The Double Chooz Experiment presents an indication of reactor electron antineutrino disappearance consistent with neutrino oscillations. An observed-to-predicted ratio of events of 0.944 ± 0.016 (stat) ± 0.040 (syst) was obtained in 101 days of running at the Chooz Nuclear Power Plant in France, with two 4.25 GW th reactors. The results were obtained from a single 10 m 3 fiducial volume detector located 1050 m from the two reactor cores. The reactor antineutrino flux prediction used the Bugey4 flux measurement after correction for differences in core composition. The deficit can be interpreted as an indication of a non-zero value of the still unmeasured neutrino mixing parameter sin 2 2θ13. Analyzing both the rate of the prompt positrons and their energy spectrum we find sin 2 2θ13= 0.086 ± 0.041 (stat) ±0.030 (syst), or, at 90% CL, 0.017 < sin 2 2θ13 < 0.16. We report first results of a search for a non-zero neutrino oscillation [1] mixing angle, θ 13 , based on reactor antineutrino disappearance. This is the last of the three neutrino oscillation mixing angles [2,3] for which only upper limits [4,5] are available. The size of θ 13 sets the required sensitivity of long-baseline oscillation experiments attempting to measure CP violation in the neutrino sector or the mass hierarchy.In reactor experiments [6,7] addressing the disappearance ofν e , θ 13 determines the survival probability of electron antineutrinos at the "atmospheric" squaredmass difference, ∆m 2 atm . This probability is given by:where L is the distance from reactor to detector in meters and E the energy of the antineutrino in MeV. The full formula can be found in Ref.[1]. Eq. 1 provides a direct way to measure θ 13 since the only additional input is the well measured value of |∆m 2 atm | = (2.32Other running reactor experiments [9,10] are using the same technique.Electron antineutrinos of < 9 MeV are produced by reactors and detected through inverse beta decay (IBD): ν e + p → e + + n. Detectors based on hydrocarbon liquid scintillators provide the free proton targets. The IBD signature is a coincidence of a prompt positron signal followed by a delayed neutron capture. We present here our first results with a detector located ∼ 1050 m from the two 4.25 GW th thermal power reactors of the Chooz Nuclear Power Plant and under a 300 MWE rock overburden. The analysis is based on 101 days of data including 16 days with one reactor off and one day with both reactors off.The antineutrino flux of each reactor depends on its thermal power and, for the four main fissioning isotopes, 235 U, 239 Pu, 238 U, 241 Pu, their fraction of the total fuel content, their energy released per fission, and their fission and capture cross-sections. The fission rates and associated errors were evaluated using two predictive and complementary reactor simulation codes: MURE [17,18] and DRAGON [19]. This allowed a study of the sensitivity to the important reactor parameters (e.g.. thermal power, boron concentration, temperatures and densities). The quality of these simulations...

The Double Chooz experiment has observed 8,249 candidate electron antineutrino events in 227.93 live days with 33.71 GW-ton-years (reactor power × detector mass × livetime) exposure using a 10.3 m 3 fiducial volume detector located at 1050 m from the reactor cores of the Chooz nuclear power plant in France. The expectation in case of θ13= 0 is 8,937 events. The deficit is interpreted as evidence of electron antineutrino disappearance. From a rate plus spectral shape analysis we find sin 2 2θ13 = 0.109 ± 0.030(stat) ± 0.025(syst). The data exclude the no-oscillation hypothesis at 99.8% CL (2.9σ).

Digital cameras and mobile phones enable us to conveniently record precious moments. While digital image quality is constantly being improved, taking high-quality photos of digital screens still remains challenging because the photos are often contaminated with moiré patterns, a result of the interference between the pixel grids of the camera sensor and the device screen. Moiré patterns can severely damage the visual quality of photos. However, few studies have aimed to solve this problem. In this paper, we introduce a novel multiresolution fully convolutional network for automatically removing moiré patterns from photos. Since a moiré pattern spans over a wide range of frequencies, our proposed network performs a nonlinear multiresolution analysis of the input image before computing how to cancel moiré artefacts within every frequency band. We also create a large-scale benchmark dataset with 100,000+ image pairs for investigating and evaluating moiré pattern removal algorithms. Our network achieves state-of-the-art performance on this dataset in comparison to existing learning architectures for image restoration problems.

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The yields and production rates of the radioisotopes 9 Li and 8 He created by cosmic muon spallation on 12 C, have been measured by the two detectors of the Double Chooz experiment. The identical detectors are located at separate sites and depths, which means that they are subject to different muon spectra. The near (far) detector has an overburden of ∼120 m.w.e. (∼300 m.w.e.) corresponding to a mean muon energy of 32.1 ± 2.0 GeV (63.7 ± 5.5 GeV). Comparing the data to a detailed simulation of the 9 Li and 8 He

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Abstract. A study on cosmic muons has been performed for the two identical near and far neutrino detectors of the Double Chooz experiment, placed at ∼120 and ∼300 m.w.e. underground respectively, including the corresponding simulations using the MUSIC simulation package. This characterization has allowed us to measure the muon flux reaching both detectors to be (3.64 ± 0.04) × 10 −4 cm −2 s −1 for the near detector and (7.00 ± 0.05) × 10 −5 cm −2 s −1 for the far one. The seasonal modulation of the signal has also been studied observing a positive correlation with the atmospheric temperature, leading to an effective temperature coefficient of α T = 0.212 ± 0.024 and 0.355 ± 0.019 for the near and far detectors respectively. These measurements, in good agreement with expectations based on theoretical models, represent one of the first measurements of this coefficient in shallow depth installations.

Retrieving salient structure from textured images is an important but difficult problem in computer vision because texture, which can be irregular, anisotropic, non-uniform and complex, shares many of the same properties as structure. Observing that salient structure in a textured image should be piece-wise smooth, we present a method to retrieve such structures using an minimization of a modified form of the relative total variation metric. Thanks to the characteristics shared by texture and small structures, our method is effective at retrieving structure based on scale as well. Our method outperforms state-of-art methods in texture removal as well as scale-space filtering. We also demonstrate our method's ability in other applications such as edge detection, clip art compression artifact removal, and inverse half-toning.