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Helium ash alpha particles at â¼100 keV in magnetically confined fusion plasmas may have the same Larmor radius, as well as cyclotron frequency, as the energetic beam-injected deuterons that heat the plasma. While the velocity-space distribution of the helium ash is monotonically decreasing, that of the energetic deuterons is a delta function in the edge plasma. Here we identify, by means of first principles particle-in-cell computations, a new physical process by which Larmor radius matching enables collective gyroresonant energy transfer between these two colocated minority energetic ion populations, embedded in majority thermal plasma. This newly identified nonlinear phenomenon rests on similar underlying physics to widely observed ion cyclotron emission from suprathermal minority ion populations.
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A fast Alfvén wave with a finite amplitude is shown to grow by a stimulated emission process that we propose for exploitation in toroidal magnetically confined fusion plasmas. Stimulated emission occurs while the wave propagates inward through the outer midplane plasma, where a population inversion of the energy distribution of fusion-born ions is observed to arise naturally. Fully nonlinear first-principles simulations, which self-consistently evolve particles and fields under the Maxwell-Lorentz system, demonstrate this novel "α-particle channeling" scenario for the first time.
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Ion cyclotron emission (ICE) offers a unique promise as a diagnostic of the fusion born alpha-particle population in magnetically confined plasmas. Pioneering observations from JET and TFTR found that ICE intensity P_{ICE} scales approximately linearly with the measured neutron flux from fusion reactions, and with the inferred concentration, n_{α}/n_{i}, of fusion born alpha particles confined within the plasma. We present fully nonlinear self-consistent kinetic simulations that reproduce this scaling for the first time. This resolves a long-standing question in the physics of fusion alpha-particle confinement and stability in magnetic confinement fusion plasmas. It confirms the magnetoacoustic cyclotron instability as the likely emission mechanism and greatly strengthens the basis for diagnostic exploitation of ICE in future burning plasmas.
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Recent measurements of microwave and x-ray emission during edge localized mode (ELM) activity in tokamak plasmas provide a fresh perspective on ELM physics. It is evident that electron kinetics, which are not incorporated in standard (fluid) models for the instability that drives ELMs, play a key role in the new observations. These effects should be included in future models for ELMs and the ELM cycle. The observed radiative effects paradoxically imply acceleration of electrons parallel to the magnetic field combined with rapid acquisition of perpendicular momentum. It is shown that this paradox can be resolved by the action of the anomalous Doppler instability which enables fast collective radiative relaxation, in the perpendicular direction, of electrons accelerated in the parallel direction by inductive electric fields generated by the initial ELM instability.
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The statistics of edge-localized plasma instabilities (ELMs) in toroidal magnetically confined fusion plasmas are considered. From first principles, standard experimentally motivated assumptions are shown to determine a specific probability distribution for the waiting times between ELMs: the Weibull distribution. This is confirmed empirically by a statistically rigorous comparison with a large data set from the Joint European Torus. The successful characterization of ELM waiting times enables future work to progress in various ways. Here we present a quantitative classification of ELM types, complementary to phenomenological approaches. It also informs us about the nature of ELM processes, such as whether they are random or deterministic. The methods are extremely general and can be applied to numerous other quasiperiodic intermittent phenomena.
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The relationship between simulated ion cyclotron emission (ICE) signals s and the corresponding 1D velocity distribution function fv⥠of the fast ions triggering the ICE is modeled using a two-layer deep neural network. The network architecture (number of layers and number of computational nodes in each layer) and hyperparameters (learning rate and number of learning iterations) are fine-tuned using a bottom-up approach based on cross-validation. Thus, the optimal mapping gs;θ of the neural network in terms of the number of nodes, the number of layers, and the values of the hyperparameters, where θ is the learned model parameters, is determined by comparing many different configurations of the network on the same training and test set and choosing the best one based on its average test error. The training and test sets are generated by computing random ICE velocity distribution functions f and their corresponding ICE signals s by modeling the relationship as the linear matrix equation Wf = s. The simulated ICE signals are modeled as edge ICE signals at LHD. The network predictions for f based on ICE signals s are on many simulated ICE signal examples closer to the true velocity distribution function than that obtained by 0th-order Tikhonov regularization, although there might be qualitative differences in which features one technique is better at predicting than the other. Additionally, the network computations are much faster. Adapted versions of the network can be applied to future experimental ICE data to infer fast-ion velocity distribution functions.
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An ion cyclotron emission (ICE) diagnostic is prepared for installation into the W7-X stellarator, with the aim to be operated in the 2022 experimental campaign. The design is based on the successful ICE diagnostic on the ASDEX Upgrade tokamak. The new diagnostic consists of four B-dot probes, mounted about 72° toroidally away (one module) from the neutral beam injector, with an unobstructed plasma view. Two of the B-dot probes are oriented parallel to the local magnetic field, aimed to detect fast magnetosonic waves. The remaining two probes are oriented poloidally, with the aim to detect slow waves. The radio frequency (RF) signals picked up by the probes are transferred via 50 Ω vacuum-compatible coaxial cables to RF detectors. Narrow band notch filters are used to protect the detectors from possible RF waves launched by the W7-X antenna. The signal will be sampled with a four-channel fast analog-to-digital converter with 14 bit depth and 1 GSample/s sampling rate. The diagnostic's phase-frequency characteristic is properly measured in order to allow measuring the wave vectors of the picked up waves.
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We present first principles simulations of the direct collisionless coupling of the free energy of fusion-born ions into electron current in a magnetically confined fusion plasma. These simulations demonstrate, for the first time, a key building block of some "alpha channeling" scenarios for tokamak experiments. Spontaneously excited obliquely propagating waves in the lower hybrid frequency range undergo Landau damping on resonant electrons, drawing out an asymmetric tail in the electron parallel velocity distribution, which carries a current.
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We use a well-known model [T. Vicsek, Phys. Rev. Lett. 15, 1226 (1995)] for flocking, to test mutual information as a tool for detecting order-disorder transitions, in particular when observations of the system are limited. We show that mutual information is a sensitive indicator of the phase transition location in terms of the natural dimensionless parameters of the system which we have identified. When only a few particles are tracked and when only a subset of the positional and velocity components is available, mutual information provides a better measure of the phase transition location than the susceptibility of the data.
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Confinement phenomenology characteristic of magnetically confined plasmas emerges naturally from a simple sandpile algorithm when the parameter controlling redistribution scale length is varied. Close analogs are found for enhanced confinement, edge pedestals, and edge localized modes (ELMs), and for the qualitative correlations between them. These results suggest that tokamak observations of avalanching transport are deeply linked to the existence of enhanced confinement and ELMs.
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A model for the solar coronal magnetic field is proposed where multiple directed loops evolve in space and time. Loops injected at small scales are anchored by footpoints of opposite polarity moving randomly on a surface. Nearby footpoints of the same polarity aggregate, and loops can reconnect when they collide. This may trigger a cascade of further reconnection, representing a solar flare. Numerical simulations show that a power law distribution of flare energies emerges, associated with a scale-free network of loops, indicating self-organized criticality.
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The surfatron offers the possibility of particle acceleration to arbitrarily high energies, given a sufficiently large system. Surfatron acceleration of electrons by waves excited by ions reflected from supernova remnant (SNR) shocks is investigated using particle simulations. It is shown that surfatron and stochastic acceleration could provide a seed population for the acceleration of cosmic ray electrons at SNR shocks.
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A simple one-dimensional sandpile model is constructed which possesses exact analytical solvability while displaying both scale-free behavior and fractal properties. The sandpile grows by avalanching on all scales, yet its shape and energy content are described by a simple, continuous (but nowhere differentiable) analytical formula. The avalanche energy distribution and the avalanche time series are both power laws with index -1 ("1/f spectra").