2018
DOI: 10.1103/physrevlett.121.025002
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Beam-Ion Acceleration during Edge Localized Modes in the ASDEX Upgrade Tokamak

Abstract: The acceleration of beam ions during edge localized modes (ELMs) in a tokamak is observed for the first time through direct measurements of fast-ion losses in low collisionality plasmas. The accelerated beamion population exhibits well-localized velocity-space structures which are revealed by means of tomographic inversion of the measurement, showing energy gains of the order of tens of keV. This suggests that the ion acceleration results from a resonant interaction between the beam ions and parallel electric … Show more

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Cited by 26 publications
(35 citation statements)
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“…The combined update steps from equations (1) and (2), and the use of a ranking function in assigning rewards, make DENSE a robust algorithm to simultaneously learn the weights and find the right architecture for a given problem. To illustrate this, we apply the method to ten distinct scientific simulation cases: inelastic x-ray Thomson scattering (XRTS) in high-energy-density physics [2,15], optical Thomson scattering (OTS) in laboratory astrophysics [16], tokamak edge-localised modes diagnostics (ELMs) in fusion energy science [3], x-ray emission spectroscopy (XES) in plasmas [17,18], galaxy halo occupation distribution modelling (Halo) in astrophysics [19], seismic tomography of the Shatsky Rise oceanic plateau (SeisTomo) [20], global aerosol-climate modelling using a general circulation model (GCM) in climate science [21], oceanic pelagic stoichiometry modelling (MOPS) in biogeochemistry [22], and neutron imaging (ICF JAG) and scalar measurements (ICF JAG Scalars) in inertial confinement fusion experiments [23].…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…The combined update steps from equations (1) and (2), and the use of a ranking function in assigning rewards, make DENSE a robust algorithm to simultaneously learn the weights and find the right architecture for a given problem. To illustrate this, we apply the method to ten distinct scientific simulation cases: inelastic x-ray Thomson scattering (XRTS) in high-energy-density physics [2,15], optical Thomson scattering (OTS) in laboratory astrophysics [16], tokamak edge-localised modes diagnostics (ELMs) in fusion energy science [3], x-ray emission spectroscopy (XES) in plasmas [17,18], galaxy halo occupation distribution modelling (Halo) in astrophysics [19], seismic tomography of the Shatsky Rise oceanic plateau (SeisTomo) [20], global aerosol-climate modelling using a general circulation model (GCM) in climate science [21], oceanic pelagic stoichiometry modelling (MOPS) in biogeochemistry [22], and neutron imaging (ICF JAG) and scalar measurements (ICF JAG Scalars) in inertial confinement fusion experiments [23].…”
Section: Resultsmentioning
confidence: 99%
“…For example, fast and accurate simulations promise to speed up new materials and drug discovery [1] by allowing rapid screening and ideas testing. Accelerated simulations also open up novel possibilities for online diagnostics for cases like x-ray scattering in plasma physics experiments [2] and to monitor edge-localized modes in magnetic confinement fusion [3], enabling real-time prediction-based experimental control and optimization. However, for such applications to be successful the simulations need not only be fast but also accurate; achieving both to the level required for advanced applications remains an active objective of current research.…”
Section: Introductionmentioning
confidence: 99%
“…The combined update steps from equations (1) and (2), and the use of a ranking function in assigning rewards, make DENSE a robust algorithm to simultaneously learn the weights and find the right architecture for a given problem. To illustrate this, we apply the method to ten distinct scientific simulation cases: inelastic x-ray Thomson scattering (XRTS) in high-energydensity physics, 2,14 optical Thomson scattering (OTS) in laboratory astrophysics, 15 tokamak edge-localised modes diagnostics (ELMs) in fusion energy science, 3 x-ray emission spectroscopy (XES) in plasmas, 16,17 galaxy halo occupation distribution modelling (Halo) in astrophysics, 18 seismic tomography of the Shatsky Rise oceanic plateau (SeisTomo), 19 global aerosol-climate modelling using a general circulation model (GCM) in climate science, 20 oceanic pelagic stoichiometry modelling (MOPS) in biogeochemistry, 21 and neutron imaging (ICF JAG) and scalar measurements (ICF JAG Scalars) in inertial confinement fusion experiments. 22 The tested simulations have ranging numbers of input parameters from 3 to 14 and outputs from 0D (scalars) to multiple 3D signals.…”
Section: Resultsmentioning
confidence: 99%
“…For example, fast and accurate simulations promise to speed up new materials and drug discovery 1 by allowing rapid screening and ideas testing. Accelerated simulations also open up novel possibilities for online diagnostics for cases like x-ray scattering in plasma physics experiments 2 and to monitor edge-localized modes in magnetic confinement fusion, 3 enabling real-time predictionbased experimental control and optimization. However, for such applications to be successful the simulations need not only be fast but also accurate; achieving both to the level required for advanced applications remains an active objective of current research.…”
Section: Introductionmentioning
confidence: 99%
“…Measurements of microwave bursts were obtained on MAST 42 , suggesting that electrons are accelerated at the beginning of the ELM, presumably by electric fields that could be created by magnetic reconnection of the filaments. On the Axially Symmetric Divertor Experiment (ASDEX) Upgrade (AUG) tokamak, accelerated fast ions were also measured, together with soft X-ray and electron cyclotron emission bursts at the beginning of the ELMs 43,44 , consistent with a reconnection event resulting in particle acceleration.…”
Section: Box 1 | Equilibrium Pressure and Current Profiles And Tokammentioning
confidence: 99%