A Search for Electron Neutrino Appearance at the Delta m**2 ~ 1 eV**2
  Scale
A Search for Electron Neutrino Appearance at the ∆m2 ∼ 1 eV2 Scale
A. A. Aguilar-Arevalo5, A. O. Bazarko12, S. J. Brice7, B. C. Brown7, L. Bugel5, J. Cao11, L. Coney5,
J. M. Conrad5, D. C. Cox8, A. Curioni16, Z. Djurcic5, D. A. Finley7, B. T. Fleming16, R. Ford7, F. G. Garcia7,
G. T. Garvey9, C. Green7,9, J. A. Green8,9, T. L. Hart4, E. Hawker15, R. Imlay10, R. A. Johnson3, P. Kasper7,
T. Katori8, T. Kobilarcik7, I. Kourbanis7, S. Koutsoliotas2, E. M. Laird12, J. M. Link14, Y. Liu11, Y. Liu1,
W. C. Louis9, K. B. M. Mahn5, W. Marsh7, P. S. Martin7, G. McGregor9, W. Metcalf10, P. D. Meyers12,
F. Mills7, G. B. Mills9, J. Monroe5, C. D. Moore7, R. H. Nelson4, P. Nienaber13, S. Ouedraogo10,
R. B. Patterson12, D. Perevalov1, C. C. Polly8, E. Prebys7, J. L. Raaf3, H. Ray9, B. P. Roe11, A. D. Russell7,
V. Sandberg9, R. Schirato9, D. Schmitz5, M. H. Shaevitz5, F. C. Shoemaker12, D. Smith6, M. Sorel5,
P. Spentzouris7, I. Stancu1, R. J. Stefanski7, M. Sung10, H. A. Tanaka12, R. Tayloe8, M. Tzanov4,
R. Van de Water9, M. O. Wascko10, D. H. White9, M. J. Wilking4, H. J. Yang11, G. P. Zeller5, E. D. Zimmerman4
(The MiniBooNE Collaboration)
1University of Alabama; Tuscaloosa, AL 35487
2Bucknell University; Lewisburg, PA 17837
3University of Cincinnati; Cincinnati, OH 45221
4University of Colorado; Boulder, CO 80309
5Columbia University; New York, NY 10027
6Embry Riddle Aeronautical University; Prescott, AZ 86301
7Fermi National Accelerator Laboratory; Batavia, IL 60510
8Indiana University; Bloomington, IN 47405
9Los Alamos National Laboratory; Los Alamos, NM 87545
10Louisiana State University; Baton Rouge, LA 70803
11University of Michigan; Ann Arbor, MI 48109
12Princeton University; Princeton, NJ 08544
13Saint Mary’s University of Minnesota; Winona, MN 55987
14Virginia Polytechnic Institute & State University; Blacksburg, VA 24061
15Western Illinois University; Macomb, IL 61455
16Yale University; New Haven, CT 06520
(Dated: February 1, 2008)
The MiniBooNE Collaboration reports first results of a search for νe appearance in a νµ beam.
With two largely independent analyses, we observe no significant excess of events above background
for reconstructed neutrino energies above 475 MeV. The data are consistent with no oscillations
within a two-neutrino appearance-only oscillation model.
This Letter reports the initial results from a search for
νµ → νe oscillations by the MiniBooNE Collaboration.
MiniBooNE was motivated by the result from the Liquid
Scintillator Neutrino Detector (LSND) experiment [1],
which has presented evidence for ν̄µ → ν̄e oscillations at
the ∆m2 ∼ 1 eV2 scale. Although the Karlsruhe Ruther-
ford Medium Energy Neutrino Experiment (KARMEN)
observed no evidence for neutrino oscillations [2], a joint
analysis [3] showed compatibility at 64% CL. Evidence
for neutrino oscillations also comes from solar-neutrino
[4, 5, 6, 7, 8] and reactor-antineutrino experiments [9],
which have observed νe disappearance at ∆m
∼ 8×10−5
eV2, and atmospheric-neutrino [10, 11, 12, 13] and long-
baseline accelerator-neutrino experiments [14, 15], which
have observed νµ disappearance at ∆m
∼ 3×10−3 eV2.
If all three phenomena are caused by neutrino oscilla-
tions, these three ∆m2 scales cannot be accommodated
in an extension of the Standard Model that allows only
three neutrino mass eigenstates. An explanation of all
three mass scales with neutrino oscillations requires the
addition of one or more sterile neutrinos [16] or further
extensions of the Standard Model (e.g., [17]).
The analysis of the MiniBooNE neutrino data pre-
sented here is performed within a two neutrino
appearance-only νµ → νe oscillation model which uses
νµ events to constrain the predicted νe rate. Other than
oscillations between these two species, we assume no ef-
fects beyond the Standard Model.
The experiment uses the Fermilab Booster neutrino
beam, which is produced from 8 GeV protons incident
on a 71-cm-long by 1-cm-diameter beryllium target. The
proton beam typically has 4 × 1012 protons per ∼ 1.6
µs beam spill at a rate of 4 Hz. The number of pro-
tons on target per spill is measured by two toroids in the
beamline. The target is located inside a focusing horn,
which produces a toroidal magnetic field that is pulsed
in time with the beam at a peak current of 174 kA. Posi-
tively charged pions and kaons, focused by the horn, pass
through a 60-cm-diameter collimator and can decay in a
50-m-long tunnel, which is 91 cm in radius and filled with
http://arXiv.org/abs/0704.1500v3
air at atmospheric pressure.
The center of the detector is 541 m from the front
of the beryllium target and 1.9 m above the center of
the neutrino beam. There is about 3 m of dirt over-
burden above the detector, which is a spherical tank of
inner radius 610 cm filled with 800 tons of pure mineral
oil (CH2) with a density of 0.86 g/cm
3 and an index of
refraction of 1.47. The light attenuation length in the
mineral oil increases with wavelength from a few cm at
280 nm to over 20 m at 400 nm. Charged particles pass-
ing through the oil can emit both directional Cherenkov
light and isotropic scintillation light. An optical bar-
rier separates the detector into two regions, an inner vol-
ume with a radius of 575 cm and an outer volume 35 cm
thick. The optical barrier supports 1280 equally-spaced
inward-facing 8-inch photomultiplier tubes (PMTs), pro-
viding 10% photocathode coverage. An additional 240
tubes are mounted in the outer volume, which acts as
a veto shield, detecting particles entering or leaving the
detector. Two types of PMT are used: 1198 Hamamatsu
model R1408 with 9 stages and 322 Hamamatsu model
R5912 with 10 stages. Approximately 98% of the PMTs
have worked well throughout the data taking period.
The experiment triggers on every beam spill, with all
PMT hits recorded for a 19.2 µs window beginning 4.4 µs
before the spill. Other triggers include a random trig-
ger for beam-unrelated measurements, a laser-calibration
trigger, cosmic-muon triggers, and a trigger to record
neutrino-induced events from the nearby Neutrinos at the
Main Injector (NuMI) beamline [18]. The detector elec-
tronics, refurbished from LSND [19], digitize the times
and integrated charges of PMT hits. PMT hit thresholds
are ∼ 0.1 photoelectrons (PE); the single-PE time reso-
lutions achieved by this system are ∼ 1.7 ns and ∼ 1.2
ns for the two types of PMTs. One PE corresponds to
∼0.2 MeV of electron energy. Laser calibration, consist-
ing of optical fibers that run from the laser to dispersion
flasks inside the tank, is run continuously at 3.33 Hz to
determine PMT gains and time offsets. Averaged over
the entire run, the beam-on livetime of the experiment is
greater than 98%.
The νµ energy spectrum peaks at 700 MeV and extends
to approximately 3000 MeV. Integrated over the neutrino
flux, interactions in MiniBooNE are mostly charged-
current quasi-elastic (CCQE) scattering (39%), neutral-
current (NC) elastic scattering (16%), charged-current
(CC) single pion production (29%), and NC single pion
production (12%). Multi-pion and deep-inelastic scatter-
ing contributions are < 5%. NC elastic scattering, with
only a recoil nucleon and a neutrino in the final state,
typically produces relatively little light in the detector
and contributes only 3 events to the final background
estimate.
Table I shows the estimated number of events with
reconstructed neutrino energy, EQEν , between 475 MeV
and 1250 MeV after the complete event selection from
TABLE I: The estimated number of events with systematic
error in the 475 < EQEν < 1250 MeV energy range from all of
the significant backgrounds, together with the estimated num-
ber of signal events for 0.26% νµ → νe transmutation, after
the complete event selection.
Process Number of Events
νµ CCQE 10 ± 2
νµe → νµe 7 ± 2
Miscellaneous νµ Events 13 ± 5
NC π0 62 ± 10
NC ∆ → Nγ 20 ± 4
NC Coherent & Radiative γ < 1
Dirt Events 17 ± 3
νe from µ Decay 132 ± 10
νe from K
+ Decay 71 ± 26
νe from K
L Decay 23 ± 7
νe from π Decay 3 ± 1
Total Background 358 ± 35
0.26% νµ → νe 163 ± 21
all of the significant backgrounds, where EQEν is deter-
mined from the reconstructed lepton energy and angle
with respect to the known neutrino direction. The back-
ground estimate includes antineutrino events, which rep-
resent < 2% of the total. Also shown is the estimated
number of νe CCQE signal events for the LSND central
expectation of 0.26% νµ → νe transmutation. Studies
of random triggers have established that no significant
backgrounds survive the analysis cuts other than those
due to beam related neutrinos, which can be divided into
either νµ-induced or νe-induced backgrounds. The small
fraction of νe from µ, K, and π decay in the beamline
gives a background that is indistinguishable from oscil-
lations except for the energy spectrum. CC νµ events
are distinguished from νe events by the distinct patterns
of Cherenkov and scintillation light for muons and elec-
trons, as well as by the observation of a delayed electron
from the muon decay, which is observed > 80% of the
time from νµ CCQE events. NC π
0 events with only a
single electromagnetic shower reconstructed are the main
νµ-induced background, followed by radiative ∆ decays
giving a single photon, and then neutrino interactions in
the dirt surrounding the detector, which can mimic a sig-
nal if a single photon, mostly from π0 decay, penetrates
the veto and converts in the fiducial volume.
We use PMT charge and time information in the 19.2
µs window to reconstruct neutrino interactions and iden-
tify the product particles. This time window is defined
as an “event” and is divided into “subevents”, collec-
tions of PMT hits clustered in time within ∼ 100 ns. A
νµ CCQE event with a muon stopping within the tank
may have two subevents: the first subevent from par-
ticles produced at the neutrino interaction, the second
from the muon decay to an electron. A νe CCQE event
has a single subevent.
To ensure stable, well-targeted beam at full horn cur-
rent, it is required that the two monitoring toroids agree
to within 5%, the estimated transverse containment of
the beam in the target be greater than 95%, and the
measured horn current be within 3% of its nominal value.
The event time at the detector must be consistent with
the beam delivery time (both determined by GPS), and
the event must pass a number of data integrity checks.
The beam quality requirements reject 0.7% of the events,
while the detector time and quality requirements remove
a further 1.8%, with the remaining data corresponding
to (5.58 ± 0.12)× 1020 protons on target.
Next, events with exactly one subevent (as expected
for νe CCQE events) are selected. By requiring that the
subevent have fewer than 6 hits in the veto and more
than 200 hits in the main tank (above the muon-decay
electron endpoint), entering cosmic-ray muons and their
associated decay electrons are eliminated. The average
time of hits in the subevent is required to be within the
beam time window of 4-7 µs. These cuts yield a cosmic
ray rejection of greater than 1000:1.
After these initial cuts, the surviving events are re-
constructed under four hypotheses: a single electron-like
Cherenkov ring, a single muon-like ring, two photon-like
rings with unconstrained kinematics, and two photon-
like rings with Mγγ = mπ0 (see Fig. 1). Photon-like
rings are assumed to be identical to electrons, but al-
lowed to be independently displaced from the neutrino
interaction vertex. The reconstruction uses a detailed
model of extended-track light production and propaga-
tion in the tank to predict the charge and time of hits on
each PMT. Event parameters are varied to maximize the
likelihood of the observed hits, yielding the vertex posi-
tion and time of the event and the direction, energy, and,
for photons, the conversion distance of the ring(s). For νe
events, the event vertex, direction, and energy are recon-
structed on average with resolutions of 22 cm, 2.8◦, and
11%, respectively, while NC π0 events are reconstructed
with a π0 mass resolution of 20 MeV/c2.
The final analysis cuts were designed to isolate a sam-
ple of νe-induced events that were primarily CCQE. The
only data that were used in developing the analysis were
samples that Monte Carlo (MC) simulation had indicated
could not contain a significant number of νµ → νe oscil-
lation events. We require that the electron-hypothesis
event vertex and muon-hypothesis track endpoint occur
at radii < 500 cm and < 488 cm, respectively, to en-
sure good event reconstruction and efficiency for pos-
sible muon decay electrons. We require visible energy
Evis > 140 MeV. We then apply particle identification
(PID) cuts to reject muon and π0 events. These are Evis-
dependent cuts on log(Le/Lµ), log(Le/Lπ0), and Mγγ,
where Le, Lµ, and Lπ0 are the likelihoods for each event
maximized under the electron 1-ring, muon 1-ring, and
fixed-mass 2-ring fits, and Mγγ is from the unconstrained
two-ring fit. These also enhance the fraction of CCQE
FIG. 1: Events in MiniBooNE are reconstructed as either a
muon event, an electron event, or a π0 event.
TABLE II: The observed number of νe CCQE candidate
events and the efficiency for νµ → νe CCQE oscillation events
after each cut is applied sequentially.
Selection #Events νe CCQE Efficiency
Cosmic Ray Cuts 109,590 100%
Fiducial Volume Cuts 68,143 55.2 ± 1.9%
PID Cuts 2037 30.6 ± 1.4%
475 < EQEν < 1250 MeV 380 20.3 ± 0.9%
events among the surviving electron candidates. Table II
shows the observed number of νe CCQE candidate events
and the efficiency for νµ → νe CCQE oscillation events
after each cut is applied sequentially. A total of 380 data
events remains after the complete selection.
Detailed Monte Carlo simulations of the beam and de-
tector were used to make initial estimates of the flux and
detector efficiencies. The Booster neutrino beam flux at
the detector is modeled using a GEANT4-based simu-
lation [20] of the beamline geometry. Pion and kaon
production in the target is parametrized [21] based on
a global fit to proton-beryllium particle production data
[22]. The kaon flux has been cross-checked with high-
energy events above 1250 MeV and with an off-axis muon
spectrometer that viewed the secondary beamline from
an angle of 7◦. This detector determined the flux of
muons with high transverse momentum, which originate
mostly from kaon decays, to be consistent with the MC
predictions.
The v3 NUANCE [23] event generator simulates neu-
trino interactions in mineral oil. Modifications are made
to NUANCE which include adjustment of the axial form
factor of the nucleon for quasi-elastic scattering, the Pauli
blocking model, and coherent pion production cross sec-
tions based on fits to MiniBooNE νµ data [24]. In addi-
tion, the final state interaction model has been tuned to
reproduce external pion-carbon rescattering data [25], an
explicit model of nuclear de-excitation photon emission
for carbon has been added [26], and the angular correla-
tions for ∆ decay are modified to be in accord with the
model of Rein and Sehgal [27].
Particles from NUANCE-generated final states are
propagated through a GEANT3-based simulation [28]
of the detector, with the subsequent decays, strong,
and electroweak interactions in the detector medium in-
cluded. Most particular to MiniBooNE, the emission of
optical and near-UV photons via Cherenkov radiation
and scintillation is simulated, with each photon individ-
ually tracked, undergoing scattering, fluorescence, and
reflection, until it is absorbed [29]. Small-sample mea-
surements of transmission, fluorescence, and scattering
are used in the model. Muon decay electrons are used
to calibrate both the light propagation in the detector
and the energy scale. The amount of scintillation light
is constrained from NC elastic scattering events. The
charge and time response of the electronics is simulated,
and from this point onward, data and MC calculations
are treated identically by the analysis programs.
All of the major νµ-induced backgrounds are con-
strained by our measurements outside the signal region.
The inclusive CC background is verified by comparing
data to MC calculations for events with two subevents,
where the second subevent has < 200 tank hits and is
consistent with a muon-decay electron. As the probabil-
ity for µ− capture in the oil is 8%, there are an order
of magnitude more CC inclusive scattering events with
two subevents than with only one subevent, so that this
background is well checked. These data events are also
modified by moving the hits of the second subevent ear-
lier in time to model early, inseparable decays which can
look more like an electron.
To determine the NC π0 background, π0 rates are mea-
sured in bins of momentum by counting events in the γγ
mass peak. The MC simulation is used to correct the
production rate for inefficiency, background and resolu-
tion (corrections are ∼ 10%). To match the data angular
distribution, the π0 candidates are fit to MC templates
(in mass and angle) for resonant and coherent production
(generated using the model of Rein and Sehgal [27]) as
well as a template for non-π0 background events. The
fitted parameters are used to reweight π0 from the MC
calculations and to constrain the ∆ → Nγ rate, which
has a branching ratio at the peak of the ∆ resonance of
0.56%. NC coherent γ background [30] and NC radiative
γ background [31] are both estimated to be negligible.
The background from interactions in the dirt surround-
ing the detector is measured from a sample of inward-
pointing events inside the tank at high radius.
A sample of ∼105 candidate νµ CCQE events is ob-
tained by requiring a µ-decay electron with a recon-
structed vertex consistent with the estimated endpoint of
the parent muon’s track (60% efficiency). The observed
rate of these νµ CCQE events is used to correct the MC
predictions for νe signal events, νµ CC backgrounds, and
νe from µ backgrounds (which share their π parentage
with the νµ CCQE events). These constraints increase
the event normalization by 32% and greatly reduce the
rate uncertainties on these three components of the final
analysis sample.
Systematic errors are associated with neutrino fluxes,
the detector model, and neutrino cross sections. The
neutrino flux systematic errors are determined from the
uncertainties of particle production measurements, the
detector model systematic errors are mostly determined
from fits to MiniBooNE data, and the neutrino cross sec-
tion systematic errors are determined from MiniBooNE
data as well as from external sources, both experimen-
tal and theoretical. These groups of errors are taken to
be independent, and, for each, an individual error ma-
trix is formed that includes the full correlation among
the systematic parameters. This is mapped to a matrix
describing the correlated errors in predicted background
plus possible signal in eight νe E
ν bins. The final co-
variance matrix for all sources of uncertainty (statistical
and systematic) is the sum of the individual error ma-
trices. The signal extraction is performed by computing
the χ2 comparing data to predicted background plus a
(sin2(2θ), ∆m2)-determined contribution from νµ → νe
two-neutrino oscillations in the eight EQEν bins and min-
imizing with respect to these two oscillation parameters
across their physical range.
With the analysis cuts set, a signal-blind test of data-
MC agreement in the signal region was performed. The
full two-neutrino oscillation fit was done in the range
300 < EQEν < 3000 MeV and, with no information on
the fit parameters revealed, the sum of predicted back-
ground and simulated best-fit signal was compared to
data in several variables, returning only the χ2. While
agreement was good in most of the comparisons, the Evis
spectrum had a χ2 probability of only 1%. This triggered
further investigation of the backgrounds, focusing on the
lowest energies where νµ-induced backgrounds, some of
which are difficult to model, are large. As part of this
study, one more piece of information from the signal re-
gion was released: unsigned bin-by-bin fractional discrep-
ancies in the Evis spectrum. While ambiguous, these re-
inforced suspicions about the low-energy region. Though
we found no specific problems with the background es-
timates, it was found that raising the minimum EQEν of
the fit region to 475 MeV greatly reduced a number of
backgrounds with little impact on the fit’s sensitivity to
oscillations. We thus performed our oscillation fits in the
energy range 475 < EQEν < 3000 MeV and opened the
full data set.
The top plot of Fig. 2 shows candidate νe events as a
function of EQEν . The vertical dashed line indicates the
minimum EQEν used in the two-neutrino oscillation anal-
ysis. There is no significant excess of events (22±19±35
events) for 475 < EQEν < 1250 MeV; however, an ex-
cess of events (96±17±20 events) is observed below 475
MeV. This low-energy excess cannot be explained by a
two-neutrino oscillation model, and its source is under
investigation. The dashed histogram in Fig. 2 shows the
predicted spectrum when the best-fit two-neutrino oscil-
lation signal is added to the predicted background. The
bottom panel of the figure shows background-subtracted
data with the best-fit two-neutrino oscillation and two
oscillation points from the favored LSND region. The
oscillation fit in the 475 < EQEν < 3000 MeV energy
range yields a χ2 probability of 93% for the null hypoth-
esis, and a probability of 99% for the (sin2 2θ = 10−3,
∆m2 = 4 eV2) best-fit point.
analysis threshold
 oscillationν2
y MiniBooNE data
µνg expected background
µνeν→µν BG + best-fit 
 backgroundµν 
 backgroundeν 
300 600 900 1200 1500
  (MeV)νreconstructed E
 data - expected background
eν→µν best-fit 
2=1.0 eV2m∆)=0.004, θ(22 sin
2=0.1 eV2m∆)=0.2, θ(22 sin
FIG. 2: The top plot shows the number of candidate νe events
as a function of EQEν . The points represent the data with sta-
tistical error, while the histogram is the expected background
with systematic errors from all sources. The vertical dashed
line indicates the threshold used in the two-neutrino oscilla-
tion analysis. Also shown are the best-fit oscillation spec-
trum (dashed histogram) and the background contributions
from νµ and νe events. The bottom plot shows the number of
events with the predicted background subtracted as a func-
tion of EQEν , where the points represent the data with total
errors and the two histograms correspond to LSND solutions
at high and low ∆m2.
A single-sided raster scan to a two neutrino
appearance-only oscillation model is used in the energy
range 475 < EQEν < 3000 MeV to find the 90% CL limit
corresponding to ∆χ2 = χ2limit − χ
bestfit = 1.64. As
shown by the top plot in Fig. 3, the LSND 90% CL al-
lowed region is excluded at the 90% CL. A joint analysis
as a function of ∆m2, using a combined χ2 of the best
fit values and errors for LSND and MiniBooNE, excludes
at 98% CL two-neutrino appearance oscillations as an
explanation of the LSND anomaly. The bottom plot of
Fig. 3 shows limits from the KARMEN [2] and Bugey
[32] experiments.
A second analysis developed simultaneously and with
the same blindness criteria used a different set of recon-
struction programs, PID algorithms, and fitting and nor-
malization processes. The reconstruction used a simpler
model of light emission and propagation. The PID used
172 quantities such as charge and time likelihoods in an-
gular bins, Mγγ, and likelihood ratios (electron/pion and
electron/muon) as inputs to boosted decision tree algo-
rithms [33] that are trained on sets of simulated signal
events and background events with a cascade-training
technique [34]. In order to achieve the maximum sen-
sitivity to oscillations, the νµ-CCQE data sample with
two subevents were fit simultaneously with the νe-CCQE
candidate sample with one subevent. By forming a χ2
using both data sets and using the corresponding covari-
ance matrix to relate the contents of the bins of the two
distributions, the errors in the oscillation parameters that
best describe the νe-CCQE candidate data set were well
constrained by the observed νµ-CCQE data. This pro-
cedure is partially equivalent to doing a νe to νµ ratio
analysis where many of the systematic uncertainties can-
The two analyses are very complementary, with the
second having a better signal-to-background ratio, but
the first having less sensitivity to systematic errors from
detector properties. These different strengths resulted in
very similar oscillation sensitivities and, when unblinded,
yielded the expected overlap of events and very similar
oscillation fit results. The second analysis also sees more
events than expected at low energy, but with less signif-
icance. Based on the predicted sensitivities before un-
blinding, we decided to present the first analysis as our
oscillation result, with the second as a powerful cross-
check.
In summary, while there is a presently unexplained
discrepancy with data lying above background at low
energy, there is excellent agreement between data and
prediction in the oscillation analysis region. If the oscil-
lations of neutrinos and antineutrinos are the same, this
result excludes two neutrino appearance-only oscillations
as an explanation of the LSND anomaly at 98% CL.
We acknowledge the support of Fermilab, the Depart-
ment of Energy, and the National Science Foundation.
We thank Los Alamos National Laboratory for LDRD
funding. We acknowledge Bartoszek Engineering for the
design of the focusing horn. We acknowledge Dmitri Top-
tygin, Anna Pla, and Hans-Otto Meyer for optical mea-
surements of mineral oil. This research was done using
resources provided by the Open Science Grid, which is
supported by the NSF and DOE-SC. We also acknowl-
edge the use of the LANL Pink cluster and Condor soft-
 LSND 90% C.L.
 LSND 99% C.L.
-310 -210 -110 1
) upper limitθ(22sin
yMiniBooNE 90% C.L.
MiniBooNE 90% C.L. sensitivity
BDT analysis 90% C.L.
)θ(22sin
-310 -210 -110 1
 LSND 90% C.L.
 LSND 99% C.L.
yMiniBooNE 90% C.L.
KARMEN2 90% C.L.
Bugey 90% C.L.
FIG. 3: The top plot shows the MiniBooNE 90% CL limit
(thick solid curve) and sensitivity (dashed curve) for events
with 475 < EQEν < 3000 MeV within a two neutrino oscilla-
tion model. Also shown is the limit from the boosted decision
tree analysis (thin solid curve) for events with 300 < EQEν <
3000 MeV. The bottom plot shows the limits from the KAR-
MEN [2] and Bugey [32] experiments. The MiniBooNE and
Bugey curves are 1-sided upper limits on sin2 2θ correspond-
ing to ∆χ2 = 1.64, while the KARMEN curve is a “unified
approach” 2D contour. The shaded areas show the 90% and
99% CL allowed regions from the LSND experiment.
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