università di Roma “La Sapienza”, Roma, Italy
22
Institute for Nuclear Research of the Russian Academy of Sciences, Moscow, Russia
23
Kavli Institute for the Physics and Mathematics of the Universe (WPI),
Todai Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba, Japan
24
Kobe University, Kobe, Japan
25
Kyoto University, Department of Physics, Kyoto, Japan
26
Lancaster University, Physics Department, Lancaster, United Kingdom
27
University of Liverpool, Department of Physics, Liverpool, United Kingdom
28
Louisiana State University, Department of Physics and Astronomy, Baton Rouge, Louisiana, U.S.A.
29
Université de Lyon, Université Claude Bernard Lyon 1, IPN Lyon (IN2P3), Villeurbanne, France
30
Miyagi University of Education, Department of Physics, Sendai, Japan
31
National Centre for Nuclear Research, Warsaw, Poland
32
State University of New York at Stony Brook, Department of Physics and Astronomy, Stony Brook, New York, U.S.A.
33
Okayama University, Department of Physics, Okayama, Japan
34
Osaka City University, Department of Physics, Osaka, Japan
35
Oxford University, Department of Physics, Oxford, United Kingdom
36
UPMC, Université Paris Diderot, CNRS/IN2P3, Laboratoire dePhysique Nucléaire et de Hautes Energies (LPNHE), Paris, France
37
University of Pittsburgh, Department of Physics and Astronomy, Pittsburgh, Pennsylvania, U.S.A.
38
Queen Mary University of London, School of Physics and Astronomy, London, United Kingdom
39
University of Regina, Department of Physics, Regina, Saskatchewan, Canada
40
University of Rochester, Department of Physics and Astronomy, Rochester, New York, U.S.A.
41
RWTH Aachen University, III. Physikalisches Institut, Aachen, Germany
42
University of Sheffield, Department of Physics and Astronomy, Sheffield, United Kingdom
43
University of Silesia, Institute of Physics, Katowice, Poland
44
STFC, Rutherford Appleton Laboratory, Harwell Oxford, and Daresbury Laboratory, Warrington, United Kingdom
45
University of Tokyo, Department of Physics, Tokyo, Japan
46
University of Tokyo, Institute for Cosmic Ray Research, Kamioka Observatory, Kamioka, Japan
47
University of Tokyo, Institute for Cosmic Ray Research, Research Center for Cosmic Neutrinos, Kashiwa, Japan
48
Tokyo Metropolitan University, Department of Physics, Tokyo, Japan
49
University of Toronto, Department of Physics, Toronto, Ontario, Canada
50
TRIUMF, Vancouver, British Columbia, Canada
51
University of Victoria, Department of Physics and Astronomy, Victoria, British Columbia, Canada
52
University of Warsaw, Faculty of Physics, Warsaw, Poland
53
Warsaw University of Technology, Institute of Radioelectronics, Warsaw, Poland
54
University of Warwick, Department of Physics, Coventry, United Kingdom
55
University of Washington, Department of Physics, Seattle, Washington, U.S.A.
56
University of Winnipeg, Department of Physics, Winnipeg, Manitoba, Canada
57
Wroclaw University, Faculty of Physics and Astronomy, Wroclaw, Poland
58
York University, Department of Physics and Astronomy, Toronto, Ontario, Canada(Dated: March 12, 2014)
The T2K experiment has reported the first observation of the appearance of electron neutrinos ina muon neutrino beam. The main and irreducible background to the appearance signal comes fromthe presence in the neutrino beam of a small intrinsic component of electron neutrinos originatingfrom muon and kaon decays. In T2K, this component is expected to represent 1.2% of the total
neutrino flux. A measurement of this component using the near detector (ND280), located 280 m
from the target, is presented. The charged current interactions of electron neutrinos are selected by3
combining the particle identification capabilities of both the time projection chambers and electromagnetic calorimeters of ND280. The measured ratio between the observed electron neutrino beamcomponent and the prediction is 1.01 ± 0.10 providing a direct confirmation of the neutrino fluxes
and neutrino cross section modeling used for T2K neutrino oscillation analyses. Electron neutrinos
coming from muons and kaons decay are also separately measured, resulting in a ratio with respect
to the prediction of 0.68 ± 0.30 and 1.10 ± 0.14, respectively.

I.

INTRODUCTION

The T2K (Tokai-to-Kamioka) experiment [1] is a long
baseline neutrino oscillation experiment that uses an intense muon neutrino beam produced at the Japan Proton
Accelerator Research Complex (J-PARC) in Tokai. The
primary goals of the experiment are the precise determination of the oscillation parameter θ13 via electron neutrino appearance, and of the parameters θ23 and ∆m232
via muon neutrino disappearance. Neutrino interactions
are observed at a near detector, ND280, where the flavour
composition of the incoming neutrino flux is not expected
to be affected by oscillation, and at the far detector,
Super-Kamiokande (SK), where oscillation significantly
affects the composition.
The T2K baseline, the neutrino beam configuration,and the ability of the far detector to distinguish electrons
from muons results in excellent sensitivity for νe appearance. The νµ → νe oscillation probability depends on
θ13 , and on sub-leading effects that depend on the δCPphase and on the mass hierarchy [2]. Recently T2K reported the first observation of electron neutrino appearance with a 7.3 σ significance, by observing 28 electron
neutrino events compared to a background expectationof 4.92 ± 0.55 events for θ13 = 0 [3]. Among those background events, 3.2 are expected to be due to the intrinsic
νe beam component, an irreducible background to theelectron neutrino appearance search.
The intrinsic νe in the beam are an unavoidable product of conventional neutrino beams where pions andkaons, produced by the interaction of a proton beam witha target, decay to form a νµ beam. When the muons andkaons decay, a small component of νe is produced in addition to the νµ . In the T2K case νe are expected torepresent about 1.2% of the total neutrino flux [4]. This
component will be the main source of background for
all the proposed long-baseline neutrino oscillation experiments [5–7] aiming to measure CP violation in the leptonic sector by precisely measuring νe (ν e ) appearance in∗ also at J-PARC, Tokai, Japana νµ (ν µ ) beam. A direct measurement of this component
performed at ND280 is presented in this paper.
ND280 is a magnetized detector located at a distance of
280 m from the target. For this analysis neutrino charged
current (CC) interactions in the Fine Grained Detectors(FGDs [8]) are selected. The combination of the particle
identification (PID) capabilities of three Time Projection Chambers (TPC [9]) and a set of Electromagnetic
Calorimeters (ECals [10]) is used to distinguish electrons
from muons, allowing the selection of a clean sample of νe
CC interactions with a purity of about 65%. The background is dominated by photon conversions producing
e+ e− pairs in the FGD.
In the T2K oscillation analyses the measurement of
the spectra of νµ CC interactions at ND280 is used toconstrain the uncertainties on the unoscillated neutrino
fluxes and on the neutrino cross section parameters. The
νµ CC sample constrains also the νe flux and cross section
because of the significant correlations between the νµ andthe νe fluxes, which originate from the same hadrons.
The νµ and νe cross sections are expected to be the same,
except for radiative corrections and the different lepton
mass [11].
The beam νe component is directly measured at ND280
and it is compared with the expectations when fluxes andcross section uncertainties are constrained by the same fit
to the ND280 νµ CC sample used for the oscillation analyses. This measurement directly confirms the validity ofthe procedure used in all T2K oscillation analyses.
The paper is organized as follows. In Section II theT2K experiment, the flux prediction and the neutrino
interaction cross section model are described, and in Section III ND280 and the detectors used in this analysis are
introduced. The electron neutrino selection is then described in Section IV and the control of the backgrounds
entering the analysis is shown in Section V. A descriptionof the systematics is given in Section VI and the fit used
to extract the beam νe component is shown in Section
VII. Finally the results are given in Section VIII and asummary in Section IX.

II.

EXPERIMENTAL OVERVIEW† also at Institute of Particle Physics, Canada‡ affiliatedmember at Kavli IPMU (WPI), the University ofTokyo, Japan§ also at Moscow Institute of Physics and Technology and National
Research Nuclear University ”MEPhI”, Moscow, Russia¶ also at JINR, Dubna, Russia∗∗ deceased†† also at BMCC/CUNY, Science Department, New York, New
York, U.S.A.

T2K is the first long baseline experiment designed toobserve electron neutrino appearance in a nearly puremuon neutrino beam. The neutrino beam is producedby the J-PARC accelerator complex where protons areaccelerated up to 31 GeV/c before being extracted in
5 µs long spills with a repetition rate that has been decreased from 3.6 s to 2.6 s over the data-taking periods.

4
The spill consists of 8 bunches (6 during the first datataking period), each 15 ns wide. The protons strike a
91.4 cm long graphite target, producing hadrons, mainly
pions and kaons. The positively charged particles are focused by a series of three magnetic horns operating at
250 kA before entering a 96 m long decay volume where
they decay producing mainly muon neutrinos. A small
fraction of the kaons, and the muons produced by pion
decay, can also decay producing electron neutrinos. Mostof the surviving charged particles are stopped in a beam
dump at the end of the decay volume. A muon monitor (MUMON) situated downstream of the beam dump
measures the profile of high energy muons not stopped
by the beam dump, monitoring the stability of the beam
intensity and the direction of the beam. The neutrinos
are sampled 280 m and 295 km from the target, at the
ND280 near detector and Super-Kamiokande (SK) far
detector, respectively.
The direction of the proton beam and the axis of thetarget and horns is 2.5◦ away from the direction to SK,
giving a narrow band νµ beam peaked at 0.6 GeV towards SK. This corresponds to the oscillation maximum
for the 295 km baseline. T2K is the first experiment designed to use this configuration, called the off-axis technique. This configuration also has the advantage of reducing the beam νe component in the oscillation region
and the high energy neutrino flux which contributes tobackgrounds in the oscillation analyses.
The near detector complex is comprised of an on-axis
detector (INGRID [12]) and an off-axis detector (ND280)
that will be described in detail in the next section. SK
is a 50 kt cylindrical water Cherenkov detector. The water tank is optically separated into two concentric detectors, an inner detector (ID) and an outer detector (OD),
both instrumented with photomultipliers. Charged particles emitted from neutrino interactions produce photons
through the Cherenkov effect and ring-shaped patterns
are detected on the walls by the photomultipliers. The
ring pattern is used to identify the type of the particle.
Until recently, the main backgrounds to the electron neutrino appearance searches came from the intrinsic beam
νe and from neutral current (NC) interactions in whicha π 0 in the final state (NCπ 0 ) is produced but only one
electron-like ring is reconstructed [13, 14]. A new reconstruction algorithm [3] has been developed to substantially reduce the NCπ 0 background, leaving the intrinsic
beam νe component as the main background to the νeappearance analysis.
In this paper a direct measurement of the νe beam component is presented. All the data collected between January 2010 and May 2013 are used for the analysis. The
data are subdivided into different run periods as shownin Tab. I. A small fraction of Run III data (∼ 15%) wascollected with magnetic horns operating at 205 kA instead of the nominal 250 kA, while for Run I data only
one subset of the ECal, the downstream module, wasinstalled and operated. The remaining modules were installed and commissioned before the start of Run II. The

TABLE I. Definition of T2K runs and the number of protons
on target (p.o.t.) used in the analysis.
T2K runRun I
Run IIRun IIIRun IV
Total

Dates
Jan. 2010 – Jun. 2010
Nov. 2010 – Mar. 2011
Mar. 2012 – Jun. 2012
Jan. 2013 – May. 2013
Jan. 2010 – May 2013

ND280 p.o.t. (×1019 )
1.7
7.9
15.6
33.8
59.0

simulated data used in this analysis corresponds to morethan ten times the p.o.t. of the data, and the various experimental conditions of the different data taking periods
are reproduced.

A.

Flux prediction

A good knowledge of the initial neutrino fluxes at
ND280 and at SK is fundamental for all the physics analyses in T2K. The νµ (νe ) components of the beam aremainly produced through charged pion (muon) and kaon
decays.
In the T2K simulation the interaction of the primary
proton beam and the propagation of secondary particles
in the carbon target are simulated with FLUKA [15].
The flux prediction is based on the hadron production
measurements performed by NA61/SHINE, a fixed target experiment at the CERN SPS in which a proton beamof the same energy as the T2K beam interacts with a thincarbon target (2 cm long) or with a T2K replica target(91.4 cm long) [16]. The charged hadrons produced in
the proton-carbon interactions are tracked by a system of
TPCs, and their production cross sections as functions of
momentum and angle are measured. The NA61/SHINE
measurements cover most of the relevant hadron production phase space for the T2K flux. The observed production cross section of pions [17] and kaons [18] on the thintarget are used in the T2K flux simulation to reduce theuncertainties on the flux prediction [4]. Measurementsfrom other experiments (Eichten et al. [19] and Allaby etal. [20]) are used to reduce the uncertainty of the particle
production in the region not covered by NA61/SHINE.
The propagation of particles through the elements ofthe beamline is simulated with GEANT3 [21]. The particles are propagated through the horns’ magnetic field
and may interact with the surrounding materials. Particle decays into neutrinos are simulated as well as theinteractions in the decay volume and the beam dump.
The modeling of hadronic interactions is done using the
GCALOR model [22]. The beam direction, its intensity
and the beam profile are measured by the INGRID and
MUMON detectors. The neutrino fluxes are describedby a covariance matrix in bins of neutrino energy andtype. The uncertainty on the νµ flux is below 12% forneutrino energies around 0.6 GeV. The expected νe fluxand its uncertainty at ND280 are shown in Figs. 1 and5Flux/(cm 2⋅50 MeV⋅10 21 p.o.t)

B.
Total ND280 ν e Flux

1010

Pion Parents
Kaon Parents

109

Muon Parents

108
107
106
0

2

4

6

8
10
Eν (GeV)

Fractional Error

FIG. 1. The prediction of the νe flux at ND280 broken downby the neutrino parent particle type [4].

0.3

ND280 νe Flux
Total
Hadronic Interactions
Proton Beam, Alignment and Off-axis Angle

0.2

Horn Current & Field

0.1

0

10-1

1

10
Eν (GeV)

FIG. 2. The νe flux uncertainties at ND280 [4].

2. Most of the intrinsic beam νe component comes fromthe decay of µ+ (µ+ → e+ ν̄µ νe ) produced by the pions’decay and from charged and neutral kaons. The charged
kaons produce νe via the decays K + → π 0 e+ νe that has abranching ratio of 5.1%, while the neutral kaons produce
νe through the decay KL0 → π − e+ νe that has a branchingratio of 40.5%. The νe from muon decays contribute tomost of the flux in the low energy region, below 1.5 GeV,
while above that energy almost all of the νe flux comesfrom kaon decays (Fig. 1). A more detailed discussion of
the uncertainties contributing to the νe flux (Fig. 2) can
be found in [4]. As the physics processes leading to νefrom muon decay and from kaon decay are different, theanalysis presented in this paper extracts a measurementof their separate contributions to the flux, as well as theinclusive flux of νe .

Neutrino interaction model

Neutrino interactions in ND280 are simulated using
the NEUT [23] event generator. This generator covers
the range of neutrino energies from several tens of MeV
to hundreds of TeV, and it simulates the full range of nuclear targets used in ND280. In the simulation, neutrino
interactions are generated in the entire ND280 volume
on both active and inactive targets, providing the necessary information for the signal and for the backgrounds
coming from interactions occurring outside of the ND280
inner detectors. A complete description of the models
used in the T2K simulation is given in [24].
The dominant cross section process at the peak of theT2K beam energy is Charged Current Quasi-Elastic scattering (CCQE): νl + N → l + N , while at higher energies, above the pion production threshold, single pion
production (CC1π) and deep inelastic scattering (DIS)
contribute to the total charged current cross section.
In NEUT, CCQE interactions are simulated using themodel of Llewellyn Smith [25], with the nuclear effects described by the relativistic Fermi gas model of Smith andMoniz [26, 27]. The form factors describing the vector
and the axial masses are parameterized with MV = 0.84
GeV and MA = 1.21 GeV. The Fermi momentum is set
to 217 (225) MeV/c and the binding energy to 25 (27)
MeV for carbon (oxygen).
The pion production is simulated in NEUT using themodel of Rein and Sehgal [28]. Below neutrino energiesof 2 GeV, 18 resonances and their interference terms are
simulated. For 20% of the ∆ resonances NEUT simulates pion-less decay in which the ∆ de-excites without
emitting pions.
Multi-pion and DIS processes are simulated using the
GRV98 parton distribution functions [29]. If the invariant mass of the hadronic system (W ) is in the range
1.3 < W < 2.0 GeV/c2 only pion multiplicities greaterthan one are considered to avoid double counting with
the Rein and Sehgal model. For W > 2.0 GeV/c2
PYTHIA/JETSET [30] is used, applying the correctionsin the small Q2 region developed by Bodek and Yang [31].
Additional details on the NEUT simulation can be foundin [1].

1.

Neutrino interaction uncertainties

The modeling of the neutrino interactions constitutes
an important source of systematic uncertainties for all
T2K analyses. A detailed description of the uncertainties can be found in [14]. Only a brief summary of thesystematic uncertainties is given here.
a. CCQE model uncertainty Recent measurementsof CCQE scattering in the 1 GeV region [32] show large
discrepancies on the measurement of the axial mass MAQE
with respect to older measurements. The strategy thatis chosen in T2K analyses is to allow the ND280 νµ CC
samples to constrain this parameter, including a large

6prior uncertainty (σM QE = 0.43 GeV) to account forA
the difference between the NEUT nominal value and theNEUT best-fit to the MiniBooNE data. Additional degrees of freedom are allowed by three independent CCQE
normalization factors (xQE
1,2,3 ) for different neutrino energy ranges. Below 1.5 GeV an uncertainty of 11% isassigned to xQE
1 , corresponding to the uncertainty of the
MiniBooNE flux. The other two normalization factors,
for Eν > 3.5 GeV
for 1.5 < Eν < 3.5 GeV and xQE
xQE
32
are given a prior uncertainty of 30% to account for thediscrepancy between MiniBooNE and NOMAD data [33].
b. Pion production For single pion production a
joint fit to the MiniBooNE measurements of charged current single π + production (CC1π + ) [34], charged current
single π 0 production (CC1π 0 ) [35], and neutral current
single π 0 production (NC1π 0 ) [36] using NEUT has been
performed, varying several parameters.
The parameters varied include the axial mass in theRein and Sehgal model MARES , the normalization ofCC1π (xCC1π
for Eν < 2.5 GeV and xCC1π
for Eν >1
2
0
2.5 GeV), and the normalization of NC1π 0 (xNC1π ).
Contributions to the MiniBooNE samples from CC
multi-pion, NC coherent interactions, NC charged pion
interactions and NC multi-pion are relatively small
and they are included in the analysis described herewith a large prior uncertainty.
For charged current coherent pion production a 100% normalization
uncertainty(xCC coh. ), motivated by the non-observationof the process in the few-GeV energy range by K2K [37]and SciBooNE [38], is assigned. For neutral current
charged pion production and all other NC interactions,
including deep inelastic scattering (DIS), a 30% normalization uncertainty is introduced (xNC oth. ).
A 20% uncertainty on the fraction of ∆ that de-excites
without emitting pions (xπ−less ) is also included.
Finally for CC multi-pion/DIS interactions an energy
dependent uncertainty is added (xCC other ), applying aweight w with the form w = 1 + xCC other /Eν ( GeV).
xCC other is allowed to vary around a nominal value of 0
with a prior uncertainty of 0.4.
c. Nuclear model uncertainties NEUT models nuclei with a relativistic Fermi gas model (RFG) using the
Fermi momentum pF determined from electron scattering data. The uncertainty on pF is 30 MeV/c, covering
possible discrepancies in the CCQE cross section at low
Q2 . The uncertainty is applied independently for interactions on carbon and oxygen targets.
Alternatives to the RFG model of the nuclei are considered by making comparisons to a spectral function
nuclear model implemented in the NuWro neutrino interaction generator [39]. The discrepancy in CCQE interaction models using the RFG and spectral function are
assigned as the uncertainty and represented by the parameter xSF , which linearly varies the predicted lepton
kinematics between the RFG (xSF = 0) and spectral
function (xSF = 1) models.

TABLE II. The parameters in the NEUT cross section model
along with their nominal values and uncertainties prior to theanalysis of ND280 data.
Parameter
QE
MA
(GeV)
xQE
1
xQE
2
xQE
3
xSF
pF (12 C) (MeV/c)pF (16 O) (MeV/c)
EB (12 C) (MeV)
EB (16 O) (MeV)
RES
MA
(GeV)
xCC1π
1
xCC1π
2
0
xNC1π
π−lessx
xCC coh.
xNC otherCC otherx(GeV)

Nominal Value
1.21
1.00
1.00
1.00
0.0
217
225
25
27
1.16
1.63
1.00
1.19
0.20
1.00
1.00
0.00

Uncertainty
0.43
0.11
0.30
0.30
1.0
30
30
3
3
0.11
0.43
0.40
0.43
0.20
1.00
0.30
0.40

d. Final state interactions (FSI) model tuning The
NEUT FSI model includes parameters which alter the
microscopic pion interaction probabilities in the nucleus.
The central value of these parameters and their uncertainties are determined from fits to pion scattering
data [40].
The cross section model parameters and their uncertainties are summarized in Tab. II. These uncertainties
are used as prior uncertainties in the fit, along with theflux uncertainties to the ND280 fit to the νµ CC samples. As will be shown in Sect. VI C, the flux systematic
uncertainties are reduced by the measurements of νµ CC
interactions in ND280.

III.

THE ND280 DETECTOR

The off-axis ND280 detector is a magnetized multipurpose detector located at the same off-axis angle as
SK, at a distance of 280 m from the T2K target. The
main purpose of ND280 is to measure the properties ofνµ and νe CC interactions before oscillation, reducing
uncertainties in the T2K oscillation analyses. It is also
used to measure neutrino cross sections.
The layout of ND280 is shown in Fig. 3 and a complete description can be found in [1]. It is composed of anumber of sub-detectors installed inside the refurbishedUA1/NOMAD magnet that provides a magnetic field of
0.2 T. The sub-detectors are side muon range detectors(SMRD [41]) installed in the magnet yokes to track highangle muons, a π 0 detector (P0D [42]) explicitly built
to measure neutrino interactions with the production ofπ 0 in the final state, and a tracking system. The tracking detector is composed of two fine-grained detectors

7
y
x
z

nation of TPC and ECal (when available) particle identification (PID) is used to select electrons, rejecting mostof the muon background produced by the dominant νµ
CC interactions in the FGD.

A.

Beam
Direction

FIG. 3. A schematic view of the ND280 detector.

(FGDs) used as the target for the neutrino interactions,and three time projection chambers (TPCs). The tracker
and the P0D are surrounded by a set of electromagnetic
calorimeters (ECal). In this analysis the tracking detector, Downstream ECal (DsECal) and the Barrel ECal
modules are used. The DsECal is installed downstreamof the tracker system while the Barrel ECal surrounds
the tracker and consists of six different modules (two installed at the top of the tracker, two at the bottom andone at each side).
The first (upstream) FGD is composed of extruded
polystyrene scintillator bars with layers oriented alternately in the x and y directions (defined in Fig. 3), allowing three dimensional tracking of the charged particles. The second FGD has the same structure, but thepolystyrene bars are interleaved with water layers to allow for the measurement of neutrino interactions on water.
The TPCs consist of an inner box filled with
Ar:CF4 :iC4 H10 and an outer box filled with CO2 . Eachside of the TPCs is instrumented with 12 MicroMEGAS
modules arranged in two columns. Each MicroMEGAS
is segmented into 1728 pads arranged in 48 rows and 36
columns, allowing a 3D reconstruction of charged particles produced in neutrino interactions.
The ECals are sampling calorimeters consisting of layers of 1 cm of plastic scintillator, divided into bars 4 cm
wide, separated by 1 mm layers of lead. Alternating layers are aligned orthogonally to one another to provide
three dimensional reconstruction of tracks and showers.
The DsECal consists of 34 layers with readout from bothends of the scintillator bars. The Barrel ECal has 31 layers with readout from both ends (one end) on the bars
parallel (perpendicular) to the beam direction.
For the analysis described in this paper, neutrino interactions in both the FGDs are selected by requiring atleast one track to enter the downstream TPC. A combi-

TPC reconstruction and PID performance

To reconstruct tracks in the TPC, the ionization signals on pads that exceed a threshold are saved as waveforms. Waveforms coincident in time and on adjacentpads in the vertical direction are joined to form clusters.
Contiguous clusters are then combined to form track candidates and the kinematic parameters of the track are
obtained with a maximum-likelihood fit to the observed
charge distribution. After track reconstruction in the
TPC, signals in the FGD are matched to the TPC tracks.
The PID in the TPC is based on the measurementof the ionization produced by charged particles crossing
the gas. To perform particle identification in the TPC,
the ionization in each cluster is corrected for the track
length sampled by the pad column. Using 70% of thelowest charge deposits on the pads, a mean ionization
value is calculated and is compared to that expected forparticle type i at the reconstructed momentum. This
comparison is used to form the ‘pull’ δi (the difference
between the measured mean ionization and the expected
one divided by the resolution). The resolution depends
on the number of samples and path length with a typicalresolution for muons of 8%.
The deposited energy as a function of the reconstructed
momentum for negatively charged particles starting in
the FGD, compared with the expected curves from thesimulation is shown in Fig. 4. In the energy region ofinterest for T2K, the ionization difference between electrons and muons is 30–40% allowing good separation between the two particles. Fig. 5 shows the distribution of
the pulls in two samples: the first is a sample of muons
which cross the detector whose selection is described in
Sect. V A, and the second is a sample of electrons andpositrons selected as described in Sect. V B.

B.

ECal reconstruction and PID performance

Each ECal module has scintillator bars in two orientations. The reconstruction is performed by forming two
sets of 2D clusters, one for each orientation, then combining them to form a 3D cluster. The 2D objects are built
by clustering together adjacent hits. If more than one
2D object exists in a particular orientation, the choiceof which should be used in the 3D object is based on alikelihood statistic combining time, position and charge
information, aided by the extrapolation of in-time TPC
tracks.
After an ECal cluster is reconstructed, PID statistics to classify the cluster are calculated. In particular,muons
pions

5
4.5

120

electrons
protons4

ers and less than one for highly ionizing particles
such as protons which deposit most of their energy
at the end of the track.

140

100

3.5
80

3
2.5

60

2

40

1.5

Samples of simulated electrons and muons are used togenerate probability density functions (PDFs) that areused to construct the likelihood ratio. Fig. 6 shows the
RMIP/EM statistic in data and simulation for samples ofe+ e− from photon conversions and from crossing muons.

20

1
200 400 600 800 1000 1200 1400 1600 1800 2000

0

Momentum (MeV/c)
FIG. 4. TPC ionization energy loss per unit length as a function of the reconstructed momentum for negatively charged
particles as measured by the TPCs (blocks) and the expected
dependencies (curves).

Entries (a.u.)

Energy loss (keV/cm)

8

0.16

e+ or e- data

0.14

e+ or e- simulation

0.12µ data0.1µ simulation

0.08
0.06

Entries (a.u.)

0.04
0.16
0.02

e+ or e- data

0.14

0-50 -40e+ or e- simulation

0.12µ data0.1µ simulation-30 -20

-10

0

10

20

30

40

50

RMIP/EM

0.08

FIG. 6. Distribution of RMIP/EM for electrons or positrons
coming from photon conversions, and for muons in the downstream ECal in data (points) and in the simulation (lines).

0.06
0.04
0.02
0
-8

-6

-4

-2

0

2

4

6

8

δe

FIG. 5. TPC PID pulls in the electron hypothesis (δe ) for
electrons or positrons coming from photon conversions andfor muons in data (points) and in the simulation (lines).

RMIP/EM is a statistic to separate electromagnetic showers and minimally ionizing tracks and is a likelihood ratiousing characteristics that distinguish tracks and showers:• circularity: clusters due to tracks are expected to
be long and thin, while showers are expected tohave a more spherical shape;• charge distribution: electromagnetic showers havea highly non-uniform charge distribution compared
to a minimally ionizing track. The charge distribution is parameterized using the ratio of the second and first moments and the ratio of the highest
charge to the lowest charge layer;• charge ratio between first quarter and last quarter of the track: it is expected to be one for minimally ionizing tracks which deposit energy uniformly, greater than one for electromagnetic show-

The energy deposited in the ECal (EEM ) is used forparticles with reconstructed momenta in the TPC larger
than 1 GeV/c, to discriminate between electrons andmuons. A charged particle that enters the ECal from the
TPC has momentum measured in the tracker and this canbe compared to the energy deposited in the ECal. Energy
is reconstructed under the hypothesis that the energy deposit is due to an electromagnetic shower. A maximum
likelihood fit for the shower energy is constructed using
the following variables:• the total visible energy in the cluster: the total energy deposited into the scintillator is strongly correlated to the energy of the particle responsible for
the EM shower and this parameter dominates theenergy measurement in the ECal;• the RMS and the skewness of the deposited energy: these parameters provide additional information that refines the energy measurement.
The fit uses PDFs constructed from simulated photons
at energies from 50 MeV to 25 GeV, with the majority ofphotons below 2 GeV. The energy resolution for electrons
at 1 GeV is approximately 10%.

9TABLE III. Fraction of electrons entering each PID branch,and efficiency and purity of the PID selection.

Category
ECal
DsDsECal

D

TPC3
TPC3
TPC3
FGD2
FGD2

FGD1
FGD1

BarrelECal
Barrel
ECal
TPC2
TPC1
TPC1
TPC2

TPC only
TPC+DsECal
TPC+Barrel
ECal

FGD1 vertices
eventseff. (%)(%)[pur. (%)]
56.6
45.4
[92.6]
82.6
32.0[97.8]
86.1
22.6[91.4]

FGD2 vertices
eventseff. (%)(%)[pur. (%)]
53.1
34.1
[90.9]
89.1
59.0[93.8]
88.6
6.9[86.5]

upon which sub-detectors are used for the track reconstruction:
BarrelECal
ECal
BarrelFIG. 7. Side view of a νe CCQE-like event in FGD2 with anelectron-like track reconstructed in TPC3 and showering in
the downstream ECal.

IV.

SELECTION OF ELECTRON NEUTRINO
CC EVENTS AT ND280

The signal events for this analysis are νe CC interactions occurring in FGD1 or FGD2. Events in which there
are electron-like tracks starting in either FGD are selected, and additional cuts are applied to reduce the contamination from photons converting into an e+ e− pair in
an FGD. The events are then split into separate CCQElike and CCnonQE-like samples. A typical νe CC candidate selected in the analysis is shown in Fig. 7.
After requiring a good beam spill and good
ND280 data quality—all subdetectors were functioning
correctly—the reconstructed objects in each spill are split
into 8 time bunches (6 for Run I). For each bunch thehighest momentum negatively charged track is selected
as the lepton candidate. If this track does not start in
the fiducial volume (FV) of one of the FGDs the event isrejected. The FGD fiducial volume is defined by removing the outer 48 mm at each edge in x and y (distanceequivalent to five scintillator bars) and the front 21 mm(7 mm) at the begin of the FGD1 (FGD2), corresponding
to the first x-y (x) layer.
The track is also rejected if the reconstructed momentum is smaller than 200 MeV/c as that region is dominated by background from photon conversions. To ensure
good TPC PID performance the selected track needs tohave at least 36 reconstructed clusters in the TPC, corresponding to tracks crossing at least half of the TPC in
the direction parallel to the beam.
Applying these criteria, 79% of the tracks are expected
to be muons and just 6.5% electrons (see the inset in
Fig. 8). To select electrons, the TPC and ECal PID capabilities are combined. The PID criteria applied depend• if the electron candidate does not enter the ECal,the energy loss in the TPC is required to beelectron-like (−1 < δe < 2), not muon-like (|δµ | >2.5) and not pion-like (|δπ | > 2). This selection is
also used for all tracks with reconstructed momentum in the TPC below 300 MeV/c as the ECal PID
is not optimized for such low energy particles;• for tracks entering the ECal, the TPC PID is relaxed, only requiring an electron-like track (−2 <δe < 2.5). The ECal particle identification criteria depend on the momentum of the track as itenters the ECal module. For tracks with a momentum greater than 1 GeV/c, the energy depositedin the ECal module is used to separate electromagnetic showers from minimum ionizing particles.
Tracks are required to have EEM > 1100 MeV. For
lower-momentum particles, the multi-variate analysis quantity RMIP/EM is used. These tracks musthave RMIP/EM > 0.
Tab. III shows the performance of the different PID
cuts, and highlights the effectiveness of combining the
TPC and ECal information.
The momentum distribution of the particles passing
the PID cuts is shown in Fig. 8. 99.9% of muons are
rejected by the PID cuts, and the sample is 92% purein electrons. Although a high-purity sample of electrons
has been selected, 65% of the tracks arise from γ → e+ e−
conversions in the FGD, and only 27% are from νe CCinteractions. The majority of the photons come fromneutrino interactions upstream of the FGD in which theconversion occurred.
To reduce the contamination from these photons, vetocuts are applied to require no reconstructed tracks in the
P0D, TPC or Barrel ECal in the same bunch, starting
more than 100 mm upstream of the initial position of theelectron candidate.
An additional cut in the selection removes electrons
that are part of an e+ e− pair. The event is rejected if
there is a positive track which is electron-like (|δe | < 3),starts within 100 mm of the electron candidate, and if thee+ e− pair has an invariant mass of less than 100 MeV/c2 .

1000

10000

νe CCnonQE
γ bkg (in FGD FV)
γ bkg (out FGD FV)

5000

500

µ background
Other background0

Entries/(200 MeV/c)

νe CCQE

Entries/(200 MeV/c)

Entries/(200 MeV/c)

10νe CCQE

80

νe CCnonQE
γ bkg (in FGD FV)
γ bkg (out FGD FV)

60µ background
Other background40

500 1000 1500 2000 2500 3000 3500 4000 4500 5000

Momentum (MeV/c)

0

20
500

1000 1500 2000 2500 3000 3500 4000 4500 5000

Momentum (MeV/c)
0

These cuts reduce the γ → e+ e− contamination from
65% to 30%.
To further improve the νe purity, additional selections
are applied and the sample is separated into CCQE-likeand CCnonQE-like categories. The first mainly contains
νe CCQE interactions while the latter is dominated by
νe CC interactions producing pions in the final state.
The CCQE-like selection requires the absence of othertracks in the TPC, except the electron candidate itself. If
the electron candidate starts in FGD1 then there must be
no isolated reconstructed tracks in FGD1 and no Michelelectrons coming from pion decays (identified as delayed
hits in FGD1). These two requirements do not apply toevents in FGD2 as the lower number of scintillator layers reduces the ability to reconstruct tracks and identify
delayed hits.
If the electron candidate starts in FGD2 there must
be no activity in the ECal, except that caused by theelectron candidate. This cut is only applied to events in
FGD2, as electrons from FGD1 can shower in FGD2 andcan cause additional ECal activity not associated withthe original electron candidate track.
The CCnonQE-like selection requires the presence ofat least one other track which starts close to the electron candidate (within 50 mm). As in the CCQE-like selection, only FGD-TPC tracks are considered for FGD2
events, whereas FGD-only tracks are also considered for
FGD1 events. For FGD1 events the presence of a Michelelectron in the FGD is used to tag CCnonQE-like candidates.
The final CCQE-like and CCnonQE-like selections areshown in Fig. 9 and Fig. 10 respectively. The overall
efficiency of selecting νe CC interactions is 26%, and theefficiency of the selections as a function of νe energy isshown in Fig. 11. The purity of the selections and thepredicted number of selected events are shown in Tab. IV.

500 1000 1500 2000 2500 3000 3500 4000 4500 5000

Momentum (MeV/c)
FIG. 9. Reconstructed electron momentum of events selectedin the CCQE-like selection. The error on the points is thestatistical error on the data, and the simulation is divided
into the same categories as Fig. 8.

Entries/(200 MeV/c)

FIG. 8. Reconstructed electron momentum of events passing
the PID selection. The inset shows the same distribution before applying the PID selection. The signal is divided into νeproducing CCQE or CCnonQE interactions. The backgroundis divided into photon conversions produced by neutrino interaction inside or outside the FGD, misidentified muon background and other background (mainly pions and protons).
The error on the points is the statistical error on the data.

νe CCQE
νe CCnonQE

80

γ bkg (in FGD FV)
γ bkg (out FGD FV)

60µ background
Other background

40

20

0

500 1000 1500 2000 2500 3000 3500 4000 4500 5000

Momentum (MeV/c)
FIG. 10. Reconstructed electron momentum of events selected in the CCnonQE-like selection. The error on the points
is the statistical error on the data, and the simulation is divided into the same categories as Fig. 8.

TABLE IV. Fractions, expected, and observed number of
events for the CCQE and CCnonQE selections.
CCQE selection
CCnonQE selection
Fraction (%) Events Fraction (%) Events
νe CCQE
48.2
132.6
12.7
56.8
νe CCnonQE
19.6
54.1
52.8
234.7
γ bkg (in FGD)
6.4
17.8
19.2
85.3
γ bkg (out FGD)
15.0
41.4
4.5
19.9
µ background
4.0
10.9
6.2
27.6
Other background
6.8
18.8
4.6
20.6
Total simulation
100.0
275.6
100.0
444.9
Data
225
392
Category

1

T2K νe flux

0.9

CCQE+CCnonQE

0.8
0.7

CCQE selection

0.6

CCnonQE selection

0.5
0.4
0.3

Misidentification probability (%)

CCνe efficiency

112

TPC only
1.5

TPC+ECal

1

0.5

0.2
0.1
0
0

0

1000

2000

3000

4000

1000

2000

5000

3000

4000
5000
Momentum (MeV/c)

True neutrino energy (MeV)
FIG. 11. Efficiency of selecting νe CC interactions as a function of true neutrino energy, and the predicted νe flux at
ND280.

V.

CONTROL OF THE BACKGROUNDSThe selection of νe CC interactions is designed to reject two large backgrounds. The first one is due to themuons produced in νµ CC interactions that are the dominant component of the T2K beam. This component isrejected using the PID capabilities of ND280. The second background is due to the conversions of photons in
the FGD producing electrons in the TPC and it cannot
be rejected using PID algorithms.
For the muon background, the combined PID of the
TPC and ECal is vital to reject 99.9% of the muons.
Such a large muon rejection power has been verified using a clean, data driven sample of muons, as describedin Sect. V A below. The photon background is constrained using a selection of photon conversions in the
FGD in which both the electron and the positron are reconstructed in the TPC, as described in Sect. V B below.

A.

Muon misidentification

A data-driven study has been carried out to confirm
the muon rejection power expected by simulation. A
clean sample of muons, produced by neutrino interactions in the sand or in the concrete walls of the ND280
pit, is selected. The selection is done by requiring one
and only one track in a bunch with negative charge crossing all the 3 TPCs and starting at the upstream edge of
the P0D. The TPC PID of the selected track must becompatible with a muon in the TPC upstream of thefirst FGD (TPC1). This requirement does not bias the
sample since the TPC1 PID is not used in the analysis.
Once a clean sample of muons is selected from the data,
the muon misidentification probability is computed as
the ratio between the number of tracks passing the PID
selection and all the selected tracks. The same PID selec-

FIG. 12. Muon misidentification probability as a functionof the muon momentum estimated using a sample of throughgoing muons for the case in which the TPC PID only is used
and for the case in which TPC and ECal PID are combined.

tions described in Sect. IV for the cases with and without
ECal information are used. In Fig. 12 the misidentification probability as a function of the track momentum
measured in the TPC is shown. The muon misidentification probability is below 1% for all the momenta andis much smaller if the TPC and the ECal PID are combined. Compatible results are obtained using simulated
data confirming that the PID performances of ND280 detectors are well understood and well reproduced in thesimulation.

B.

Photon selection

The background, especially at low momentum, is dominated by electrons coming from photon conversions.
Those electrons are background to the νe CC analysis
as they typically come from νµ interactions that occur
inside or outside the FGD producing a π 0 in the final
state which immediately decays into two photons. Oneof the two photons then converts inside the FGD producing an e+ e− pair. If the positron is not reconstructed in
the TPC the event is topologically equivalent to a νe CCinteraction.
This background can be estimated using a selectionof photon conversions in which both the electron andthe positron are reconstructed. A typical example of aphoton conversion with the e+ e− pair reconstructed in
the TPC is shown in Fig. 13.
To select these events, two tracks are required to startin the FGD fiducial volume and to have opposite charge.
The same data quality criteria described in Sect. IV are
also required.
Both tracks have to be electron-like (|δe | < 2 for thenegatively charged track and |δe | < 3 for the positively
charged track), the distance of the starting point of thetwo tracks is required to be within 100 mm, and the

12

Ds ECalDs
ECal

D

TABLE V. Fractions (in %) of the different interaction types
and of the production point for the events selected in thephoton selection and in the photon background to the νe CC
selection.

TPC3
TPC3
TPC3
FGD2
FGD2
FGD2

FGD1
FGD1

BarrelECal
Barrel
ECal
TPC2
TPC1
TPC2
TPC1
TPC2

BarrelECal
ECal
BarrelFIG. 13. Side view of a photon conversion in the FGD1 withan e+ e− pair reconstructed in TPC2.

Entries/(200 MeV/c)reconstructed invariant mass of the pair has to be smaller
than 50 MeV/c2 .
The most powerful requirement among those is the invariant mass cut that alone is able to select a sample
with a 90% purity in electrons. After applying all thecriteria a sample with an electron purity of 99% is selected. The momentum of the electrons in the selected
events is shown in Fig. 14. The purity of photon conversions in the sample is 92% with the remaining events
mainly coming from νe interactions in which the electron
showers in the FGD and produces a positron in the TPC.
The efficiency of this selection with respect to the total
number of photons converting in the FGD is 12%.

νe CCQE

600

γ bkg (in FGD FV)

γ selection
4.1
11.5
0.4
41.7
10.9
31.4
30.6
69.4

The purpose of this selection is to estimate the number of electrons coming from photon conversions enteringthe νe CC selection. In order to do this it is necessary
to ensure that the characteristics of the events selectedin the photon selection and in the photon background inthe νe CC selection are similar. Specifically they need tohave the same origin, they need to be produced in thesame type of neutrino interactions, and the selected lepton in the two cases needs to cover the same phase space.
Tab. V shows the neutrino interactions contributing to
the two samples and the fraction of neutrinos interacting inside or outside the FGD. The fractions of neutrino
interactions are similar while the photon selection has
more events coming from outside of the FGD. This difference is due to the different geometrical acceptance ofthe two samples because the photon selection requires
both tracks to enter the TPC while the νe CC selection
requires only one TPC track.
The lepton momentum and angle, and the neutrinoenergy are in reasonable agreement between the two selections. The strategy used to constrain the backgroundin the extraction of the beam νe component will be described in Sect. VII.

VI.

SYSTEMATIC UNCERTAINTIESµ background
Other background200

0

γ backgroundin νe CC selection
4.3
14.2
0.5
43.5
8.6
28.8
57.0
43.0

νe CCnonQE
γ bkg (out FGD FV)400Interaction(Production point)
CCQE
CC1π
CC Coherent
CC other
NC1π 0NC otherInside FGD FVOutside FGD FV

500 1000 1500 2000 2500 3000 3500 4000 4500 5000

The systematic uncertainties in the measurement of
the beam νe component are separated into three maincategories: detector performance, external backgrounds,
and neutrino flux and cross section uncertainties. The
systematic uncertainties described in this section are usedas prior constraints in the fit to extract the beam νe component that will be described in Sect. VII.

Momentum (MeV/c)
A.
FIG. 14. Reconstructed electron momentum of events selected in the photon selection. The error on the points is thestatistical error on the data, and the simulation is divided
into the same categories as Fig. 8.

Detector systematic uncertainties

The detector systematic uncertainties are computedfor each subdetector used in this analysis: the TPCs, theFGDs and the different ECal modules. Systematic effects

13
related to neutrino interactions outside ND280 producing particles entering the detector are also considered inthis class of systematics.
To determine the effect of the detector systematic uncertainties on the analysis 1000 toy experiments havebeen performed. Each toy experiment has a set of detector systematic parameter values drawn from Gaussian
distributions. The 1000 toy experiments are used to evaluate the covariance of the number of events in bins of reconstructed electron momentum and neutrino flavor foreach selection. Seven bins are included for the CCQElike and CCnonQE-like selection and 3 bins for the γ
selection.

1.

TPC systematic uncertainties

TPC systematic uncertainties are divided into threeclasses: selection efficiency, momentum resolution, andparticle identification.
The efficiency systematic uncertainty arises from thecluster finding, track finding and charge assignment. It
is evaluated using events with a single particle passing
through multiple TPCs, to check for the presence of areconstructed track with the correct charge assignment.
The TPC reconstruction efficiency is determined to be(99.8+0.2−0.4 )% and the charge misassignment probability is
below 1% for tracks with momenta less than 5 GeV/c.
Momentum reconstruction is affected by nonuniformity of the magnetic field and the overall magnetic
field strength. The field inside the magnet has beenmeasured with a Hall probe and non-uniformities arechecked with photoelectrons produced by shining a laser
at the central cathode of the TPC that has small aluminium dots on it. Uncertainty in the overall magnetic
field strength leads to an uncertainty on the momentum
scale of 0.6%. An additional source of systematic
uncertainty is the momentum resolution that has been
determined using tracks crossing multiple TPCs andcomparing their reconstructed momenta. The inverse
momentum resolution is found to be significantly betterin simulations than in data, which could be due tonon-uniformity of the electric field. At momenta larger
than 1.4 GeV/c, the inverse momentum resolution is(30 ± 10)% larger in data than in simulation.
Systematic uncertainties on the TPC particle identification are computed using high-purity samples of electrons, muons and protons. By definition the electron
sample should give a δe distribution that is Gaussianwith mean 0 and width 1. The simulation and the data
have a difference on the mean of the pull distribution of(−0.12 ± 0.12), and a scale of the width of (1.02 ± 0.07).
These are converted into systematic uncertainties on theenergy loss for each true electron track, and all the TPC
PID pulls are recomputed. Similarly, the δp distributionof a proton sample is used to determine the energy loss
systematic uncertainties of true protons. The δµ distribution of the through going muon sample is used for bothmuons and pions, as their masses are similar.

2.

FGD systematic uncertainties

The systematic uncertainties related to the FGDs arise
from potential mismodelling of the track-finding efficiency, the efficiency with which TPC and FGD tracks
are matched, the Michel electron tagging efficiency, secondary pion interactions, and the FGD mass.
The efficiency with which FGD tracks are reconstructed is computed for FGD1, as the analysis uses isolated FGD reconstruction for FGD1 only. To determine
the efficiency, samples of stopping proton-like tracks in
FGD1 are used and differences between the data and thesimulation are evaluated for different angles, being 3%
for forward-going tracks and rising to 21% for high angle
tracks. Additional studies have been done for multiple
tracks in the FGD by using hybrid samples in which simulated particles (pions or protons) are injected into dataand simulated events finding differences between dataand simulation of 3% (4%) for pions (protons).
The TPC-FGD matching efficiency is studied using asample of through-going particles, in which the presenceof a track in the TPC upstream and downstream implies
that a track should be seen in the FGD. The efficiency isfound to be 99.9%. The matching efficiency has also beenchecked for electrons using samples of photon conversions
in the FGD in which the e+ e− tracks were not required
to start in the FGD.
The Michel electron tagging efficiency is studied usinga sample of cosmic rays which stop in FGD1. The particles must have a range compatible with being a muonwith the momentum as reconstructed in the TPC. The
Michel tagging efficiency is found to be about 60%, depending on the beam bunch of the primary neutrino interaction.
There is an uncertainty in the modeling of pion reinteractions (where a pion created in an interaction is ejectedfrom the nucleus and interacts with another nucleus in
the detector). Differences between external pion interaction data [40] and GEANT4 simulation are evaluated.
The external data are extrapolated to cover the whole
momentum region relevant for T2K and a correction
weight is calculated for each event, along with an uncertainty based on the error of the extrapolated data. Thissystematic uncertainty can only migrate events between
the CCQE-like and the CCnonQE-like selections and theeffect on this analysis is found to be negligible.
The uncertainty on the mass of the FGDs—and thus
on the number of target nucleons—is computed using the
known density and size of the individual components, andtheir uncertainties. The overall uncertainty on the FGD
mass is 0.67%.

14
3.

ECal systematic uncertainties

ECal systematic uncertainties are computed for theparticle identification, the energy resolution and scale,and the efficiency with which ECal objects are reconstructed and matched to TPC tracks.
Uncertainties in RMIP/EM are calculated using highpurity samples of electrons and muons. The efficiencyof the RMIP/EM > 0 requirement is calculated for data
and for the simulation, and the difference is taken as thesystematic uncertainty. The systematic uncertainty forselecting electrons is 2.1% in the DsECal and 2.9% in the
Barrel, and the uncertainty for rejecting muons is 0.6%
in the DsECal and 0.7% in the Barrel ECal.
EEM systematic uncertainties are computed using botha high-purity sample of electrons from T2K data andtest beam data taken at CERN before the DsECal wasshipped to Japan. The reconstructed EEM is comparedto the known momentum, either as measured by the TPC
for the in-situ sample, or as defined in the test beam. The
uncertainty on the energy scale is 6% and the uncertainty
on the energy resolution is 15%.
A combined systematic uncertainty is computed for theefficiency of reconstructing an ECal object and matching it to a TPC track. A high-purity sample of electrons
that appear to enter the ECal (by extrapolating the TPC
track) is used. The uncertainty is 1.6% for tracks entering the DsECal, and 3.4% for tracks entering the Barrel
ECal.

2.

Systematic uncertainties from neutrino interactions
outside ND280

The standard ND280 simulation only includes neutrino
interactions inside the magnet volume. Neutrino interactions outside this volume can affect the analysis in two
different ways. First, the particles produced in these interactions can enter the ND280 volume, interact in an
FGD, and be selected as signal. A separate simulation ofneutrino interactions outside the ND280 magnet is used
to estimate the expected number of extra signal eventsand is found to be negligible. Particles produced outside
ND280 can also enter in one of the ND280 sub-detectors
in the same beam bunch in which a true νe signal interaction occurs in an FGD. These particles can then cause
an event to be vetoed, reducing the selection efficiency
in data. The probability of this occurring is calculated
separately for each veto cut and for each T2K run, as it
depends on the beam intensity. The largest correction is(2.3 ± 0.5)% for the ECal veto cut in Run IV.

C.

Flux and cross section systematic uncertainties

For the T2K oscillation analyses, the flux and the crosssection systematic uncertainties described in Sect. II are
evaluated using a selection of νµ CC interactions in
ND280 [3]. Events with a muon candidate produced in
FGD1 and entering the downstream TPC are divided
into the following samples:• CC0π sample in which there are no tracks compatible with a pion. Most of the events arise from
CCQE interactions;

B.

External background systematic uncertainties

1.

Systematic uncertainties from neutrino interactions
outside the FGD FVIn the νe CC selection there is a large background component coming from νµ interactions outside of the FGD.
Differences between data and simulation in this component might arise from mismodelling of the π 0 production
and in the description of the material and efficiencies outside of the FGD. The fit to the ND280 νµ CC samples
cannot constrain this component as < 5% of the events
selected in that analysis come from outside of the FGD.
In this analysis, the majority of the selected events
arising from neutrino interactions outside of the FGD are
due to photon conversion in the FGD and this component
is well measured by the photon selection. The remainderof this background is due to other charged particles (pions
or protons) and this component cannot be measured by
the photon selection. The systematic uncertainty prior
to the fit for each of the two components is set to 30%.

• CC1π sample in which there is one reconstructed
track (in the TPC or in the FGD) compatible with apion or there is a delayed energy deposit consistent
with a stopping pion. It is mainly composed of CC
interactions with resonant pion production;• CC-other sample, for all other topologies. Most
events are from deep inelastic scattering and multipion production.
These three samples are fit to evaluate the νµ flux andcross section parameters and their uncertainties. The
oscillation analyses also use these samples to evaluate theνe flux parameters, which is possible because νµ and νearise from the same parent particles. The cross sectionsfor νe and νµ interactions are assumed to be the same.
The muon momentum distributions for the CC0π andCC1π samples are shown in Fig. 15 together with theprediction before and after the fit.
The systematic parameters and their uncertainties obtained from the fit to the ND280 νµ CC data are shownin Tab. VI. The effect of those systematic uncertainties
on the evaluation of the beam νe component is 6%, aswill be shown in Sect. VIII. Without using the ND280 νµData/Sim. Events/(125 MeV/c)

15

3500
3000
2500
2000
1500
1000
500
0
1.2
1
0.8
0

Prediction before ND ν µ constraint
Prediction after ND ν µ constraint
Data

Systematic

Muon momentum (MeV/c)5001000 1500 2000 2500 3000 3500 4000 4500 >5000

Data/Sim. Events/(125 MeV/c)

Muon momentum (MeV/c)

500

Prediction before ND ν µ constraint

400

Prediction after ND ν µ constraint

300

Data

200
100
0
1.2
1
0.8
0

Muon momentum (MeV/c)5001000 1500 2000 2500 3000 3500 4000 4500 >5000

Muon momentum (MeV/c)

FIG. 15. Reconstructed momentum distribution for events
selected in the ND280 νµ CC analysis in the CC0π sample(top) and in the CC1π sample (bottom) before and after the
fit to evaluate flux and cross section parameters. The last bins
contain all the events with reconstructed muon momentum
larger than 5 GeV/c. The error on the points is the statisticalerror on the data.

data the uncertainty on the beam νe prediction is larger
than 20%.
In the analysis described in this paper, systematic uncertainties of final state interactions are not evaluatedfrom the ND280 νµ CC samples; their effect is evaluatedin bins of reconstructed electron momentum using thepion scattering data described in Sect. II B.

D.

TABLE VI. Summary of the values and errors of the systematic parameters used as priors for the measurement describedin this paper. The values in squared brackets show the rangeof variation for systematic uncertainties with more than one
parameter as a function of neutrino energy.

Summary of the systematic uncertainties

The 60 parameters included in this analysis are shownin Tab. VI. The variance due to limited statistics in thesimulation is added to the diagonal of the detector and
FSI parameter covariance matrix.

Central Uncertainty
NumberValueof parametersνµ -flux[0.93-1.05] [0.07-0.08]
11
νe -flux[0.95-1.02] [0.07-0.09]7ν̄µ -flux[0.99-1.03] [0.09-0.14]
5ν̄e -flux[0.95-1.01] [0.08-0.17]
2
QE
MA
[GeV]
1.025
0.059
1
xQE
[0.85-0.97] [0.07-0.11]
3
1,2,3
xSF
0.240
0.129
1
pF [MeV/c]266
111
Eb [MeV]
30.9
5.2
1
RES
MA
[GeV]
0.797
0.056
1
xCC1π
[1.12-1.26] [0.16-0.17]
2
1,2
0
xNC1π
1.410
0.218
1
xNC other
1.135
0.248
1
xπ−less
0.206
0.085
1
xCC coh.
0.449
0.164
1
xCC other (GeV)
0.225
0.285
1
σν̄ /σν1
0.4
1
Detector+FSI
1[0.07-0.19]
17
Out FGD FV e−
1
0.3
1
Out FGD FV oth.
1
0.3
1
Total
60

VII.
MEASUREMENT OF THE ELECTRONNEUTRINO COMPONENT OF THE BEAM

In order to extract the beam νe component, a likelihood fit of the selected distributions (CCQE-like,
CCnonQE-like and γ samples) has been performed. To
account for systematic uncertainties, 60 nuisance parameters are included in the likelihood function. An additional term, R(νe ), is included that scales the expected
number of events arising from νe interactions. A second
approach introduces two additional terms, R(νe (µ)) andR(νe (K)), which separately scale the expected numberof νe events arising from muon and kaon decays respectively.
It is important to notice that in this analysis the crosssection parameters shown in Tab. VI have been evaluatedfrom the ND280 νµ CC samples assuming that the effective cross section parameters for νµ and νe interactions
are the same. A measurement of the νe CC interactions
at ND280 is important to put experimental constraints
on this assumption that is poorly constrained from experimental data [11].
The likelihood ratio applied to the momentum distributions of the νe CCQE-like, νe CCnonQE-like and γ

16samples is:

TABLE VII.
Number of events for CCQE-like andCCnonQE-like selections before and after the fit to the ND280
νµ CC samples.

−2 ln λ(R; f~) = − 2 ln λνe CCQE (R; f~)− 2 ln λνe CCnonQE (R; f~)− 2 ln λγ (R; f~)Category+ (f~ − f~0 )T V −1 (f~ − f~0 )(1)
where −2 ln λi is the likelihood ratio for each sample andthe last term is the penalty term that constrains the systematic nuisance parameters. f~0 is the vector of central
values for the systematic parameters shown in Tab. VI,
f~ is the vector of nuisance parameters and V is the covariance matrix that takes into account the correlations
among the systematics parameters.
The likelihood function is calculated in 18 bins of reconstructed electron momentum from 200 MeV/c to 10
GeV/c for each selection, with a 100 MeV/c bin width
up to 1 GeV/c and a wider binning at higher momenta.
The predicted number of events in each bin depends
on the free parameter R(νe ) and on the 60 systematicparameters according to the formula:niexp (R; f~) =Nidata X
Np.o.t.
jffjlux fx(norm.)·
sim.
Np.o.t.
jjjfx(resp.)fdet(pi ) × R(νe )(2)

The sum j runs over the events with momentum compatible with the i-th momentum bin pi , with Ni total
data
sim.
events in that bin. Np.o.t.
and Np.o.t.
are the number of
p.o.t. for data and simulation. ff lux multiply the flux
prediction in bins of true neutrino energy. fdet multiply
the expected number of events in bins of electron reconstructed momentum. The cross section parameters aretreated in two ways: fx(norm.) multiply the cross section
normalization for a given true neutrino energy and interaction model while fx(resp.) are pre-calculated response
functions whose value for the nominal parameter settingsof Tab. VI is one. The reason for which they are treatedin this way is that they can have a non-linear dependency
on the cross section parameters. The prediction for thenumber of selected events before and after the application of the detector systematic and of the flux and crosssection parameters obtained from the fit to the ND280
νµ CC samples is shown in Tab. VII.
For each of the three samples k the likelihood ratio is:−2 ln λk (R; f~) = 2×

18
X

νe from µνe from K
νµ (in FV)
νµ (OOFV)
Total
Data

CCQE selection
Before
After
61.2
52.7
125.9
108.2
30.4
31.7
58.1
67.0
275.5
259.6
225

VIII.

CCnonQE selection
Before
After
38.9
34.9
253.6
221.0
124.9
132.4
27.5
26.8
444.9
415.1
392

RESULTSThe result obtained for the parameter R(νe ) is:R(νe ) = 1.01 ± 0.06(stat.) ± 0.06(f lux ⊕ x.sec)± 0.05(det. ⊕ F SI) = 1.01 ± 0.10

(4)where the first term represents the statistical error,
the second term represents the systematic uncertainties
related to the flux and to the cross section models, andthe last term represents the detector systematics and the
FSI uncertainties.
This result indicates that the beam νe component measured in the data is consistent with the expectation forthis component after the constraint from the ND280 νµCC sample. This is a key validation of the strategy followed by T2K to constrain the flux and cross section
parameters for all the neutrino oscillation analyses.
The second measurement is performed by fitting independently the νe originating from muons and from kaons.
As is shown in Fig. 1 the νe from muons mainly populate the low energy region while the νe from kaons are
dominant at high momenta.
Given the larger efficiency of the analysis at high energy (shown in Fig. 11) there are three times as many selected events from kaon decay as from muon decay. Theνe from muon decay mainly populate the CCQE-like selection in its low momentum region. The results obtained
for the two components are:R(νe (µ)) = 0.68 ± 0.24(stat.) ± 0.11(f lux ⊕ x.sec)± 0.14(det. ⊕ F SI) = 0.68 ± 0.30 (5)and{ niexp (R; f~) − nidata

i=1


o
+nidata ln nidata /niexp (R; f~)R(νe (K)) = 1.10 ± 0.08(stat.) ± 0.09(f lux ⊕ x.sec)± 0.06(det. ⊕ F SI) = 1.10 ± 0.14 (6)(3)
where niexp and nidata are the number of expected andobserved events in the i-th momentum bin.

Due to the small amount of νe coming from muons,
the uncertainty on the measurement of this component isstill statistically limited and will be improved when moreνe from µνe from K
γ bkg (in FGD FV)
γ bkg (out FGD FV)µ background
Other background

30
25
20
15
10
5
0

500

1000

1500

2000

2500

3000

3500

Momentum (MeV/c)
Entries/(100 MeV/c)data is available. With the present statistics both numbers are compatible with unity showing no discrepancies
between the predicted and the observed beam νe component. The larger systematic uncertainty for R(νe (µ)) isdue to the fact that the detector, flux and cross-section
systematic uncertainties are larger at low momenta. The
distribution of the reconstructed electron momentum forthe three samples after the fit are shown in Fig. 16.
As far as the nuisance parameters are concerned, thefitted values are in good agreement with the expectations. The out of FGD electron component is reducedin the fit by 0.64 ± 0.10, compatible with the prior systematic uncertainty of 30%. This reduction might point
to the fact that the simulation does not properly reproduce the amount of π 0 produced in neutrino interactionsin the materials surrounding the ND280 tracker region.
Those interactions are mainly high energy deep inelastic
scattering events for which the π 0 multiplicity is not wellmeasured. This reduction does not have a large impact
on the measurements presented here because of the presence of the photon conversion sample used to evaluate
this background.

Entries/(100 MeV/c)

17

νe from µνe from K
γ bkg (in FGD FV)
γ bkg (out FGD FV)µ background
Other background

40
35
30
25
20
15

IX.

10

SUMMARY

5
0

500

1000

1500

2000

2500

3000

3500

Momentum (MeV/c)
Entries/(100 MeV/c)

In summary, a selection of νe CC interactions has been
performed using the T2K off-axis near detector combining the PID capabilities of the TPC and ECal. The combination of these two detectors allows the selection ofa clean sample of electrons with a purity of 92% and amuon misidentification probability smaller than 1%.
The selected sample is mainly composed of electrons
coming from νe CC interactions but a non negligible component comes from photon conversions in the FGD. Thisbackground is constrained in the analysis using a sample
of e+ e− pairs coming from photon conversions in which
both outgoing particles are reconstructed in the TPC.
To extract the beam νe component from the data alikelihood fit is performed. The expected number of νeinteractions is predicted by the same model used for theT2K oscillation analyses where the neutrino fluxes andthe neutrino cross sections are evaluated by the νµ CC
samples selected at ND280.
The observed number of events is in good agreementwith the prediction, providing a direct confirmation ofthis method. This measurement is still statistically limited but when additional data is collected it will be possible to further improve the measurement of the intrinsic
νe component in the T2K beam and perform measurements of νe cross sections and of the νe /νµ cross section
differences that have not been measured at T2K energies.
This measurement is particularly important because
the intrinsic νe component is the main background for
all the proposed long-baseline neutrino oscillation experiments aiming to measure CP violation in the leptonic
sector. In this paper it is shown that, although the component is small, it is possible to measure it with a prop-

νe from µνe from K
γ bkg (in FGD FV)
γ bkg (out FGD FV)µ background
Other background

350
300
250
200
150
100
50
0

500

1000

1500

2000

2500

3000

3500

Momentum (MeV/c)

FIG. 16. Reconstructed electron momentum distribution for
the events selected in the three samples after the fit to extract the beam νe component: CCQE-like selection (top),
CCnonQE-like selection (center) and γ selection (bottom).
The last bin contains all the events with reconstructed electron momentum larger than 3.5 GeV/c. The signal is divided
into νe produced by muon and kaon decays. The backgroundis divided into the same categories as Fig. 8. The error on the
points is the statistical error on the data.

erly designed near detector.

18

We thank the J-PARC staff for superb accelerator performance and the CERN NA61 collaboration for providing valuable particle production data. We acknowledge
the support of MEXT, Japan; NSERC, NRC and CFI,
Canada; CEA and CNRS/IN2P3, France; DFG, Germany; INFN, Italy; Ministry of Science and Higher Education, Poland; RAS, RFBR and MES, Russia; MICINN

and CPAN, Spain; SNSF and SER, Switzerland; STFC,
U.K.; and DOE, U.S.A. We also thank CERN for the
UA1/NOMAD magnet, DESY for the HERA-B magnet
mover system, NII for SINET4, the WestGrid and SciNet
consortia in Compute Canada, and GridPP, UK. In addition participation of individual researchers and institutions has been further supported by funds from: ERC(FP7), EU; JSPS, Japan; Royal Society, UK; DOE Early
Career program, U.S.A.

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