The spectral broadening of characteristic γ-ray emission peaks from the reaction (12)C((3)He,pγ)(14)N was measured in D((3)He) plasmas of the JET tokamak with ion cyclotron resonance heating tuned to the fundamental harmonic of (3)He. Intensities and detailed spectral shapes of γ-ray emission peaks were successfully reproduced using a physics model combining the kinetics of the reacting ions with a detailed description of the nuclear reaction differential cross sections for populating the L1-L8 (14)N excitation levels yielding the observed γ-ray emission. The results provide a paradigm, which leverages knowledge from areas of physics outside traditional plasma physics, for the development of nuclear radiation based methods for understanding and controlling fusion burning plasmas.

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.

Velocity-space tomography of the fast-ion distribution function in a fusion plasma is usually a photon-starved tomography method due to limited optical access and signal-to-noise ratio of fast-ion D α (FIDA) spectroscopy as well as the strive for high-resolution images. In highdefinition tomography, prior information makes up for this lack of data. We restrict the target velocity space through the measured absence of FIDA light, impose phase-space densities to be non-negative, and encode the known geometry of neutral beam injection (NBI) sources. We further use a numerical simulation as prior information to reconstruct where in velocity space the measurements and the simulation disagree. This alternative approach is demonstrated for four-view as well as for two-view FIDA measurements. The high-definition tomography tools allow us to study fast ions in sawtoothing plasmas and the formation of NBI peaks at full, half and one-third energy by time-resolved tomographic movies.

We describe a new technique for efficient generation of high-energy ions with electromagnetic ion cyclotron waves in multi-ion plasmas. The discussed 'three-ion' scenarios are especially suited for strong wave absorption by a very low number of resonant ions. To observe this effect, the plasma composition has to be properly adjusted, as prescribed by theory. We demonstrate the potential of this technique on the world-largest plasma magnetic confinement device JET (Joint European Torus, Culham, UK) and the high magnetic field tokamak Alcator C-Mod (MIT, USA). The obtained results demonstrate efficient acceleration of 3 He ions to high energies in dedicated hydrogen-deuterium mixtures. Simultaneously, effective plasma heating is observed, as a result of the slowing-down of the fast 3 He ions. The developed technique is not only limited to laboratory plasmas, but can also be applied to explain observations of energetic ions in space plasma environments, in particular, 3 He-rich solar flares.Accepted version of the paper published in Nature Physics (2017) http://dx