The Tokai-to-Kamioka (T2K) experiment studies neutrino oscillations using an off-axis muon neutrino beam with a peak energy of about 0.6 GeV that originates at the J-PARC accelerator facility. Interactions of the neutrinos are observed at near detectors placed at 280 m from the production target and at the far detector -Super-Kamiokande (SK) -located 295 km away. The flux prediction is an essential part of the successful prediction of neutrino interaction rates at the T2K detectors and is an important input to T2K neutrino oscillation and cross section measurements. A FLUKA and GEANT3 based simulation models the physical processes involved in the neutrino production, from the interaction of primary beam protons in the T2K target, to the decay of hadrons 3 and muons that produce neutrinos. The simulation uses proton beam monitor measurements as inputs. The modeling of hadronic interactions is re-weighted using thin target hadron production data, including recent charged pion and kaon measurements from the NA61/SHINE experiment. For the first T2K analyses the uncertainties on the flux prediction are evaluated to be below 15% near the flux peak. The uncertainty on the ratio of the flux predictions at the far and near detectors is less than 2% near the flux peak.

NEXT-100 is an electroluminescent high-pressure xenon gas time projection chamber that will search for the neutrinoless double beta (0νββ) decay of 136 Xe. The detector possesses two features of great value for 0νββ searches: energy resolution better than 1% FWHM at the Q value of 136 Xe and track reconstruction for the discrimination of signal and background events. This combination results in excellent sensitivity, as discussed in this paper. Material-screening measurements and a detailed Monte Carlo detector simulation predict a background rate for NEXT-100 of at most 4 × 10 −4 counts keV −1 kg −1 yr −1 . Accordingly, the detector will reach a sensitivity to the 0νββ-decay half-life of 2.8 × 10 25 years (90% CL) for an exposure of 100 kg · year, or 6.0 × 10 25 years after a run of 3 effective years.

The T2K collaboration reports evidence for electron neutrino appearance at the atmospheric mass splitting, |∆m 2 32 | ≈ 2.4 × 10 −3 eV 2 . An excess of electron neutrino interactions over background is observed from a muon neutrino beam with a peak energy of 0.6 GeV at the Super-Kamiokande (SK) detector 295 km from the beam's origin. Signal and background predictions are constrained by data from near detectors located 280 m from the neutrino production target. We observe 11 electron neutrino candidate events at the SK detector when a background of 3.3 ± 0.4(syst.) events is expected. The background-only hypothesis is rejected with a p-value of 0.0009 (3.1σ), and a 3 fit assuming νµ → νe oscillations with sin 2 2θ23=1, δCP =0 and |∆m 2 32 | = 2.4 × 10 −3 eV 2 yields sin 2 2θ13=0.088+0.049 −0.039 (stat.+syst.).

We present an ultrafast neural network (NN) model, QLKNN, which predicts core tokamak transport heat and particle fluxes. QLKNN is a surrogate model based on a database of 300 million flux calculations of the quasilinear gyrokinetic transport model QuaLiKiz. The database covers a wide range of realistic tokamak core parameters. Physical features such as the existence of a critical gradient for the onset of turbulent transport were integrated into the neural network training methodology. We have coupled QLKNN to the tokamak modelling framework JINTRAC and rapid control-oriented tokamak transport solver RAPTOR. The coupled frameworks are demonstrated and validated through application to three JET shots covering a representative spread of H-mode operating space, predicting turbulent transport of energy and particles in the plasma core. JINTRAC-QLKNN and RAPTOR-QLKNN are able to accurately reproduce JINTRAC-QuaLiKiz T i,e and n e profiles, but 3 to 5 orders of magnitude faster. Simulations which take hours are reduced down to only a few tens of seconds. The discrepancy in the final source-driven predicted profiles between QLKNN and QuaLiKiz is on the order 1%-15%. Also the dynamic behaviour was well captured by QLKNN, with differences of only 4%-10% compared to JINTRAC-QuaLiKiz observed at mid-radius, for a study of density buildup following the L-H transition. Deployment of neural network surrogate models in multi-physics integrated tokamak modelling is a promising route towards enabling accurate and fast tokamak scenario optimization, Uncertainty Quantification, and control applications.

NEXT-DEMO is a high-pressure xenon gas TPC which acts as a technological testbed and demonstrator for the NEXT-100 neutrinoless double beta decay experiment. In its current configuration the apparatus fully implements the NEXT-100 design concept. This is an asymmetric TPC, with an energy plane made of photomultipliers and a tracking plane made of silicon photomultipliers (SiPM) coated with TPB. The detector in this new configuration has been used to reconstruct the characteristic signature of electrons in dense gas. Demonstrating the ability to identify the MIP and "blob" regions. Moreover, the SiPM tracking plane allows for the definition of a large fiducial region in which an excellent energy resolution of 1.82% FWHM at 511 keV has been measured (a value which extrapolates to 0.83% at the xenon Q β β ).