Search for a Light Sterile Neutrino at Daya Bay
F. P. An,1A. B. Balantekin,2H. R. Band,2W. Beriguete,3M. Bishai,3S. Blyth,4I. Butorov,5G. F. Cao,6J. Cao,6Y. L. Chan,7 J. F. Chang,6 L. C. Chang,8 Y. Chang,9C. Chasman,3 H. Chen,6 Q. Y. Chen,10S. M. Chen,11X. Chen,7 X. Chen,6 Y. X. Chen,12Y. Chen,13Y. P. Cheng,6 J. J. Cherwinka,2 M. C. Chu,7 J. P. Cummings,14J. de Arcos,15Z. Y. Deng,6 Y. Y. Ding,6 M. V. Diwan,3 E. Draeger,15X. F. Du,6D. A. Dwyer,16W. R. Edwards,16S. R. Ely,17J. Y. Fu,6L. Q. Ge,18 R. Gill,3M. Gonchar,5G. H. Gong,11H. Gong,11M. Grassi,6W. Q. Gu,19M. Y. Guan,6X. H. Guo,20R. W. Hackenburg,3 G. H. Han,21 S. Hans,3 M. He,6 K. M. Heeger,2,22Y. K. Heng,6P. Hinrichs,2 Y. K. Hor,23Y. B. Hsiung,4B. Z. Hu,8 L. M. Hu,3 L. J. Hu,20T. Hu,6 W. Hu,6E. C. Huang,17H. Huang,24X. T. Huang,10P. Huber,23G. Hussain,11Z. Isvan,3 D. E. Jaffe,3P. Jaffke,23K. L. Jen,8S. Jetter,6 X. P. Ji,25X. L. Ji,6 H. J. Jiang,18J. B. Jiao,10R. A. Johnson,26L. Kang,27 S. H. Kettell,3M. Kramer,16,28K. K. Kwan,7M. W. Kwok,7T. Kwok,29W. C. Lai,18K. Lau,30L. Lebanowski,11J. Lee,16 R. T. Lei,27R. Leitner,31A. Leung,29J. K. C. Leung,29C. A. Lewis,2D. J. Li,32F. Li,18,6G. S. Li,19Q. J. Li,6W. D. Li,6 X. N. Li,6X. Q. Li,25Y. F. Li,6Z. B. Li,33H. Liang,32C. J. Lin,16G. L. Lin,8P. Y. Lin,8S. K. Lin,30Y. C. Lin,18J. J. Ling,3,17 J. M. Link,23L. Littenberg,3B. R. Littlejohn,26D. W. Liu,30H. Liu,30J. L. Liu,19J. C. Liu,6S. S. Liu,29Y. B. Liu,6C. Lu,34
H. Q. Lu,6 K. B. Luk,28,16Q. M. Ma,6X. Y. Ma,6 X. B. Ma,12Y. Q. Ma,6 K. T. McDonald,34M. C. McFarlane,2 R. D. McKeown,35,21 Y. Meng,23I. Mitchell,30J. Monari Kebwaro,36Y. Nakajima,16J. Napolitano,37D. Naumov,5 E. Naumova,5 I. Nemchenok,5 H. Y. Ngai,29Z. Ning,6 J. P. Ochoa-Ricoux,38,16A. Olshevski,5 S. Patton,16V. Pec,31 J. C. Peng,17L. E. Piilonen,23 L. Pinsky,30C. S. J. Pun,29F. Z. Qi,6 M. Qi,39X. Qian,3 N. Raper,40B. Ren,27 J. Ren,24 R. Rosero,3B. Roskovec,31X. C. Ruan,24B. B. Shao,11H. Steiner,28,16 G. X. Sun,6 J. L. Sun,41Y. H. Tam,7 X. Tang,6 H. Themann,3K. V. Tsang,16R. H. M. Tsang,35C. E. Tull,16Y. C. Tung,4B. Viren,3V. Vorobel,31C. H. Wang,9L. S. Wang,6 L. Y. Wang,6M. Wang,10N. Y. Wang,20R. G. Wang,6W. Wang,21,33W. W. Wang,39X. Wang,42Y. F. Wang,6Z. Wang,11 Z. Wang,6Z. M. Wang,6D. M. Webber,2H. Y. Wei,11Y. D. Wei,27L. J. Wen,6K. Whisnant,43C. G. White,15L. Whitehead,30 T. Wise,2H. L. H. Wong,28,16S. C. F. Wong,7E. Worcester,3Q. Wu,10D. M. Xia,6J. K. Xia,6X. Xia,10Z. Z. Xing,6J. Y. Xu,7 J. L. Xu,6 J. Xu,20 Y. Xu,25 T. Xue,11J. Yan,36C. C. Yang,6 L. Yang,27M. S. Yang,6 M. T. Yang,10M. Ye,6 M. Yeh,3 Y. S. Yeh,8B. L. Young,43G. Y. Yu,39J. Y. Yu,11Z. Y. Yu,6S. L. Zang,39B. Zeng,18L. Zhan,6 C. Zhang,3F. H. Zhang,6
J. W. Zhang,6 Q. M. Zhang,36Q. Zhang,18S. H. Zhang,6 Y. C. Zhang,32 Y. M. Zhang,11Y. H. Zhang,6 Y. X. Zhang,41 Z. J. Zhang,27Z. Y. Zhang,6Z. P. Zhang,32J. Zhao,6 Q. W. Zhao,6Y. Zhao,12,21Y. B. Zhao,6L. Zheng,32W. L. Zhong,6
L. Zhou,6 Z. Y. Zhou,24 H. L. Zhuang,6and J. H. Zou6 (Daya Bay Collaboration)
1
Institute of Modern Physics, East China University of Science and Technology, Shanghai
2
University of Wisconsin, Madison, Wisconsin, USA 3Brookhaven National Laboratory, Upton, New York, USA 4
Department of Physics, National Taiwan University, Taipei 5Joint Institute for Nuclear Research, Dubna, Moscow Region
6
Institute of High Energy Physics, Beijing 7Chinese University of Hong Kong, Hong Kong 8
Institute of Physics, National Chiao-Tung University, Hsinchu 9National United University, Miao-Li
10
Shandong University, Jinan
11Department of Engineering Physics, Tsinghua University, Beijing 12
North China Electric Power University, Beijing 13
Shenzhen University, Shenzhen 14
Siena College, Loudonville, New York, USA 15
Department of Physics, Illinois Institute of Technology, Chicago, Illinois, USA 16
Lawrence Berkeley National Laboratory, Berkeley, California, USA 17
Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA 18
Chengdu University of Technology, Chengdu 19
Shanghai Jiao Tong University, Shanghai 20
Beijing Normal University, Beijing 21
College of William and Mary, Williamsburg, Virginia, USA 22
23Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia, USA 24
China Institute of Atomic Energy, Beijing 25School of Physics, Nankai University, Tianjin 26
Department of Physics, University of Cincinnati, Cincinnati, Ohio, USA 27Dongguan University of Technology, Dongguan
28
Department of Physics, University of California, Berkeley, California, USA 29Department of Physics, The University of Hong Kong, Pokfulam, Hong Kong
30
Department of Physics, University of Houston, Houston, Texas, USA 31Charles University, Faculty of Mathematics and Physics, Prague
32
University of Science and Technology of China, Hefei 33Sun Yat-Sen (Zhongshan) University, Guangzhou 34
Joseph Henry Laboratories, Princeton University, Princeton, New Jersey, USA 35California Institute of Technology, Pasadena, California, USA
36
Xi’an Jiaotong University, Xi’an
37Department of Physics, College of Science and Technology, Temple University, Philadelphia, Pennsylvania, USA 38
Instituto de Física, Pontificia Universidad Católica de Chile, Santiago, Chile 39Nanjing University, Nanjing
40
Department of Physics, Applied Physics, and Astronomy, Rensselaer Polytechnic Institute, Troy, New York, USA 41China General Nuclear Power Group, Shenzhen
42
College of Electronic Science and Engineering, National University of Defense Technology, Changsha
43
Iowa State University, Ames, Iowa, USA (Received 28 July 2014; published 1 October 2014)
A search for light sterile neutrino mixing was performed with the first 217 days of data from the Daya Bay Reactor Antineutrino Experiment. The experiment’s unique configuration of multiple baselines from six 2.9 GWthnuclear reactors to six antineutrino detectors deployed in two near (effective baselines 512 m and 561 m) and one far (1579 m) underground experimental halls makes it possible to test for oscillations to a fourth (sterile) neutrino in the10−3eV2< jΔm241j < 0.3 eV2range. The relative spectral distortion due to the disappearance of electron antineutrinos was found to be consistent with that of the three-flavor oscillation model. The derived limits on sin22θ14 cover the 10−3eV2≲ jΔm241j ≲ 0.1 eV2 region, which was largely unexplored.
DOI:10.1103/PhysRevLett.113.141802 PACS numbers: 14.60.Pq, 14.60.St, 28.50.Hw, 29.40.Mc
Measurements in the past decades have revealed large mixing between the flavor and mass eigenstates of neu-trinos. The neutrino mixing framework [1–3] with three flavors has been successful in explaining most experimen-tal results, and several-percent precision has been attained in the determination of the neutrino mixing angles and the mass splittings. Despite this great progress, there is still room for other generations of neutrinos to exist. Fits to precision electroweak measurements[4,5]have limited the number of light active neutrino flavors to three, although other light neutrinos may exist as long as they do not participate in standard V-A interactions. These neutrinos, which arise in extensions of the standard model that incorporate neutrino masses, are typically referred to as sterile neutrinos [2].
In addition to being well motivated from the theoretical standpoint, sterile neutrinos are among the leading candi-dates to resolve outstanding puzzles in astronomy and cosmology. Sterile neutrinos with ∼keV masses are good candidates for nonbaryonic dark matter[6,7]. Light sterile neutrinos with eV or sub-eV mass have been shown to help reconcile the tensions in the cosmological data between
current measurements of the present and early Universe[8]
as well as between cosmic microwave background and lensing measurements[9]. The recentB-mode polarization data from BICEP2[10]has spurred even more discussion in this area[11–14].
If light sterile neutrinos mix with the three active neutrinos, their presence could be detected via the modi-fication to the latter’s oscillatory behavior. Various searches for active-sterile neutrino mixing in the mass-squared splitting jΔm2j > 0.1 eV2 region have been carried out in this way. The LSND [15] and MiniBooNE [16,17]
experiments observed excesses of electron (anti-)neutrino events in their muon (anti-)neutrino beams, which could be interpreted as sterile neutrino oscillation withjΔm2j ∼ 1 eV2. However, these results are in tension[18–21]with
the limits derived from other appearance [22–25] or disappearance searches [26–36]. Moreover, a reanalysis of the measured vs predicted electron antineutrino events from previous reactor experiments has revealed a deficit of about 6% [37,38]. Although the significance of this effect is still under discussion [39,40], it is compatible with the so-called gallium anomaly [41–43] in that both
can be explained by introducing a sterile neutrino with jΔm2j > 0.5 eV2 [44]. Until now, however, the jΔm2j <
0.1 eV2 region has remained largely unexplored.
This Letter describes a search for a light sterile neutrino via its mixing with the active neutrinos using more than 300 000 reactor antineutrino interactions collected in the Daya Bay Reactor Antineutrino Experiment. This data set was recorded during the six-detector data period from December 2011 to July 2012. Since the antineutrino detectors are located at baselines ranging from a few hundred to almost two thousand meters away from the reactor cores, Daya Bay is most sensitive to active-sterile neutrino mixing in the 10−3 eV2< jΔm2j < 0.3 eV2 range. In this region, a positive signal for active-sterile neutrino mixing would predominantly manifest itself as an additional spectral distortion with a frequency different from the one due to the atmospheric mass splitting.
This work used a minimal extension of the standard model: the3ðactiveÞ þ 1ðsterileÞ neutrino mixing model. In this model, if the neutrino mass is much smaller than its momentum, the probability that an¯νeproduced with energy E is detected as an ¯νeafter traveling a distanceL is given by
P¯νe→¯νe¼ 1 − 4 X3 i¼1 X4 j>i jUeij2jUejj2sin2Δji: ð1Þ
Here Uei is the element of the neutrino mixing matrix for the flavor eigenstate νe and the mass eigenstate νi, Δji ¼ 1.267Δm2jiðeV2Þ½LðmÞ=EðMeVÞ with Δm2ji¼
m2
j− m2i being the mass-squared difference between the
mass eigenstates νj and νi. Using the parametrization of Ref. [34], Uei can be expressed in terms of the neutrino mixing angles θ14,θ13, andθ12,
Ue1¼ cos θ14cosθ13cosθ12;
Ue2¼ cos θ14cosθ13sinθ12;
Ue3¼ cos θ14sinθ13;
Ue4¼ sin θ14: ð2Þ
If θ14 ¼ 0, the probability returns to the expression for three-neutrino oscillation.
The Daya Bay experiment has two near underground experimental halls (EH1 and EH2) and one far hall (EH3). Each hall houses functionally identical, three-zone anti-neutrino detectors submerged in pools of ultrapure water segmented into two optically decoupled regions. The water pools are instrumented with photomultiplier tubes to tag cosmic-ray-induced interactions. Reactor antineutrinos were detected via the inverse β-decay (IBD) reaction (¯νeþ p → eþþ n). The coincidence of the prompt (eþ ionization and annihilation) and delayed (n capture on Gd) signals efficiently suppressed the backgrounds, which amounted to less than 2% (5%) of the entire candidate samples in the near (far) halls [45]. The prompt signal
measured the ¯νe energy with an energy resolution σE=E ≈ 8% at 1 MeV. More details on the reconstruction
and detector performance can be found in Ref. [46]. A summary of the IBD candidates used in this analysis, together with the baselines of the three experimental halls to each pair of reactors, is shown in TableI.
The uncertainty in the absolute energy scale of positrons was estimated to be about 1.5% through a combination of the uncertainties of calibration data and various energy models
[45]. This quantity had a negligible effect on the sensitivity of the sterile neutrino search due to the relative nature of the measurement with functionally identical detectors. The uncertainty of the relative energy scale was determined from the relative response of all antineutrino detectors to various calibration sources that spanned the IBD positron energy range, and was found to be 0.35%. The predicted ¯νe flux took into account the daily live-time-corrected thermal power, the fission fractions of each isotope as provided by the reactor company, the fission energies, and the number of antineutrinos produced per fission per isotope[47].
The precision of the measured baselines was about 2 cm with both the GPS and total station[48]. The geometric effect due to the finite size of the reactor cores and the antineutrino detectors, whose dimensions are comparable to the oscillation length atjΔm2j ∼ eV2, was assessed by assuming that antineutrinos were produced and interacted uniformly in these volumes. The impact was found to be unimportant in the range ofΔm2where Daya Bay is most sensitive (jΔm2j < 0.3 eV2). Higher order effects, such as the nonuniform production of antineutrinos inside the reactor cores due to a particular reactor fuel burning history, also had a negligible impact on the final result.
The greatest sensitivity to sin22θ14 in the jΔm241j < 0.3 eV2 region came from the relative measurements
between multiple EHs at different baselines. Figure 1
shows the ratios of the observed prompt energy spectra at EH2 (EH3) and the three-neutrino best-fit prediction from the EH1 spectrum[45]. The data are compared with the 3+1 neutrino oscillation with sin22θ14¼ 0.1 and two representativejΔm241j values, illustrating that the sensitivity atjΔm241j ¼ 4 × 10−2ð4 × 10−3Þ eV2came primarily from the relative spectral shape comparison between EH1 and EH2 (EH3). Sensitivities for various combinations of the data sets from different EHs were estimated with the method described later in this Letter, and are shown in
TABLE I. Total number of IBD candidates and baselines of the three experimental halls to the reactor pairs.
Mean distance to reactor core (m) Location IBD candidates Daya Bay Ling Ao Ling Ao-II
EH1 203 809 365 860 1310
EH2 92 912 1345 479 528
Fig.2. The sensitivity in the0.01 eV2< jΔm241j < 0.3 eV2 region originated predominantly from the relative meas-urement between the two near halls, while the sensitivity in the jΔm241j < 0.01 eV2 region arose primarily from the comparison between the near and far halls. The high-precision data at multiple baselines are essential for probing a wide range of values of jΔm241j.
The uncertainty of the reactor flux model’s normalization had a marginal impact in thejΔm241j < 0.3 eV2region. For jΔm2
41j > 0.3 eV2, spectral distortion features are smeared
out and the relative measurement loses its discriminatory power. The sensitivity in this region can be regained by comparing the event rates of the Daya Bay near halls with the flux model prediction, which will be reported in a future publication. In this Letter, we focus on thejΔm241j < 0.3 eV2 region.
Three independent analyses were conducted, each with a different treatment of the predicted reactor antineutrino flux and systematic errors. The first analysis used the predicted reactor antineutrino spectra to simultaneously fit the data from the three halls, in a fashion similar to what was described in the recent Daya Bay spectral analysis[45]. A binned log-likelihood method was adopted with nuisance parameters constrained with the detector response and the backgrounds, and with a covariance matrix encapsulating the reactor flux uncertainties as given in the Huber [49]
and Mueller[39]flux models. The rate uncertainty of the absolute reactor ¯νe flux was enlarged to 5% based on Ref.[40]. The fit used sin22θ12 ¼ 0.857 0.024, Δm221¼ ð7.50 0.20Þ × 10−5 eV2 [50], and jΔm2
32j ¼ ð2.41
0.10Þ × 10−3 eV2 [51]. The values of sin22θ
14, sin22θ13
and jΔm241j were unconstrained. For the 3 þ 1 neutrino model, a global minimum ofχ24ν=NDF ¼ 158.8=153 was obtained, while the minimum for the three-neutrino model wasχ23ν=NDF ¼ 162.6=155, where NDF represents num-ber of degrees of freedom. We used the Δχ2¼ χ23ν− χ24ν distribution obtained from three-neutrino Monte Carlo samples that incorporated both statistical and systematic variations to obtain ap-value [52]of 0.74 forΔχ2¼ 3.8. The data were thus found to be consistent with the three-neutrino model, and there was no significant evidence for sterile neutrino mixing.
The second analysis performed a purely relative compari-son between data at the near and far halls. The observed prompt energy spectra of the near halls were extrapolated to the far hall and compared with observation. This process was done independently for each prompt energy bin, by first unfolding it into the corresponding true antineutrino energy spectrum and then extrapolating to the far hall based on the known baselines and the reactor power profiles. A covariance matrix, generated from a large Monte Carlo data set incor-porating both statistical and systematic variations, was used to
(Measured) / (Expected from EH1)
Prompt energy (MeV)
1 2 3 4 5 6 7
0.8 0.9 1 1.1
1.2 Data Unc. of 3ν prediction
2 eV -3 = 4x10 41 2 m Δ 2 eV -2 = 4x10 41 2 m Δ EH2 = 0.10 assumed 14 θ 2 2 sin
Prompt energy (MeV)
1 2 3 4 5 6 7 8 0.8 0.9 1 1.1 1.2 EH3
FIG. 1 (color online). Prompt energy spectra observed at EH2 (top) and EH3 (bottom), divided by the prediction from the EH1 spectrum with the three-neutrino best-fit oscillation parameters from the previous Daya Bay analysis[45]. The gray band represents the uncertainty of the three-neutrino oscillation prediction, which includes the statistical uncertainty of the EH1 data and all the systematic uncertainties. Predictions with sin22θ14¼ 0.1 and two representative jΔm241j values are also shown as the dotted and dashed curves.
14 θ 2 2 sin -3 10 10-2 10-1 1 ) 2 | (eV 41 2 m Δ| -4 10 -3 10 -2 10 -1 10 1 Daya Bay 95% CLs EH1 EH1+EH2 EH1+EH3 3 EHs
3 EHs (spectra only)
KARMEN+LSND 95% CL Bugey 90% CL (40m/15m)
Sensitivity
FIG. 2 (color online). Comparison of the 95% exclusion limit sensitivities based on the confidence levels CLs method for various combinations of EH’s data (see text for details). The sensitivities were estimated from an Asimov Monte Carlo data set that was generated without statistical or systematic variations. All the Daya Bay sensitivity curves were calculated assuming 5% rate uncertainty in the reactor flux except the dot-dashed one, which corresponds to a comparison of spectra only. Normal mass hierarchy was assumed for bothΔm231 and Δm2
41. The dip structure atjΔm241j ≈ 2.4 × 10−3 eV2was caused by the degeneracy between sin22θ14 and sin22θ13. The green dashed line represents Bugey’s[32]90% confidence level (C.L.) limit on ¯νe disappearance and the magenta double-dot-single-dashed line represents the combined KARMEN and LSND 95% C.L. limit onνedisappearance fromνe-carbon cross section measurements[33].
account for all uncertainties. The resultingp-value was 0.87. More details about this approach can be found in Ref.[53]. The third analysis exploited both rate and spectral information in a way that is similar to the first method but using a covariance matrix. This matrix was calculated based on standard uncertainty propagation methods, with-out an extensive generation of Monte Carlo samples. The obtainedp-value was 0.74.
The various analyses have complementary strengths. Those that incorporated reactor antineutrino flux constraints had a slightly higher reach in sensitivity, particularly for higher values of jΔm241j. The purely relative analysis was more robust against uncertainties in the predicted reactor antineutrino flux. The different treatments of systematic uncertainties provided a thorough cross-check of the results, which were found to be consistent for all the analyses in the region where the relative spectral measurement dominated the sensitivity (jΔm241j < 0.3 eV2). As evidenced by the reported p-values, no significant signature for sterile neu-trino mixing was found by any of the methods.
Two methods were adopted to set the exclusion limits in theðjΔm241j; sin22θ14Þ space. The first one was a frequent-ist approach with a likelihood ratio as the ordering principle, as proposed by Feldman and Cousins [54]. For each point η ≡ ðjΔm241j; sin22θ14Þ, the value Δχ2cðηÞ encompassing a fraction α of the events in the χ2ðηÞ − χ2ðη
bestÞ distribution was determined, where ηbest was the
best-fit point. This distribution was obtained by fitting a large number of simulated experiments that included statistical and systematic variations. To reduce the number of computations, the simulated experiments were generated with a fixed value of sin22θ13 ¼ 0.09 [45], after it was verified that the dependency of Δχ2cðηÞ on this parameter was negligible. The point η was then declared to be inside the α confidence level (C.L.) acceptance region if Δχ2dataðηÞ < Δχ2cðηÞ.
The second method was the confidence levels CLs statistical method[55] described in detail in Ref. [56]. A two-hypothesis test was performed in the (sin22θ14, jΔm2
41j) phase space with the null hypothesis H0 (3-ν
model) and the alternative hypothesis H1(3 þ 1-ν model with fixed value of sin22θ14andjΔm241j). The value of θ13 was fixed with the best-fit value of the data for each hypothesis. Since both hypotheses have fixed values of sin22θ14andjΔm241j, their χ2difference follows a Gaussian distribution. The mean and variance of these Gaussian distributions were calculated from Asimov data sets with-out statistical or systematic fluctuations, which avoided massive computing. The CLs value is defined by
CLs¼1 − p1
1 − p0; ð3Þ
wherep0andp1are thep-values for the 3-ν and 3 þ 1-ν hypotheses models respectively. The condition of CLs≤ 0.05 was required to set the 95% CLs exclusion regions.
The 95% confidence level contour from the Feldman-Cousins method and the 95% CLs method’s exclusion
contour are shown in Fig. 3 [57]. The two methods gave comparable results. The detailed structure is due to the finite statistics of the data. The impact of varying the bin size of the IBD prompt energy spectrum from 200 to 500 keV was negligible. Moreover, the choice of mass ordering in both the three- and four-neutrino scenarios had a marginal impact on the results. For comparison, Bugey’s 90% C.L. exclusion on ¯νe disappearance obtained from their ratio of the positron energy spectra measured at 40=15 m[32]is also shown. Our result presently provides the most stringent limits on sterile neutrino mixing at jΔm2
41j < 0.1 eV2 using the electron antineutrino
disap-pearance channel. This result is complementary to those from theð−Þνμ → νð−Þe andð−Þνμ → νð−Þμoscillation channels. While theð−Þνe appearance mode constrains the product of jUμ4j2 andjUe4j2, the ð−Þνμ andð−Þνe disappearance modes constrain jUμ4j2 andjUe4j2, respectively.
In summary, we report on a sterile neutrino search based on a minimal extension of the standard model, the 3ðactiveÞ þ 1ðsterileÞ neutrino mixing model, in the Daya Bay Reactor Antineutrino Experiment using the electron-antineutrino disappearance channel. The analysis used the
14 θ 2 2 sin -3 10 10-2 10-1 1 ) 2 | (eV 41 2 m Δ| -4 10 -3 10 -2 10 -1 10 DayaBay 95% C.L. DayaBay 95% CLs Bugey 90% C.L. (40m/15m)
FIG. 3 (color online). Exclusion contours for the neutrino oscillation parameters sin22θ14 and jΔm241j. Normal mass hier-archy is assumed for bothΔm231andΔm241. The red long-dashed curve represents the 95% C.L. exclusion contour with Feldman-Cousins method[54]. The black solid curve represents the 95% CLsexclusion contour[55]. The parameter space to the right side of the contours is excluded. For comparison, Bugey’s [32]
90% C.L. limit on¯νedisappearance is also shown as the green dashed curve.
relative event rate and the spectral comparison of three far and three near antineutrino detectors at different baselines from six nuclear reactors. The data are in good agreement with the three-neutrino model. The current precision is dominated by statistics. With at least three more years of additional data, the sensitivity to sin22θ14 is expected to improve by a factor of two for most Δm241 values. The current result already yields the world’s most stringent limits on sin22θ14 in thejΔm41j2< 0.1 eV2region.
Daya Bay is supported in part by the Ministry of Science and Technology of China, the U.S. Department of Energy, the Chinese Academy of Sciences, the National Natural Science Foundation of China, the Guangdong provincial government, the Shenzhen municipal government, the China General Nuclear Power Group, Key Laboratory of Particle and Radiation Imaging (Tsinghua University), the Ministry of Education, Key Laboratory of Particle Physics and Particle Irradiation (Shandong University), the Ministry of Education, Shanghai Laboratory for Particle Physics and Cosmology, the Research Grants Council of the Hong Kong Special Administrative Region of China, the University Development Fund of The University of Hong Kong, the MOE program for Research of Excellence at National Taiwan University, National Chiao-Tung University, and NSC fund support from Taiwan, the U.S. National Science Foundation, the Alfred P. Sloan Foundation, the Ministry of Education, Youth, and Sports of the Czech Republic, the Joint Institute of Nuclear Research in Dubna, Russia, the CNFC-RFBR joint research program, the National Commission of Scientific and Technological Research of Chile, and the Tsinghua University Initiative Scientific Research Program. We acknowledge Yellow River Engineering Consulting Co., Ltd., and China Railway 15th Bureau Group Co., Ltd., for building the underground laboratory. We are grateful for the ongoing cooperation from the China General Nuclear Power Group and China Light and Power Company.
[1] B. Pontecorvo, Sov. Phys. JETP 6, 429 (1957). [2] B. Pontecorvo, Sov. Phys. JETP 26, 984 (1968).
[3] Z. Maki, M. Nakagawa, and S. Sakata,Prog. Theor. Phys. 28, 870 (1962).
[4] J. Beringer et al. (Particle Data Group),Phys. Rev. D 86,
010001 (2012).
[5] S. Schael et al. (ALEPH Collaboration, DELPHI Collaboration, L3 Collaboration, OPAL Collaboration, SLD Collaboration, LEP Electroweak Working Group, SLD Electroweak Group, SLD Heavy Flavour Group),
Phys. Rep. 427, 257 (2006).
[6] S. Dodelson and L. M. Widrow, Phys. Rev. Lett. 72, 17 (1994).
[7] A. Kusenko,Phys. Rep. 481, 1 (2009).
[8] M. Wyman, D. H. Rudd, R. A. Vanderveld, and W. Hu,
Phys. Rev. Lett. 112, 051302 (2014).
[9] R. A. Battye and A. Moss,Phys. Rev. Lett. 112, 051303 (2014).
[10] P. Ade et al. (BICEP2 Collaboration),Phys. Rev. Lett. 112,
241101 (2014).
[11] E. Giusarma, E. Di Valentino, M. Lattanzi, A. Melchiorri, and O. Mena,Phys. Rev. D 90, 043507 (2014).
[12] J.-F. Zhang, Y.-H. Li, and X. Zhang,arXiv:1403.7028.
[13] M. Archidiacono, N. Fornengo, S. Gariazzo, C. Giunti, S. Hannestad, and M. Laveder,J. Cosmol. Astropart. Phys. 06 (2014) 031.
[14] B. Leistedt, H. V. Peiris, and L. Verde,Phys. Rev. Lett. 113,
041301 (2014).
[15] A. Aguilar et al. (LSND Collaboration),Phys. Rev. D 64,
112007 (2001).
[16] A. Aguilar-Arevalo et al. (MiniBooNE Collaboration),
Phys. Rev. Lett. 110, 161801 (2013).
[17] A. A. Aguilar-Arevalo et al. (MiniBooNE Collaboration),
Phys. Rev. Lett. 98, 231801 (2007).
[18] M. Maltoni and T. Schwetz, Phys. Rev. D 76, 093005 (2007).
[19] G. Karagiorgi, Z. Djurcic, J. M. Conrad, M. Shaevitz, and M. Sorel, Phys. Rev. D 80, 073001 (2009).
[20] G. Karagiorgi,arXiv:1110.3735.
[21] C. Giunti and M. Laveder,Phys. Lett. B 706, 200 (2011). [22] B. Armbruster et al. (KARMEN Collaboration),Phys. Rev.
D 65, 112001 (2002).
[23] P. Astier et al. (NOMAD Collaboration),Phys. Lett. B 570, 19 (2003).
[24] N. Agafonova et al. (OPERA Collaboration), J. High Energy Phys. 07 (2013) 004; 07 (2013) 085.
[25] M. Antonello et al. (ICARUS Collaboration),Eur. Phys. J.
C 73, 2599 (2013).
[26] I. Stockdale et al.,Phys. Rev. Lett. 52, 1384 (1984). [27] F. Dydak et al.,Phys. Lett. 134B, 281 (1984).
[28] G. Cheng et al. (SciBooNE and MiniBooNE Collabora-tions),Phys. Rev. D 86, 052009 (2012).
[29] K. B. M. Mahn et al. (SciBooNE and MiniBooNE Collaborations),Phys. Rev. D 85, 032007 (2012). [30] S. Fukuda et al. (Super-Kamiokande Collaboration),Phys.
Rev. Lett. 85, 3999 (2000).
[31] P. Adamson et al. (MINOS Collaboration),Phys. Rev. Lett.
107, 011802 (2011).
[32] Y. Declais et al.,Nucl. Phys. B434, 503 (1995).
[33] J. M. Conrad and M. H. Shaevitz,Phys. Rev. D 85, 013017 (2012).
[34] A. Palazzo,J. High Energy Phys. 10 (2013) 172.
[35] A. Esmaili, E. Kemp, O. L. G. Peres, and Z. Tabrizi,Phys.
Rev. D 88, 073012 (2013).
[36] I. Girardi, D. Meloni, T. Ohlsson, H. Zhang, and S. Zhou,
J. High Energy Phys. 08 (2014) 057.
[37] G. Mention, M. Fechner, Th. Lasserre, Th. A. Mueller, D. Lhuillier, M. Cribier, and A. Letourneau,Phys. Rev. D 83,
073006 (2011).
[38] C. Zhang, X. Qian, and P. Vogel,Phys. Rev. D 87, 073018 (2013).
[39] T. Mueller et al.,Phys. Rev. C 83, 054615 (2011). [40] A. C. Hayes, J. L. Friar, G. T. Garvey, G. Jungman, and
G. Jonkmans,Phys. Rev. Lett. 112, 202501 (2014). [41] W. Hampel et al. (GALLEX Collaboration),Phys. Lett. B
[42] J. Abdurashitov et al. (SAGE Collaboration),Phys. Rev. C
80, 015807 (2009).
[43] C. Giunti and M. Laveder,Phys. Rev. C 83, 065504 (2011). [44] C. Giunti, M. Laveder, Y. F. Li, Q. Y. Liu, and H. W. Long,
Phys. Rev. D 86, 113014 (2012).
[45] F. An et al. (Daya Bay Collaboration),Phys. Rev. Lett. 112,
061801 (2014).
[46] F. An et al. (Daya Bay Collaboration), Nucl. Instrum.
Methods Phys. Res., Sect. A 685, 78 (2012).
[47] F. An et al. (Daya Bay Collaboration),Chin. Phys. C 37,
011001 (2013).
[48] F. An et al. (Daya Bay Collaboration),Phys. Rev. Lett. 108,
171803 (2012).
[49] P. Huber,Phys. Rev. C 84, 024617 (2011).
[50] A. Gando et al. (KamLAND Collaboration),Phys. Rev. D
83, 052002 (2011).
[51] This value was reported in Ref. [58]. An independent measurement was recently released in Ref. [59]. Both
values are consistent, and the results presented here are not very sensitive to this parameter.
[52] The p-value is the probability of obtaining a test statistic result at least as extreme as the observed one.
[53] Y. Nakajima and J. P. Ochoa-Ricoux (to be published). [54] G. J. Feldman and R. D. Cousins, Phys. Rev. D 57, 3873
(1998).
[55] A. L. Read,J. Phys. G 28, 2693 (2002).
[56] X. Qian, A. Tan, J. J. Ling, Y. Nakajima, and C. Zhang,
arXiv:1407.5052.
[57] See the Supplemental Material at http://link.aps.org/
supplemental/10.1103/PhysRevLett.113.141802 for the
90% confidence level contour with the Feldman-Cousins method.
[58] P. Adamson et al. (MINOS Collaboration),Phys. Rev. Lett.
110, 251801 (2013).
[59] K. Abe et al. (T2K Collaboration),Phys. Rev. Lett. 112,
