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# Fusion

11.01.2021
06:20 Validity of models for Dreicer generation of runaway electrons in dynamic scenarios. (arXiv:2101.02740v1 [physics.plasm-ph])

Runaway electron modelling efforts are motivated by the threat these energetic particles pose to large fusion devices. The sophisticated kinetic models can now capture most features of the runaway electron generation but have high computational costs which can be avoided by using cheaper reduced kinetic codes. In this paper, we compare the reduced kinetic and kinetic models to determine when the former solvers, based on analytical calculations assuming quasi-stationarity, can be used. The Dreicer generation rate is calculated by two different solvers in parallel in a workflow developed in the European Integrated Modeling framework, and this is complemented by calculations of a third code that is not yet integrated into the framework. Runaway Fluid, a reduced kinetic code, NORSE, a kinetic code using non-linear collision operator, and DREAM, a linearized Fokker-Planck solver, are used to investigate the effect of a dynamic change in the electric field for different plasma scenarios

08.01.2021
11:09 COVID19-HPSMP: COVID-19 Adopted Hybrid and Parallel Deep Information Fusion Framework for Stock Price Movement Prediction. (arXiv:2101.02287v1 [q-fin.ST])

The novel of coronavirus (COVID-19) has suddenly and abruptly changed the world as we knew at the start of the 3rd decade of the 21st century. Particularly, COVID-19 pandemic has negatively affected financial econometrics and stock markets across the globe. Artificial Intelligence (AI) and Machine Learning (ML)-based prediction models, especially Deep Neural Network (DNN) architectures, have the potential to act as a key enabling factor to reduce the adverse effects of the COVID-19 pandemic and future possible ones on financial markets. In this regard, first, a unique COVID-19 related PRIce MOvement prediction (COVID19 PRIMO) dataset is introduced in this paper, which incorporates effects of social media trends related to COVID-19 on stock market price movements. Afterwards, a novel hybrid and parallel DNN-based framework is proposed that integrates different and diversified learning architectures. Referred to as the COVID-19 adopted Hybrid and Parallel deep fusion framework for Stock

07:20 COVID19-HPSMP: COVID-19 Adopted Hybrid and Parallel Deep Information Fusion Framework for Stock Price Movement Prediction. (arXiv:2101.02287v1 [q-fin.ST])

The novel of coronavirus (COVID-19) has suddenly and abruptly changed the world as we knew at the start of the 3rd decade of the 21st century. Particularly, COVID-19 pandemic has negatively affected financial econometrics and stock markets across the globe. Artificial Intelligence (AI) and Machine Learning (ML)-based prediction models, especially Deep Neural Network (DNN) architectures, have the potential to act as a key enabling factor to reduce the adverse effects of the COVID-19 pandemic and future possible ones on financial markets. In this regard, first, a unique COVID-19 related PRIce MOvement prediction (COVID19 PRIMO) dataset is introduced in this paper, which incorporates effects of social media trends related to COVID-19 on stock market price movements. Afterwards, a novel hybrid and parallel DNN-based framework is proposed that integrates different and diversified learning architectures. Referred to as the COVID-19 adopted Hybrid and Parallel deep fusion framework for Stock

07:08 Depolarization of Spin-Polarized hydrogen via Spin-Exchange Collisions with chlorine Atoms at Ultrahigh Density. (arXiv:2101.02675v1 [physics.atom-ph])

Recently, the production of ultrahigh-density ($>10^{19} cm^{-3}$) spin-polarized D atoms was demonstrated, from the photodissociation of deuterium iodide, but the upper density limit was not determined. Here, we present studies of spin-polarized hydrogen (SPH) densities up to $10^{20}$\si{\per\centi\meter\cubed}, by photodissociating 5 bar of hydrogen chloride with a focused 213 nm, 150 ps laser pulse. We extract the depolarization cross-section of hydrogen and chlorine atom collisions, which is the main depolarization mechanism at this high-density regime, to be $\sigma_{H-Cl}=7(2)\times10^{-17}$\si{\centi\meter\squared}. We discuss the conditions under which SPH densities of $10^{20}$\si{\per\centi\meter\cubed} can be reached, and the potential applications to ultrafast magnetometry, laser-ion acceleration, and tests of polarized nuclear fusion.

07:08 Modelling of runaway electron dynamics during argon-induced disruptions in ASDEX Upgrade and JET. (arXiv:2101.02575v1 [physics.plasm-ph])

Disruptions in tokamak plasmas may lead to the generation of runaway electrons that have the potential to damage plasma-facing components. Improved understanding of the runaway generation process requires interpretative modelling of experiments. In this work we simulate eight discharges in the ASDEX Upgrade and JET tokamaks, where argon gas was injected to trigger the disruption. We use a fluid modelling framework with the capability to model the generation of runaway electrons through the hot-tail, Dreicer and avalanche mechanisms, as well as runaway electron losses. Using experimentally based initial values of plasma current and electron temperature and density, we can reproduce the plasma current evolution using realistic assumptions about temperature evolution and assimilation of the injected argon in the plasma. The assumptions and results are similar for the modelled discharges in ASDEX Upgrade and JET, indicating that the implemented models are applicable to machines of varying

07.01.2021
18:20 Nuclear fusion group calls for US to construct pilot plant by 2040s or risk falling behind other nations

A group of leading nuclear fusion scientists and researchers has submitted a report to the Department of Energy calling for a nuclear fusion pilot plant to be constructed and operational in the US by the 2040s. Read Full Article at RT.com

09:42 Real-Space Green's functions for Warm Dense Matter. (arXiv:2101.02088v1 [physics.plasm-ph])

Accurate modeling of the electronic structure of warm dense matter is a challenging problem whose solution would allow a better understanding of material properties like equation of state, opacity, and conductivity, with resulting applications from astrophysics to fusion energy research. Here we explore the real-space Green's function method as a technique for solving the Kohn-Sham density functional theory equations under warm dense matter conditions. We find the method to be tractable and accurate throughout the density and temperature range of interest, in contrast to other approaches. Good agreement on equation of state is found when comparing to other methods, where they are thought to be accurate.

09:42 Role of wave-particle resonance in turbulent transport in toroidal plasmas. (arXiv:2101.01924v1 [physics.plasm-ph])

Wave-particle interaction in toroidal plasmas is an essential transport mechanism in drift wave instability-driven microturbulence. In tokamkas, different wave-particle resonance conditions have been found important for the energy and particle transport of multiple species in various drift wave turbulences. To confirm the transport mechanism for electrons and ions in tokamak drift-wave instabilities, the effect of wave-particle resonance on turbulent transport is studied using global gyrokinetic particle simulations of the plasma core ion temperature gradient (ITG) and collisionless trapped electron mode (CTEM) turbulence. Simulation results show that in CTEM and ITG turbulence, electron transport is primarily regulated by wave-particle linear resonance, and the ion transport is regulated by nonlinear wave-particle decorrelation.

09:42 WEST operation with real time feed back control based on wall component temperature toward machine protection in a steady state tungsten environment. (arXiv:2101.01914v1 [physics.plasm-ph])

A real time Wall Monitoring System (WMS) is used on the WEST tokamak during the C4 experimental campaign. The WMS uses the wall surface temperatures from 6 fields of view of the Infrared viewing system. It extracts the raw digital data from selected areas, converts it to temperatures using the calibration and write it on the shared memory network being used by the Plasma Control System (PCS). The PCS feeds back to actuators, namely the injected power from 5 antennae's of the lower hybrid and ion cyclotron resonance radiofrequency (RF) heating systems. WMS activates feed back control 63 times during C4, which is 14% of the plasma discharges. It activates mainly as the result of a direct RF loss to the upper divertor pipes. The feedback control maintains the wall temperature within the operation envelope during 97% of the occurrences, while enabling plasma discharge continuation. The false positive rate establishes at 0.2%. WMS significantly facilitated the operation path to high power

09:42 Simulations of COMPASS Vertical Displacement Events with a self-consistent model for halo currents including neutrals and sheath boundary conditions. (arXiv:2101.01755v1 [physics.plasm-ph])

The understanding of the halo current properties during disruptions is key to design and operate large scale tokamaks in view of the large thermal and electromagnetic loads that they entail. For the first time, we present a fully self-consistent model for halo current simulations including neutral particles and sheath boundary conditions. The model is used to simulate Vertical Displacement Events (VDEs) occurring in the COMPASS tokamak. Recent COMPASS experiments have shown that the parallel halo current density at the plasma-wall interface is limited by the ion saturation current during VDE-induced disruptions. We show that usual MHD boundary conditions can lead to the violation of this physical limit and we implement this current density limitation through a boundary condition for the electrostatic potential. Sheath boundary conditions for the density, the heat flux, the parallel velocity and a realistic parameter choice (e.g. Spitzer $\eta$ and Spitzer-H\"arm $\chi_\parallel$

09:42 Blocks-in-Conduit: REBCO cable for a 20T@20K toroid for compact fusion tokamaks. (arXiv:2101.01754v1 [physics.acc-ph])

Blocks-in-Conduit is a novel approach to cable, coil, and splice technologies with unique benefits for a high-current-den-sity toroid D winding to operate at 20 T, 20 K. Blocks of REBCO tape are cabled in conduit, with a thin-wall center-tube spring that provides transposition, stress management at the cable level, and cross-flow cooling of a thick-coil toroid winding. The coil technology utilizes a co-wound armor structure that integrates stress manage-ment and cross-flow cooling and bypasses coil stress to protect the BIC. An interleaved splice joint enables low-resistance demountable splices of the windings. These provisions yield maximum current density in the winding pack, maximum stability of the REBCO tape blocks, and minimum conductor cost for a tokamak toroid.

00:10 Nuclear fusion group calls for building a pilot plant by the 2040s

The main criticism about nuclear fusion has been that its vast potential as a commercial source of energy has always been just out of reach.

06.01.2021
05:24 CNN-Driven Quasiconformal Model for Large Deformation Image Registration. (arXiv:2011.00731v2 [cs.CV] CROSS LISTED)

Image registration has been widely studied over the past several decades, with numerous applications in science, engineering and medicine. Most of the conventional mathematical models for large deformation image registration rely on prescribed landmarks, which usually require tedious manual labeling and are prone to error. In recent years, there has been a surge of interest in the use of machine learning for image registration. However, most learning-based methods cannot ensure the bijectivity of the registration, which makes it difficult to establish a 1-1 correspondence between the images. In this paper, we develop a novel method for large deformation image registration by a fusion of convolutional neural network (CNN) and quasiconformal theory. More specifically, we propose a new fidelity term for incorporating the CNN features in our quasiconformal energy minimization model, which enables us to obtain meaningful registration results without prescribing any landmarks. Moreover,

05.01.2021
07:55 CNN-Driven Quasiconformal Model for Large Deformation Image Registration. (arXiv:2011.00731v2 [cs.CV] UPDATED)

Image registration has been widely studied over the past several decades, with numerous applications in science, engineering and medicine. Most of the conventional mathematical models for large deformation image registration rely on prescribed landmarks, which usually require tedious manual labeling and are prone to error. In recent years, there has been a surge of interest in the use of machine learning for image registration. However, most learning-based methods cannot ensure the bijectivity of the registration, which makes it difficult to establish a 1-1 correspondence between the images. In this paper, we develop a novel method for large deformation image registration by a fusion of convolutional neural network (CNN) and quasiconformal theory. More specifically, we propose a new fidelity term for incorporating the CNN features in our quasiconformal energy minimization model, which enables us to obtain meaningful registration results without prescribing any landmarks. Moreover,

01.01.2021
11:51 Understanding and Improving Encoder Layer Fusion in Sequence-to-Sequence Learning. (arXiv:2012.14768v1 [cs.CL])

Encoder layer fusion (EncoderFusion) is a technique to fuse all the encoder layers (instead of the uppermost layer) for sequence-to-sequence (Seq2Seq) models, which has proven effective on various NLP tasks. However, it is still not entirely clear why and when EncoderFusion should work. In this paper, our main contribution is to take a step further in understanding EncoderFusion. Many of previous studies believe that the success of EncoderFusion comes from exploiting surface and syntactic information embedded in lower encoder layers. Unlike them, we find that the encoder embedding layer is more important than other intermediate encoder layers. In addition, the uppermost decoder layer consistently pays more attention to the encoder embedding layer across NLP tasks. Based on this observation, we propose a simple fusion method, SurfaceFusion, by fusing only the encoder embedding layer for the softmax layer. Experimental results show that SurfaceFusion outperforms EncoderFusion on several

11:38 Disruption Avoidance via RF Current Condensation in Magnetic Islands Produced by Off-Normal Events. (arXiv:2012.15389v1 [physics.plasm-ph])

As tokamaks are designed and built with increasing levels of stored energy in the plasma, disruptions become increasingly dangerous. It has been reported that 95% of the disruptions in the Joint European Torus (JET) tokamak with the ITER-like wall are preceded by the growth of large locked islands, and these large islands are mostly produced by off-normal events other than neoclassical tearing modes. This paper discusses the use of RF current drive to stabilize large islands, focusing on nonlinear effects that appear when relatively high powers are used to stabilize large islands. An RF current condensation effect can concentrate the RF driven current near the center of the island, increasing the efficiency of the stabilization. A nonlinear shadowing effect can hinder the stabilization of islands if the aiming of the ray trajectories does not properly consider the nonlinear effects.

11:38 On a fusion chain reaction via suprathermal ions in high-density H-$^{11}$B plasma. (arXiv:2012.14533v1 [physics.plasm-ph])

The $^{11}$B$(p,\alpha)2\alpha$ fusion reaction is particularly attractive for energy production purposes because of its aneutronic character and the absence of radioactive species among reactants and products. Its exploitation in the thermonuclear regime, however, appears to be prohibitive due to the low reactivity of the $^{11}$B fuel at temperatures up to 100 keV. A fusion chain sustained by elastic collisions between the alpha particles and fuel ions, this way scattered to suprathermal energies, has been proposed as a possible route to overcome this limitation. Based on a simple model, this work investigates the reproduction process in an infinite, non-degenerate $^{11}$B plasma, in a wide range of densities and temperatures which are of interest for laser-driven experiments ($10^{24} \lesssim n_e \lesssim 10^{28} {\rm cm}^{-3}$, $T_e \lesssim 100$ keV, $T_i \sim$ 1 keV). In particular, cross section data for the $\alpha$-$p$ scattering which include the nuclear interaction have

30.12.2020
18:21 Development of fusion energy

Physicists are working to develop a unique tokamak fusion device called 'SPARC.'

29.12.2020
15:29 2020 in review: Nuclear fusion power is slowly getting closer

While progress has been made on nuclear fusion, efforts to harness the process that powers the sun were delayed by the coronavirus pandemic, so the energy source remains decades away

09:36 Korean Artificial Sun Breaks New Operational Record, Reaches more than 100 Million Degrees Celsius

On 24 November, the KSTAR Research Centre at the Korea Institute of Fusion Energy (KFE) had announced a

05:40 DeepSurfels: Learning Online Appearance Fusion. (arXiv:2012.14240v1 [cs.CV])

We present DeepSurfels, a novel hybrid scene representation for geometry and appearance information. DeepSurfels combines explicit and neural building blocks to jointly encode geometry and appearance information. In contrast to established representations, DeepSurfels better represents high-frequency textures, is well-suited for online updates of appearance information, and can be easily combined with machine learning methods. We further present an end-to-end trainable online appearance fusion pipeline that fuses information provided by RGB images into the proposed scene representation and is trained using self-supervision imposed by the reprojection error with respect to the input images. Our method compares favorably to classical texture mapping approaches as well as recently proposed learning-based techniques. Moreover, we demonstrate lower runtime, improved generalization capabilities, and better scalability to larger scenes compared to existing methods.

05:40 Human Expression Recognition using Facial Shape Based Fourier Descriptors Fusion. (arXiv:2012.14097v1 [cs.CV])

Dynamic facial expression recognition has many useful applications in social networks, multimedia content analysis, security systems and others. This challenging process must be done under recurrent problems of image illumination and low resolution which changes at partial occlusions. This paper aims to produce a new facial expression recognition method based on the changes in the facial muscles. The geometric features are used to specify the facial regions i.e., mouth, eyes, and nose. The generic Fourier shape descriptor in conjunction with elliptic Fourier shape descriptor is used as an attribute to represent different emotions under frequency spectrum features. Afterwards a multi-class support vector machine is applied for classification of seven human expression. The statistical analysis showed our approach obtained overall competent recognition using 5-fold cross validation with high accuracy on well-known facial expression dataset.

05:40 You Have a Point There: Object Selection Inside an Automobile Using Gaze, Head Pose and Finger Pointing. (arXiv:2012.13449v1 [cs.HC])

Sophisticated user interaction in the automotive industry is a fast emerging topic. Mid-air gestures and speech already have numerous applications for driver-car interaction. Additionally, multimodal approaches are being developed to leverage the use of multiple sensors for added advantages. In this paper, we propose a fast and practical multimodal fusion method based on machine learning for the selection of various control modules in an automotive vehicle. The modalities taken into account are gaze, head pose and finger pointing gesture. Speech is used only as a trigger for fusion. Single modality has previously been used numerous times for recognition of the user's pointing direction. We, however, demonstrate how multiple inputs can be fused together to enhance the recognition performance. Furthermore, we compare different deep neural network architectures against conventional Machine Learning methods, namely Support Vector Regression and Random Forests, and show the enhancements in

00:34 Fusion Reactor Sets Record By Running for 20 Seconds

A team from South Korea just made a major advancement -- the Korea Superconducting Tokamak Advanced Research (KSTAR) device recently ran for 20 seconds. That might not sound impressive, but it doubles the previous record.  The post Fusion Reactor Sets Record By Running for 20 Seconds appeared first on ExtremeTech.

28.12.2020
17:54 Korean artificial sun sets the new world record of 20-sec-long operation at 100 million degrees

The Korea Superconducting Tokamak Advanced Research (KSTAR), a superconducting fusion device also known as the Korean artificial sun, set the new world record as it succeeded in maintaining the high temperature plasma for 20 seconds with an ion temperature over 100 million degrees (Celsius). On November 24 (Tuesday), the KSTAR Research Center at the Korea Institute of Fusion Energy (KFE) announced that in a joint research with the Seoul National University (SNU) and Columbia University of the United States, it succeeded in continuous operation of plasma for 20 seconds with an ion-temperature higher than 100 million degrees, which is one of the core conditions of nuclear fusion in the 2020 KSTAR Plasma Campaign.

24.12.2020
20:54 Korean artificial sun sets the new world record of 20-sec-long operation at 100 million degrees

The Korea Superconducting Tokamak Advanced Research(KSTAR), a superconducting fusion device also known as the Korean artificial sun, set the new world record as it succeeded in maintaining the high temperature plasma for 20 seconds with an ion temperature over 100 million degrees.

05:05 Theoretical description of chirping waves using phase-space waterbags. (arXiv:2012.12504v1 [physics.plasm-ph])

The guiding centre dynamics of fast particles can alter the behaviour of energetic particle driven modes with chirping frequencies. In this paper, the applicability of an earlier trapped/passing locus model [H. Hezaveh et al 2017 Nucl. Fusion 57 126010] has been extended to regimes where the wave trapping region can expand and trap ambient particles. This extension allows the study of waves with up-ward and down-ward frequency chirping across the full range of energetic particle orbits. Under the adiabatic approximation, the phase-space of energetic particles is analysed by a Lagrangian contour approach where the islands are discretised using phase-space waterbags. In order to resolve the dynamics during the fast formation of phase-space islands and find an appropriate initialisation for the system, full-scale modelling is implemented using the bump-on-tail (BOT) code. In addition to investigating the evolution of chirping waves with deepening potentials in a single resonance, we

23.12.2020
07:37 Comparison of local and global gyrokinetic calculations of collisionless zonal flow damping in quasi-symmetric stellarators. (arXiv:2012.12213v1 [physics.plasm-ph])

The linear collisionless damping of zonal flows is calculated for quasi-symmetric stellarator equilibria in flux-tube, flux-surface, and full-volume geometry. Equilibria are studied from the quasi-helical symmetry configuration of the Helically Symmetric eXperiment (HSX), a broken symmetry configuration of HSX, and the quasi-axial symmetry geometry of the National Compact Stellarator eXperiment (NCSX). Zonal flow oscillations and long-time damping affect the zonal flow evolution, and the zonal flow residual goes to zero for small radial wavenumber. The oscillation frequency and damping rate depend on the bounce-averaged radial particle drift in accordance with theory. While each flux tube on a flux surface is unique, several different flux tubes in HSX or NCSX can reproduce the zonal flow damping from a flux-surface calculation given an adequate parallel extent. The flux-surface or flux-tube calculations can accurately reproduce the full-volume long-time residual for moderate $k_x$,

07:37 Implementation of higher-order velocity mapping between marker particles and grid in the particle-in-cell code XGC. (arXiv:2012.11764v1 [physics.plasm-ph])

The global total-$f$ gyrokinetic particle-in-cell code XGC, used to study transport in magnetic fusion plasmas, implements a continuum grid to perform the dissipative operations, such as plasma collisions. To transfer the distribution function between marker particles and a rectangular velocity-space grid, XGC employs a bilinear mapping. The conservation of particle density and momentum is accurate enough in this bilinear operation, but the error in the particle energy conservation can become undesirably large in special conditions. In the present work we update XGC to use a novel mapping technique, based on the calculation of a pseudo-inverse, to exactly preserve moments up to the order of the discretization space. We describe the details of the implementation and we demonstrate the reduced interpolation error for a neoclassical tokamak test case by using $1^{\mathrm{st}}$- and $2^{\mathrm{nd}}$-order elements with the pseudo-inverse method and comparing to the bilinear mapping.

22.12.2020
10:22 Dual-energy CT Reconstruction from Dual Quarter Scans. (arXiv:2012.11374v1 [physics.med-ph])

Compared with conventional single-energy computed tomography (CT), dual-energy CT (DECT) provides better material differentiation but most DECT imaging systems require dual full-angle projection data at different X-ray spectra. Relaxing the requirement of data acquisition is a particularly attractive research to promote the applications of DECT in a wide range of imaging areas. In this work, we design a novel DECT imaging scheme with dual quarter scans and propose an efficient method to reconstruct the desired DECT images from dual limited-angle projection data, which enables DECT on imaging configurations with half-scan and largely reduces scanning angles and radiation doses. We first study the characteristics of image artifacts under dual quarter scans scheme, and find that the directional limited-angle artifacts of DECT images are complementarily distributed in image domain because the corresponding X-rays of high- and low-energy scans are orthogonal. Inspired by this finding, a

10:22 Constructing a new predictive scaling formula for ITER's divertor heat-load width informed by a simulation-anchored machine learning. (arXiv:2012.10750v1 [physics.plasm-ph])

Understanding and predicting divertor heat-load width $\lambda_q$ is a critically important problem for an easier and more robust operation of ITER. Previous predictive simulation data using the extreme-scale edge gyrokinetic code XGC1 in the electrostatic limit for $\lambda_q$ under attached divertor plasma conditions in three major US tokamaks [C. S. Chang et al., Nucl. Fusion 57, 116023 (2017)] reproduced the Eich and Goldston attached-divertor formula results [T. Eich et al., Phys. Rev. Lett. 107, 215001 (2011); R.J. Goldston, Nucl. Fusion 52, 013009 (2012)], and furthermore predicted over six times wider $\lambda_q^{XGC}$ than the maximal Eich and Goldston formula predictions on a full-current scenario ITER plasma. After adding data from further predictive simulations on a highest current JET and highest-current Alcator C-Mod, a machine learning program is used to identify a new scaling formula for $\lambda_q$ as a simple modification to the Eich formula(14), which reproduces the

21.12.2020
05:42 Gradient-based optimization of 3D MHD equilibria. (arXiv:2012.10028v1 [physics.plasm-ph])

Using recently developed adjoint methods for computing the shape derivatives of functions that depend on MHD equilibria (Antonsen et al.2019; Paul et al.2020), we present the first example of analytic gradient-based optimization of fixed-boundary stellarator equilibria. We take advantage of gradient-based information for the rotational transform, magnetic well, and quasisymmetry near the axis. Because the cost of computing the gradient becomes independent of the dimensionality of the space, we are able to optimize in higher-dimensional spaces than previous optimization efforts. We include novel regularization terms that prevent self-intersection of the plasma boundary. This work has enabled the identification of several configurations, including an equilibrium with very low magnetic shear throughout the volume.

18.12.2020
06:16 Combined plasma-coil optimization algorithms. (arXiv:2012.09278v1 [physics.plasm-ph])

Combined plasma-coil optimization approaches for designing stellarators are discussed and a new method for calculating free-boundary equilibria is proposed. Four distinct categories of stellarator optimization, two of which are novel approaches, are the fixed-boundary optimization, the generalized fixed-boundary optimization, the quasi free-boundary optimization, and the free-boundary (coil) optimization. These are described using the multi-region relaxed magnetohydrodynmics (MRxMHD) energy functional, the Biot-Savart integral, the coil-penalty functional and the virtual casing integral, and their derivatives. The proposed free-boundary equilibrium calculation differs from existing methods in how the boundary-value problem is posed, and for the new approach it seems that there is not an associated energy minimization principle because a non-symmetric functional arises. We propose to solve the weak formulation of this problem using a spectral-Galerkin method, and this will reduce the

17.12.2020
08:48 A comparison of source term estimators in coupled finite-volume/Monte-Carlo methods with applications to plasma edge simulations in nuclear fusion. (arXiv:2012.08981v1 [math.NA])

In many applications, such as plasma edge simulation of a nuclear fusion reactor, a coupled PDE/kinetic description is required, which is usually solved with a coupled finite-volume/Monte-Carlo method. Different procedures have been proposed to estimate the source terms in the finite volume part that appear from the Monte Carlo part of the simulation. In this paper, we present a systematic comparison of the variance and computational cost of a coherent set of such estimation procedures. We compare the different estimation procedures for mass in a simplified forward-backward scattering model problem, where an analytical comparison is possible, and for mass and momentum in a model problem with realistic scattering. Our results reveal a non-trivial dependence of the optimal choice of estimator on the model parameters and show that different estimation procedures prevail for different quantities of interest.

08:48 Shifting and splitting of resonance lines due to dynamical friction in plasmas. (arXiv:2012.08661v1 [physics.plasm-ph])

A quasilinear plasma transport theory that incorporates Fokker-Planck dynamical friction (drag) and scattering is self-consistently derived from first principles for an isolated, marginally-unstable mode resonating with an energetic minority species. It is found that drag fundamentally changes the structure of the wave-particle resonance, breaking its symmetry and leading to the shifting and splitting of resonance lines. In contrast, scattering broadens the resonance in a symmetric fashion. Comparison with fully nonlinear simulations shows that the proposed quasilinear system preserves the exact instability saturation amplitude and the corresponding particle redistribution of the fully nonlinear theory. Even though drag is shown to lead to a relatively small resonance shift, it underpins major changes in the redistribution of resonant particles. These findings suggest that drag can play a key role in modeling the energetic particle confinement in future burning fusion plasmas.

08:48 A comparison of source term estimators in coupled finite-volume/Monte-Carlo methods with applications to plasma edge simulations in nuclear fusion. (arXiv:2012.08981v1 [math.NA])

In many applications, such as plasma edge simulation of a nuclear fusion reactor, a coupled PDE/kinetic description is required, which is usually solved with a coupled finite-volume/Monte-Carlo method. Different procedures have been proposed to estimate the source terms in the finite volume part that appear from the Monte Carlo part of the simulation. In this paper, we present a systematic comparison of the variance and computational cost of a coherent set of such estimation procedures. We compare the different estimation procedures for mass in a simplified forward-backward scattering model problem, where an analytical comparison is possible, and for mass and momentum in a model problem with realistic scattering. Our results reveal a non-trivial dependence of the optimal choice of estimator on the model parameters and show that different estimation procedures prevail for different quantities of interest.

16.12.2020
19:18 Characterising cold fusion in 2-D models

Progress towards 'cold fusion,' where nuclear fusion can occur at close to room temperatures, has now been at a standstill for decades. However, an increasing number of studies are now proposing that the reaction could be triggered more easily through a mechanism involving muons—elementary particles with the same charge as electrons, but with around 200 times their mass. Through a study published in EPJ D, researchers led by Francisco Caruso at the Brazilian Centre for Physical Research have shown theoretically how this process would unfold within 2-D systems, without any need for approximations.

11:28 Probing ultrafast laser plasma processes inside solids with resonant small-angle X-ray scattering. (arXiv:2012.07922v1 [physics.plasm-ph])

Extreme states of matter exist throughout the universe e.g. inside planetary cores, stars or astrophysical jets. Such conditions are generated in the laboratory in the interaction of powerful lasers with solids, and their evolution can be probed with femtosecond precision using ultra-short X-ray pulses to study laboratory astrophysics, laser-fusion research or compact particle acceleration. X-ray scattering (SAXS) patterns and their asymmetries occurring at X-ray energies of atomic bound-bound transitions contain information on the volumetric nanoscopic distribution of density, ionization and temperature. Buried heavy ion structures in high intensity laser irradiated solids expand on the nanometer scale following heat diffusion, and are heated to more than 2 million Kelvin. These experiments demonstrate resonant SAXS with the aim to better characterize dynamic processes in extreme laboratory plasmas.

11:28 FCFR-Net: Feature Fusion based Coarse-to-Fine Residual Learning for Monocular Depth Completion. (arXiv:2012.08270v1 [cs.CV])

Depth completion aims to recover a dense depth map from a sparse depth map with the corresponding color image as input. Recent approaches mainly formulate the depth completion as a one-stage end-to-end learning task, which outputs dense depth maps directly. However, the feature extraction and supervision in one-stage frameworks are insufficient, limiting the performance of these approaches. To address this problem, we propose a novel end-to-end residual learning framework, which formulates the depth completion as a two-stage learning task, i.e., a sparse-to-coarse stage and a coarse-to-fine stage. First, a coarse dense depth map is obtained by a simple CNN framework. Then, a refined depth map is further obtained using a residual learning strategy in the coarse-to-fine stage with coarse depth map and color image as input. Specially, in the coarse-to-fine stage, a channel shuffle extraction operation is utilized to extract more representative features from color image and coarse depth

15.12.2020
07:07 Fusion of Range and Stereo Data for High-Resolution Scene-Modeling. (arXiv:2012.06769v1 [cs.CV])

This paper addresses the problem of range-stereo fusion, for the construction of high-resolution depth maps. In particular, we combine low-resolution depth data with high-resolution stereo data, in a maximum a posteriori (MAP) formulation. Unlike existing schemes that build on MRF optimizers, we infer the disparity map from a series of local energy minimization problems that are solved hierarchically, by growing sparse initial disparities obtained from the depth data. The accuracy of the method is not compromised, owing to three properties of the data-term in the energy function. Firstly, it incorporates a new correlation function that is capable of providing refined correlations and disparities, via subpixel correction. Secondly, the correlation scores rely on an adaptive cost aggregation step, based on the depth data. Thirdly, the stereo and depth likelihoods are adaptively fused, based on the scene texture and camera geometry. These properties lead to a more selective growing

14.12.2020
17:01 World's Largest Fusion Reactor Begins Assembly

The pieces are finally coming together on the long-delayed ITER experiment to create nuclear fusion -- Read more on ScientificAmerican.com

16:13 Towards "An Artificial Sun" - Will China Win The Nuclear Fusion Race?

China is on a quest for world domination. Beijing has been making assertive moves into global energy markets for a while now, stepping into energy market power vacuums in largely untapped markets around the world. Chinese president Xi Jinping has made major inroads with his ambitious Belt and Road Initiative, started in 2013, which is a massive-scale, globe-spanning infrastructure development program that now includes approximately 70 countries and international organizations. Beijing has a lot of irons in the global energy market fire, facing off against Russia for nuclear energy dominance in Africa, ramping up coal-fired capacity abroad while simultaneously touting its lofty decarbonization plans back at home, and now, powering up a brand new, cutting-edge “artificial sun.”

09:41 Nonresonant Diffusion in Alpha Channeling. (arXiv:2012.06532v1 [physics.plasm-ph])

The gradient of fusion-born alpha particles that arises in a fusion reactor can be exploited to amplify waves, which cool the alpha particles while diffusively extracting them from the reactor. The corresponding extraction of the resonant alpha particle charge has been suggested as a mechanism to drive rotation. By deriving a coupled linear-quasilinear theory of alpha channeling, we show that, for a time-growing wave with a purely poloidal wavevector, a current in the nonresonant ions cancels the resonant alpha particle current, preventing the rotation drive but fueling the fusion reaction.

09:13 £453,000 grant awarded to boost research and development for COVID-19 antibodies

Fusion Antibodies, pre-clinical antibody discovery, engineering and supply experts, and Queen’s University Belfast, leader in innovation and impact, have been awarded a £453,000 grant from Invest Northern Ireland to further expand their COVID-19 targeted research and development efforts.

11.12.2020
10:30 Global linear and nonlinear gyrokinetic modelling of Alfv\'en eigenmodes in ITER. (arXiv:2012.05651v1 [physics.plasm-ph])

Linear and nonlinear modelling of Alfv\'enic instabilities, most notably toroidal Alfv\'en eigenmodes (TAEs), obtained by using the global nonlinear electromagnetic gyrokinetic model of the code ORB5 are presented for the 15 MA scenario of the ITER tokamak. Linear simulations show that elliptic Alfv\'en eigenmodes and odd-parity TAEs are only weakly damped but not excited by alpha particles, whose drive favours even-parity TAEs. Low mode number TAEs are found to be global, requiring global treatment. Nonlinearly, even with double the nominal EP density, single mode simulations lead to saturation with negligible EP transport however multi-mode simulations predict that with double the nominal EP density, enhanced saturation and significant EP redistribution will occur.

10:30 Magnetic Field Transport in Propagating Thermonuclear Burn. (arXiv:2012.05280v1 [physics.plasm-ph])

High energy gain in inertial fusion schemes requires the propagation of a thermonuclear burn wave from hot to cold fuel. We consider the problem of burn propagation when a magnetic field is orthogonal to the burn wave. Using an extended-MHD model with a magnetized $\alpha$ energy transport equation we find that the magnetic field can reduce the rate of burn propagation by suppressing electron thermal conduction and $\alpha$ particle flux. Magnetic field transport during burn propagation is subject to competing effects: field can be advected from cold to hot regions by ablation of cold fuel, while the Nernst and $\alpha$ particle flux effects transport field from hot to cold fuel. These effects, combined with the temperature increase due to burn, can cause the electron Hall parameter to grow rapidly at the burn front. This results in the formation of a self-insulating layer between hot and cold fuel that reduces electron thermal conductivity and $\alpha$ transport, increases the

10:30 Machine Learning Information Fusion in Earth Observation: A Comprehensive Review of Methods, Applications and Data Sources. (arXiv:2012.05795v1 [cs.CV])

This paper reviews the most important information fusion data-driven algorithms based on Machine Learning (ML) techniques for problems in Earth observation. Nowadays we observe and model the Earth with a wealth of observations, from a plethora of different sensors, measuring states, fluxes, processes and variables, at unprecedented spatial and temporal resolutions. Earth observation is well equipped with remote sensing systems, mounted on satellites and airborne platforms, but it also involves in-situ observations, numerical models and social media data streams, among other data sources. Data-driven approaches, and ML techniques in particular, are the natural choice to extract significant information from this data deluge. This paper produces a thorough review of the latest work on information fusion for Earth observation, with a practical intention, not only focusing on describing the most relevant previous works in the field, but also the most important Earth observation applications

10:30 An Integrated Search Framework for Leveraging the Knowledge-Based Web Ecosystem. (arXiv:2012.05397v1 [cs.IR])

The explosion of information constrains the judgement of search terms associated with Knowledge-Based Web Ecosystem (KBWE), making the retrieval of relevant information and its knowledge management challenging. The existing information retrieval (IR) tools and their fusion in a framework need attention, in which search results can effectively be managed. In this article, we demonstrate the effective use of information retrieval services by a variety of users and agents in various KBWE scenarios. An innovative Integrated Search Framework (ISF) is proposed, which utilises crawling strategies, web search technologies and traditional database search methods. Besides, ISF offers comprehensive, dynamic, personalized, and organization-oriented information retrieval services, ranging from the Internet, extranet, intranet, to personal desktop. In this empirical research, experiments are carried out demonstrating the improvements in the search process, as discerned in the conceptual ISF. The

10.12.2020
05:52 A non-twisting flux tube for local gyrokinetic simulations. (arXiv:2012.04785v1 [physics.plasm-ph])

Local gyrokinetic simulations use a field-aligned domain that twists due to the magnetic shear of the background magnetic equilibrium. However, if the magnetic shear is strong and/or the domain is long, the twist can become so extreme that it fails to properly resolve the turbulence. In this work, we derive and implement the "non-twisting flux tube," a local simulation domain that remains rectangular at all parallel locations. Convergence and runtime tests indicate that it can calculate the heat flux more efficiently than the conventional flux tube. For one test case, it was 30 times less computationally expensive and we found no case for which it was more expensive. It is most advantageous when the magnetic shear is high and the domain includes at least two regions of turbulent drive (e.g. stellarator simulations, pedestal simulations, tokamak simulations with several poloidal turns). Additionally, it more accurately models the inboard midplane when the magnetic shear is large.

02:56 When the pandemic hit, it left Yo-Yo Ma wondering ‘What is music for?’ — his album ‘Songs of Comfort and Hope’ provides one answer

Yo-Yo Ma, the Paris-born, New York-raised, world-renowned cellist, has packed a lot of living into his 65 years. He’s recorded more than 150 albums, earned 18 Grammy Awards and performed in every place imaginable around the world. But until the pandemic hit earlier this year, there was one thing that Ma had never experienced: regular business hours. “I’m realizing for the first time that I have a 9-to-5 job, Monday to Friday and that the weekends are off,” he said from his Cambridge, Massachusetts, home during a Zoom interview to promote “Songs of Comfort and Hope,” his latest album with British pianist Kathryn Stott. “I can’t wait for the weekends,” he laughed. “I always used to work the weekends and I worked nights. I never could hold a day job. I now know what a day job feels like.” Since his last performance in front of an audience in New York on March 10, Ma has been spending his days

09.12.2020
08:28 Non-Maxwellian rate coefficients for electron and ion collisions in Rydberg plasmas: implications for excitation and ionization. (arXiv:2012.04069v1 [physics.plasm-ph])

Scattering phenomena between charged particles and highly excited Rydberg atoms are of critical importance in many processes in plasma physics and astrophysics. While a Maxwell-Boltzmann (MB) energy distribution for the charged particles is often assumed for calculations of collisional rate coefficients, in this contribution we relax this assumption and use two different energy distributions, a bimodal MB distribution and a $\kappa$-distribution. Both variants share a high-energy tails occurring with higher probability than the corresponding MB distribution. The high energy tail may significantly affect rate coefficients for various processes. We focus the analysis to specific situations by showing the dependence of the rate coefficients on the principal quantum number of hydrogen atoms in n-changing collisions with electrons in the excitation and ionization channels and in a temperature range relevant to the divertor region of a tokamak device. We finally discuss the implications for

01:28 U.S. physicists rally around ambitious plan to build fusion power plant

Plan calls for a subtle but crucial shift toward applied research in Department of Energy fusion program

08.12.2020
11:43 Fusing Optical and SAR time series for LAI gap filling with multioutput Gaussian processes. (arXiv:2012.02998v1 [eess.IV])

The availability of satellite optical information is often hampered by the natural presence of clouds, which can be problematic for many applications. Persistent clouds over agricultural fields can mask key stages of crop growth, leading to unreliable yield predictions. Synthetic Aperture Radar (SAR) provides all-weather imagery which can potentially overcome this limitation, but given its high and distinct sensitivity to different surface properties, the fusion of SAR and optical data still remains an open challenge. In this work, we propose the use of Multi-Output Gaussian Process (MOGP) regression, a machine learning technique that learns automatically the statistical relationships among multisensor time series, to detect vegetated areas over which the synergy between SAR-optical imageries is profitable. For this purpose, we use the Sentinel-1 Radar Vegetation Index (RVI) and Sentinel-2 Leaf Area Index (LAI) time series over a study area in north west of the Iberian peninsula.

11:01 Search for solar electron anti-neutrinos due to spin-flavor precession in the Sun with Super-Kamiokande-IV. (arXiv:2012.03807v1 [hep-ex])

Due to a very low production rate of electron anti-neutrinos ($\bar{\nu}_e$) via nuclear fusion in the Sun, we expect to see $\bar{\nu}_e$ from other contribution. An appearance of $\bar{\nu}_e$ in solar neutrino flux opens a new window for the new physics beyond the standard model. In particular, a spin-flavor precession process is expected to convert an electron neutrino into an electron anti-neutrino (${\nu_e\to\bar{\nu}_e}$) if neutrino has a finite magnetic moment. In this work, we have searched for solar $\bar{\nu}_e$ in the Super-Kamiokande experiment, using neutron tagging to identify their inverse beta decay signature. We identified 78 $\bar{\nu}_e$ candidates for neutrino energies of 9.3 to 17.3 MeV in 2970.1 live days with a fiducial volume of 22.5 kiloton water (183.0 kton$\cdot$year exposure). The energy spectrum has been consistent with background predictions and we thus derived a 90\% confidence level upper limit of ${3.6\times10^{-4}}$ on the $\nu_e\to\bar{\nu}_e$

11:01 Fusing Optical and SAR time series for LAI gap filling with multioutput Gaussian processes. (arXiv:2012.02998v1 [eess.IV])

The availability of satellite optical information is often hampered by the natural presence of clouds, which can be problematic for many applications. Persistent clouds over agricultural fields can mask key stages of crop growth, leading to unreliable yield predictions. Synthetic Aperture Radar (SAR) provides all-weather imagery which can potentially overcome this limitation, but given its high and distinct sensitivity to different surface properties, the fusion of SAR and optical data still remains an open challenge. In this work, we propose the use of Multi-Output Gaussian Process (MOGP) regression, a machine learning technique that learns automatically the statistical relationships among multisensor time series, to detect vegetated areas over which the synergy between SAR-optical imageries is profitable. For this purpose, we use the Sentinel-1 Radar Vegetation Index (RVI) and Sentinel-2 Leaf Area Index (LAI) time series over a study area in north west of the Iberian peninsula.

11:01 Fusing Optical and SAR time series for LAI gap filling with multioutput Gaussian processes. (arXiv:2012.02998v1 [eess.IV])

The availability of satellite optical information is often hampered by the natural presence of clouds, which can be problematic for many applications. Persistent clouds over agricultural fields can mask key stages of crop growth, leading to unreliable yield predictions. Synthetic Aperture Radar (SAR) provides all-weather imagery which can potentially overcome this limitation, but given its high and distinct sensitivity to different surface properties, the fusion of SAR and optical data still remains an open challenge. In this work, we propose the use of Multi-Output Gaussian Process (MOGP) regression, a machine learning technique that learns automatically the statistical relationships among multisensor time series, to detect vegetated areas over which the synergy between SAR-optical imageries is profitable. For this purpose, we use the Sentinel-1 Radar Vegetation Index (RVI) and Sentinel-2 Leaf Area Index (LAI) time series over a study area in north west of the Iberian peninsula.

11:01 Multi-Source Data-Driven Outage Location in Distribution Systems Using Probabilistic Graph Learning. (arXiv:2012.02877v1 [eess.SP])

Efficient outage location is critical to enhancing the resilience of power systems. However, accurate outage location requires combining massive evidence received from diverse data sources, including smart meter (SM) signals, customer trouble calls, social media messages, weather data, vegetation information, and physical parameters of the network. This is a computationally complex task due to the high dimensionality of data in distribution grids. In this paper, we propose a multi-source data fusion approach to locate outage events in partially observable distribution systems using Bayesian networks (BNs). A novel aspect of the proposed approach is that it takes multi-source evidence and the complex structure of distribution systems into account using a probabilistic graphical method. This method can radically reduce the computational complexity of outage location inference in high-dimensional spaces. The graphical structure of the proposed BN is established based on the grid's

07.12.2020
17:13 D614/G614 variants of SARS-CoV-2 affect neuronal transmission; G614 better at membrane fusion

The COVID-19 pandemic is showing a strong comeback after an initial reduction in the number of cases, following energetic public health interventions.

06:36 Impact of plasma shaping on tokamak microstability. (arXiv:2012.02669v1 [physics.plasm-ph])

We have used the local-$\delta{f}$ gyrokinetic code GS2 to perform studies of the effect of flux-surface shaping on two highly-shaped, low- and high-$\beta$ JT-60SA-relevant equilibria, including a successful benchmark with the GKV code. We find a novel destabilization of electrostatic fluctuations with increased elongation for plasma with a strongly peaked pressure profile. We explain the results as a competition between the local magnetic shear and finite-Larmor-radius (FLR) stabilization. Electromagnetic studies indicate that kinetic ballooning modes are stabilized by increased shaping due to an increased sensitivity to FLR effects, relative to the ion-temperature-gradient instability. Nevertheless, at high enough $\beta$, increased elongation degrades the local magnetic shear stabilization that enables access to the region of ballooning second-stability.

04.12.2020
20:22 China turns on nuclear-powered ‘artificial sun’, TEN TIMES hotter than the real thing

Beijing has successfully powered up its “artificial sun” nuclear fusion reactor for the first time, China’s People’s Daily reported on Friday. It’s designed to be a clean energy source, similar to the real Sun. Made to replicate the natural reactions that occur in the sun using hydrogen and deuterium gases as fuels, the HL-2M Tokamak reactor is China's largest and most advanced nuclear fusion experimental research device. It is located in southwestern Sichuan province and was completed late last year. The reactor is often called an "artificial sun" due to the enormous heat and power it produces.

19:29 News24.com | China turns on nuclear-powered 'artificial sun'

China successfully powered up its "artificial sun" nuclear fusion reactor for the first time, state media reported Friday, marking a great advance in the country's nuclear power research capabilities.

17:55 China turns on nuclear-powered ‘artificial sun’, TEN TIMES hotter than the real thing

Beijing has successfully powered up its “artificial sun” nuclear fusion reactor for the first time, China’s People’s Daily reported on Friday. It’s designed to be a clean energy source, similar to the real Sun. Read Full Article at RT.com

14:43 China turns on nuclear-powered 'artificial sun'

China successfully powered up its "artificial sun" nuclear fusion reactor for the first time, state media reported Friday, marking a great advance in the country's nuclear power research capabilities.

14:42 China turns on nuclear-powered 'artificial sun'

China successfully powered up its "artificial sun" nuclear fusion reactor for the first time, state media reported Friday, marking a great advance in the country's nuclear power research capabilities. The HL-2M Tokamak reactor is China's largest and most advanced nuclear fusion experimental research device, and scientists hope that the device can potentially unlock a powerful clean energy source. It uses a powerful magnetic field to fuse hot plasma and can reach temperatures of over 150 million degrees Celsius, according to the People's Daily -- approximately ten times hotter than the core of the sun. Located in southwestern Sichuan province and completed late last year, the reactor is often called an "artificial sun" on account of the enormous heat and power it produces. "The development of nuclear fusion energy is not only a way to solve China's strategic energy needs, but also has great significance for the future sustainable development of China's energy and national economy,"

07:20 Plasma Confinement Mode Classification Using a Sequence-to-Sequence Neural Network With Attention. (arXiv:2012.02114v1 [physics.plasm-ph])

In a typical fusion experiment, the plasma can have several possible confinement modes. At the TCV tokamak, aside from the Low (L) and High (H) confinement modes, an additional mode, dithering (D), is frequently observed. Developing methods that automatically detect these modes is considered to be important for future tokamak operation. Previous work with deep learning methods, particularly convolutional recurrent neural networks (Conv-RNNs), indicates that they are a suitable approach. Nevertheless, those models are sensitive to noise in the temporal alignment of labels, and that model in particular is limited to making individual decisions taking into account only its own hidden state and its input at each time step. In this work, we propose an architecture for a sequence-to-sequence neural network model with attention which solves both of those issues. Using a carefully calibrated dataset, we compare the performance of a Conv-RNN with that of our proposed sequence-to-sequence model,

03.12.2020
09:55 Figures of merit for stellarators near the magnetic axis. (arXiv:2012.00865v1 [physics.plasm-ph])

A new paradigm for rapid stellarator configuration design has been recently demonstrated, in which the shapes of quasisymmetric or omnigenous flux surfaces are computed directly using an expansion in small distance from the magnetic axis. To further develop this approach, here we derive several other quantities of interest that can be rapidly computed from this near-axis expansion. First, the $\nabla\vec{B}$ and $\nabla\nabla\vec{B}$ tensors are computed, which can be used for direct derivative-based optimization of electromagnetic coil shapes to achieve the desired magnetic configuration. Moreover, if the norm of these tensors is large compared to the field strength for a given magnetic field, the field must have a short length scale, suggesting it may be hard to produce with coils that are suitably far away. Second, we evaluate the minor radius at which the flux surface shapes would become singular, providing a lower bound on the achievable aspect ratio. This bound is also shown to

09:55 Study of momentum diffusion with the effect of adiabatic focusing. (arXiv:2012.00852v1 [physics.plasm-ph])

Momentum diffusion of the energetic charged particles is an important mechanism of the transport process in astrophysics, physics of the fusion devices, and laboratory plasmas. In addition to the uniform field momentum diffusion, we obtain the modifying term due to the focusing effect of the large-scale magnetic field. After evaluating the modifying term, we find that it is determined by the sign of the focusing characteristic length and the Fokker-Planck coefficients $D_{\mu\mu}$, $D_{\mu p}$, $D_{p\mu}$, and $D_{pp}$. It is shown that we get a new second order acceleration mechanism in this work.

02.12.2020
20:38 U.K. seeks site for world’s first fusion power station

Spherical Tokamak for Energy Production reactor would be small—key to avoiding astronomical costs

04:07 UK takes step towards world's first nuclear fusion power station

The UK has embarked on a step to building the world’s first nuclear fusion power station, by launching a search for a 100-plus hectare site where it can be plugged into the electricity grid

03:06 UK seeks site for first nuclear fusion power station

Prototype to pave way for plants which would provide large amount of Britain’s energy

01.12.2020
22:48 Collision models impact the future of energy

A new database of electron-molecule reactions is a major step forward in making nuclear fusion power a reality, by allowing researchers to accurately model plasmas containing molecular hydrogen.

21:06 Curtin collision models impact the future of energy

A new Curtin University-created database of electron-molecule reactions is a major step forward in making nuclear fusion power a reality, by allowing researchers to accurately model plasmas containing molecular hydrogen.

08:08 Design of simple stellarator using tilted toroidal field coils. (arXiv:2011.14831v1 [physics.plasm-ph])

This paper deals with the design of the stellarator field with the simple coil set. In order to realize the stellarator field by the simple coil set, the tilted toroidal field coil uses for creating the rotational transform. Sixteen tilted TF coils create the small radial field and large vertical field. With reducing the vertical field of the tilted toroidal field coil by the axisymmetric poloidal field coil, the stellarator field can be made. The formation of clear and nested flux surfaces is confirmed, and the rotational transform is proportional to the tilting angle of the toroidal field coil. Main components of the magnetic field for the simple stellarator in this paper are the large mirror ripple and small helical ripple. This is a similar property to the quasi-isodynamic configuration like the Wendelstein 7-X stellarator. The collisionless orbit for the proton is studied. For a moderate tilting angle of the toroidal field coil, the confinement of the passing and trapped particles

08:08 Short-Term Load Forecasting using Bi-directional Sequential Models and Feature Engineering for Small Datasets. (arXiv:2011.14137v1 [cs.LG])

Electricity load forecasting enables the grid operators to optimally implement the smart grid's most essential features such as demand response and energy efficiency. Electricity demand profiles can vary drastically from one region to another on diurnal, seasonal and yearly scale. Hence to devise a load forecasting technique that can yield the best estimates on diverse datasets, specially when the training data is limited, is a big challenge. This paper presents a deep learning architecture for short-term load forecasting based on bidirectional sequential models in conjunction with feature engineering that extracts the hand-crafted derived features in order to aid the model for better learning and predictions. In the proposed architecture, named as Deep Derived Feature Fusion (DeepDeFF), the raw input and hand-crafted features are trained at separate levels and then their respective outputs are combined to make the final prediction. The efficacy of the proposed methodology is evaluated

30.11.2020
10:53 Testing of the new JOREK stellarator-capable model in the tokamak limit. (arXiv:2011.13820v1 [physics.plasm-ph])

In preparation for extending the JOREK nonlinear MHD code to stellarators, a hierarchy of stellarator-capable reduced and full MHD models has been derived and tested. The derivation was presented at the EFTC 2019 conference. Continuing this line of work, we have implemented the reduced MHD model (arXiv:1907.12486) as well as an alternative model which was newly derived using a different set of projection operators for obtaining the scalar momentum equations from the full MHD vector momentum equation. With the new operators, the reduced model matches the standard JOREK reduced models for tokamaks in the tokamak limit and conserves energy exactly, while momentum conservation is less accurate than in the original model whenever field-aligned flow is present.

10:53 Importance of theory, computation and predictive modeling in the US magnetic fusion energy strategic plan. (arXiv:2011.13390v1 [physics.plasm-ph])

Based on the community input at the National Academy of Sciences (NAS) Madison and Austin workshops in July and December 2017, respectively, this whitepaper was prepared and submitted to the NAS in the category of US fusion theory and computation. This whitepaper was submitted to NAS as one of five community-approved whitepapers. The revised version was also submitted for the Knoxville American Physical Society Division of Plasma Physics Community Planning Process (APS-DPP-CPP) workshop in September 2019.

26.11.2020
14:29 Sun model completely confirmed for the first time

The Borexino Experiment research team has succeeded in detecting neutrinos from the sun's second fusion process, the Carbon Nitrogen Oxygen cycle (CNO cycle) for the first time. This means that all of the theoretical predictions on how energy is generated within the sun have now also been experimentally verified.

07:16 Automatic Identification of MHD Modes in Magnetic Fluctuations Spectrograms using Deep Learning Techniques. (arXiv:2011.12615v1 [physics.plasm-ph])

The control and mitigation of MHD oscillations modes is an open problem in fusion science because they can contribute to the outward particle/energy flux and can drive the device away from ignition conditions. It is then of general interest to extract the mode information from large experimental databases in a fast and reliable way. We present a software tool based on Deep Learning that can identify these oscillations modes taking Mirnov coil spectrograms as input data. It uses Convolutional Neural Networks that we trained with manually annotated spectrograms from the TJ-II stellarator database. We have tested several detector architectures, resultingin a detector AUC score of 0.99 on the test set. Finally, it is applied to find MHD modes in our spectrograms to show how this new software tool can be used to mine other databases.

07:16 Automatic Identification of MHD Modes in Magnetic Fluctuations Spectrograms using Deep Learning Techniques. (arXiv:2011.12615v1 [physics.plasm-ph])

The control and mitigation of MHD oscillations modes is an open problem in fusion science because they can contribute to the outward particle/energy flux and can drive the device away from ignition conditions. It is then of general interest to extract the mode information from large experimental databases in a fast and reliable way. We present a software tool based on Deep Learning that can identify these oscillations modes taking Mirnov coil spectrograms as input data. It uses Convolutional Neural Networks that we trained with manually annotated spectrograms from the TJ-II stellarator database. We have tested several detector architectures, resultingin a detector AUC score of 0.99 on the test set. Finally, it is applied to find MHD modes in our spectrograms to show how this new software tool can be used to mine other databases.

25.11.2020
09:50 WeiPS: a symmetric fusion model framework for large-scale online learning. (arXiv:2011.11983v1 [cs.LG])

The recommendation system is an important commercial application of machine learning, where billions of feed views in the information flow every day. In reality, the interaction between user and item usually makes user's interest changing over time, thus many companies (e.g. ByteDance, Baidu, Alibaba, and Weibo) employ online learning as an effective way to quickly capture user interests. However, hundreds of billions of model parameters present online learning with challenges for real-time model deployment. Besides, model stability is another key point for online learning. To this end, we design and implement a symmetric fusion online learning system framework called WeiPS, which integrates model training and model inference. Specifically, WeiPS carries out second level model deployment by streaming update mechanism to satisfy the consistency requirement. Moreover, it uses multi-level fault tolerance and real-time domino degradation to achieve high availability requirement.

23.11.2020
19:51 Laser fusion reactor approaches ‘burning plasma’ milestone

After a decade, National Ignition Facility nears a self-heated, sustained reaction, though net energy gain is still elusive

08:23 Subcritical route to turbulence via the Orr mechanism in a quasi-two-dimensional boundary layer. (arXiv:2011.10143v1 [physics.flu-dyn])

The link to the online abstract of this manuscript, accepted in Phys. Rev. Fluids, is https://journals.aps.org/prfluids/accepted/32074S4aH8b1c608e19768b42571f9001086a3f44. A subcritical route to turbulence via purely quasi-two-dimensional mechanisms, for a quasi-two-dimensional system composed of an isolated exponential boundary layer, is numerically investigated. Exponential boundary layers are highly stable, and are expected to form on the walls of liquid metal coolant ducts within magnetic confinement fusion reactors. Subcritical transitions were detected only at weakly subcritical Reynolds numbers (at most $\approx 70$% below critical). Furthermore, the likelihood of transition was very sensitive to both the perturbation structure and initial energy. Only the quasi-two-dimensional Tollmien-Schlichting wave disturbance, attained by either linear or nonlinear optimisation, was able to initiate the transition process, by means of the Orr mechanism. The lower initial energy bound

20.11.2020
10:04 Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification. (arXiv:2011.09588v1 [cs.LG])

Among the many ways of quantifying uncertainty in a regression setting, specifying the full quantile function is attractive, as quantiles are amenable to interpretation and evaluation. A model that predicts the true conditional quantiles for each input, at all quantile levels, presents a correct and efficient representation of the underlying uncertainty. To achieve this, many current quantile-based methods focus on optimizing the so-called pinball loss. However, this loss restricts the scope of applicable regression models, limits the ability to target many desirable properties (e.g. calibration, sharpness, centered intervals), and may produce poor conditional quantiles. In this work, we develop new quantile methods that address these shortcomings. In particular, we propose methods that can apply to any class of regression model, allow for selecting a Pareto-optimal trade-off between calibration and sharpness, optimize for calibration of centered intervals, and produce more accurate

09:12 Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification. (arXiv:2011.09588v1 [cs.LG])

Among the many ways of quantifying uncertainty in a regression setting, specifying the full quantile function is attractive, as quantiles are amenable to interpretation and evaluation. A model that predicts the true conditional quantiles for each input, at all quantile levels, presents a correct and efficient representation of the underlying uncertainty. To achieve this, many current quantile-based methods focus on optimizing the so-called pinball loss. However, this loss restricts the scope of applicable regression models, limits the ability to target many desirable properties (e.g. calibration, sharpness, centered intervals), and may produce poor conditional quantiles. In this work, we develop new quantile methods that address these shortcomings. In particular, we propose methods that can apply to any class of regression model, allow for selecting a Pareto-optimal trade-off between calibration and sharpness, optimize for calibration of centered intervals, and produce more accurate

19.11.2020
18:10 Tungsten develops layers under fusion reactor extreme heat conditions

In tokamaks, magnetic confinement devices being explored for use as nuclear fusion reactors, anomalous events can cause a transfer of energy with 10 million times the intensity of the solar radiation on Earth's surface. These events can cause damage to structural components, potentially threatening the longevity of a tokamak.

12:00 Guiding Center and Gyrokinetic Theory for Large Electric Field Gradients and Strong Shear Flows. (arXiv:2011.08945v1 [physics.plasm-ph])

The guiding center and gyrokinetic theory of magnetized particle motion is extended to the regime of large electric field gradients perpendicular to the magnetic field. A gradient in the electric field directly modifies the oscillation frequency and causes the Larmor orbits to deform from circular to elliptical trajectories. In order to retain a good adiabatic invariant, there can only be strong dependence on a single coordinate at lowest order, so that resonances do not generate chaotic motion that destroys the invariant. When the gradient across magnetic flux surfaces is dominant, the guiding center drift velocity becomes anisotropic in response to external forces and additional curvature drifts must be included. The electric polarization density remains gyrotropic, but both the polarization and magnetization are modified by the change in gyrofrequency. The theory can be applied to strong shear flows, such as are commonly observed in the edge transport barrier of a high-performance

12:00 The interaction of the ITER first wall with magnetic perturbations. (arXiv:2011.09386v1 [physics.plasm-ph])

The innermost structure on ITER, the first wall, has its surface covered by separated beryllium tiles. The interaction of this tiled surface with magnetic perturbations is subtle---not only in the effects on the perturbations but also in the forces on the first wall. Indeterminacy can be introduced by tile-to-tile shorting. A determinate subtlety is introduced because electrically separated tiles can act as a conducting surface for magnetic perturbations that have a normal component. A practical method for including this determinate subtlety into plasma codes is developed. An assessment of the forces exerted on a first wall covered with electrically isolated tiles will require a number of calculations using these codes. The outcome of the calculations is problematic for two reasons: (1) The wall that can carry a net current is separated by a significant distance from the first wall, which cannot. (2) The existence of localized regions in which the continuously-conducting wall or the

12:00 The JOREK non-linear extended MHD code and applications to large-scale instabilities and their control in magnetically confined fusion plasmas. (arXiv:2011.09120v1 [physics.plasm-ph])

JOREK is a massively parallel fully implicit non-linear extended MHD code for realistic tokamak X-point plasmas. It is a widely used versatile code for studying large-scale plasma instabilities and their control and is continuously developed in an international community with strong involvements in European fusion research. This article gives a comprehensive overview of the physics models implemented, numerical methods applied for solving the equations and physics studies performed with the code. A dedicated section highlights verification work. A hierarchy of different physics models is available including a free boundary and resistive wall extension and hybrid kinetic-fluid models. The code allows for flux-surface aligned iso-parametric finite element grids in single and double X-point plasmas, which can be extended to the physical walls and uses a robust fully implicit time stepping. Particular focus is laid on plasma edge and scrape-off layer (SOL) physics as well as disruption

12:00 Hybrid-drive pressure suppressing implosion instabilities and offering nonstagnation hotspot ignition with low convergence ratio for high-gain inertial fusion. (arXiv:2011.09082v1 [physics.plasm-ph])

In laser-drive ICF, hybrid drive (HD) combined direct drive (DD) and indirect drive (ID) offers a smoothed HD pressure $P_{HD}$, far higher than the ablation pressure in ID and DD, to suppress hydrodynamic instabilities. In this letter, simulations of a new robust HD ignition target show that maximal HD pressure as high as $P_{HD} \sim$ 650 Mbar driven by a novel "bulldozer" effect is achieved, resulting in nonstagnation hotspot ignition at the convergence ratio $C_r \sim$23, and finally, fusion energy gain $\sim$ 10 in total laser energy = 1.42 MJ. Two-dimensional simulations have confirmed that hydrodynamic instabilities are suppressed. A well-fitted scale of maximal HD pressure $P_{HD}$ (Mbar)= $BE_{DD}^{1/4} T_r$ is found from simulations of different targets and laser energies as long as $T_r> 160$ eV, where B is the constant depending on ablator materials, $E_{DD}$ in kJ is DD laser energy and $T_r$ in 100 eV is radiation temperature depending on ID laser energy $E_{ID}$.

12:00 Guiding Center and Gyrokinetic Theory for Large Electric Field Gradients and Strong Shear Flows. (arXiv:2011.08945v1 [physics.plasm-ph])

The guiding center and gyrokinetic theory of magnetized particle motion is extended to the regime of large electric field gradients perpendicular to the magnetic field. A gradient in the electric field directly modifies the oscillation frequency and causes the Larmor orbits to deform from circular to elliptical trajectories. In order to retain a good adiabatic invariant, there can only be strong dependence on a single coordinate at lowest order, so that resonances do not generate chaotic motion that destroys the invariant. When the gradient across magnetic flux surfaces is dominant, the guiding center drift velocity becomes anisotropic in response to external forces and additional curvature drifts must be included. The electric polarization density remains gyrotropic, but both the polarization and magnetization are modified by the change in gyrofrequency. The theory can be applied to strong shear flows, such as are commonly observed in the edge transport barrier of a high-performance

12:00 Efficient Sensor Management for Multitarget Tracking in Passive Sensor Networks via Cauchy-Schwarz Divergence. (arXiv:2011.08976v1 [eess.SP])

This paper presents an efficient sensor management approach for multi-target tracking in passive sensor networks. Compared with active sensor networks, passive sensor networks have larger uncertainty due to the nature of passive sensing. Multi-target tracking in passive sensor networks is challenging because the multi-sensor multi-target fusion problem is difficult and sensor management is necessary to achieve good trade-offs between tracking accuracy and energy consumption or other costs. To address this problem, we present an efficient information-theoretic approach to manage the sensors for better tracking of the unknown and time-varying number of targets. This is accomplished with two main technical innovations. The first is a tractable information-based multi-sensor selection solution via a partially observed Markov decision process framework. The Cauchy-Schwarz divergence is used as the criterion to select informative sensors sequentially from the candidates. The second is a

18.11.2020
07:28 Alpha particle driven Alfv\'enic instabilities in ITER post-disruption plasmas. (arXiv:2011.08607v1 [physics.plasm-ph])

Fusion-born alpha particles in ITER disruption simulations are investigated as a possible drive of Alfv\'enic instabilities. The ability of these waves to expel runaway electron (RE) seed particles is explored in the pursuit of a passive, inherent RE mitigation scenario. The spatiotemporal evolution of the alpha particle distribution during the disruption is calculated using the linearized Fokker-Planck solver CODION coupled to a fluid disruption simulation. The radial anisotropy of the resulting alpha population provides free energy to drive Alfv\'enic modes during the quench phase of the disruption. We use the linear gyrokinetic magnetohydrodynamic code LIGKA to calculate the Alfv\'en spectrum and find that the equilibrium is capable of sustaining a wide range of modes. The self-consistent evolution of the mode amplitudes and the alpha distribution is calculated utilizing the wave-particle interaction tool HAGIS. Intermediate mode number ($n=7-15,~22-26$) Toroidal Alfv\'en Eigenmodes

07:28 Excitation of Zonal Flow by Intermediate-Scale Toroidal Electron Temperature Gradient Turbulence. (arXiv:2011.08256v1 [physics.plasm-ph])

We show that zonal flow can be preferentially excited by intermediate-scale toroidal electron temperature gradient (ETG) turbulence in tokamak plasmas. Previous theoretical studies that yielded an opposite conclusion assumed a fluid approximation for ETG modes. Here, we carry out a gyrokinetic analysis which ultimately yields a nonlinear Schr\"{o}dinger equation for the ETG dynamics with a Navier-Stokes type nonlinearity. For typical tokamak parameters, it is found that zonal flow generation plays an important role in the intermediate-scale ETG turbulence. This finding offers an explanation for recent multi-scale gyrokinetic simulations.

07:28 FTK: A High-Dimensional Simplicial Meshing Framework for Robust and Scalable Feature Tracking. (arXiv:2011.08697v1 [cs.GR])

We present the Feature Tracking Kit (FTK), a framework that simplifies, scales, and delivers various feature-tracking algorithms for scientific data. The key of FTK is our high-dimensional simplicial meshing scheme that generalizes both regular and unstructured spatial meshes to spacetime while tessellating spacetime mesh elements into simplices. The benefits of using simplicial spacetime meshes include (1) reducing ambiguity cases for feature extraction and tracking, (2) simplifying the handling of degeneracies using symbolic perturbations, and (3) enabling scalable and parallel processing. The use of simplicial spacetime meshing simplifies and improves the implementation of several feature-tracking algorithms for critical points, quantum vortices, and isosurfaces. As a software framework, FTK provides end users with VTK/ParaView filters, Python bindings, a command line interface, and programming interfaces for feature-tracking applications. We demonstrate use cases as well as

17.11.2020
10:07 The On-Axis Magnetic Well and Mercier's Criterion for Arbitrary Stellarator Geometries. (arXiv:2011.07416v1 [physics.plasm-ph])

A simplified analytical form of the on-axis magnetic well and Mercier's criterion for interchange instabilities for arbitrary three-dimensional magnetic field geometries is derived. For this purpose, a near-axis expansion based on a direct coordinate approach is used by expressing the toroidal magnetic flux in terms of powers of the radial distance to the magnetic axis. The magnetic well and Mercier's criterion are then written as a one-dimensional integral with respect to the axis arclength. When compared with the original work of Mercier, the derivation here is presented using modern notation and in a more streamlined manner that highlights essential steps, especially for the case of vacuum fields. Finally, for the first time, this expression is verified numerically using several stellarator configurations including Wendelstein 7-X.

10:07 Lagrangian particle model for 3D simulation of pellets and SPI fragments in tokamaks. (arXiv:2011.07111v1 [physics.plasm-ph])

A 3D numerical model for the ablation of pellets and shattered pellet injection (SPI) fragments in tokamaks in the plasma disruption mitigation and fueling parameter space has been developed based on the Lagrangian particle code [R. Samulyak, X. Wang, H.-S. Chen, Lagrangian Particle Method for Compressible Fluid Dynamics, J. Comput. Phys., 362 (2018), 1-19]. The pellet code implements the low magnetic Reynolds number MHD equations, kinetic models for the electronic heating, a pellet surface ablation model, an equation of state that supports multiple ionization states, radiation, and a model for grad-B drift of the ablated material across the magnetic field. The Lagrangian particle algorithm is highly adaptive, capable of simulating a large number of fragments in 3D while eliminating numerical difficulties of dealing with the tokamak background plasma. The code has achieved good agreement with theory for spherically symmetric ablation flows. Axisymmetric simulations of neon and

10:07 Deep Multi-view Image Fusion for Soybean Yield Estimation in Breeding Applications Deep Multi-view Image Fusion for Soybean Yield Estimation in Breeding Applications. (arXiv:2011.07118v1 [cs.CV])

Reliable seed yield estimation is an indispensable step in plant breeding programs geared towards cultivar development in major row crops. The objective of this study is to develop a machine learning (ML) approach adept at soybean [\textit{Glycine max} L. (Merr.)] pod counting to enable genotype seed yield rank prediction from in-field video data collected by a ground robot. To meet this goal, we developed a multi-view image-based yield estimation framework utilizing deep learning architectures. Plant images captured from different angles were fused to estimate the yield and subsequently to rank soybean genotypes for application in breeding decisions. We used data from controlled imaging environment in field, as well as from plant breeding test plots in field to demonstrate the efficacy of our framework via comparing performance with manual pod counting and yield estimation. Our results demonstrate the promise of ML models in making breeding decisions with significant reduction of

13.11.2020
06:40 Domain Generalization in Biosignal Classification. (arXiv:2011.06207v1 [cs.CV])

Objective: When training machine learning models, we often assume that the training data and evaluation data are sampled from the same distribution. However, this assumption is violated when the model is evaluated on another unseen but similar database, even if that database contains the same classes. This problem is caused by domain-shift and can be solved using two approaches: domain adaptation and domain generalization. Simply, domain adaptation methods can access data from unseen domains during training; whereas in domain generalization, the unseen data is not available during training. Hence, domain generalization concerns models that perform well on inaccessible, domain-shifted data. Method: Our proposed domain generalization method represents an unseen domain using a set of known basis domains, afterwhich we classify the unseen domain using classifier fusion. To demonstrate our system, we employ a collection of heart sound databases that contain normal and abnormal sounds

06:40 Deep learning and hand-crafted features for virus image classification. (arXiv:2011.06123v1 [cs.CV])

In this work, we present an ensemble of descriptors for the classification of transmission electron microscopy images of viruses. We propose to combine handcrafted and deep learning approaches for virus image classification. The set of handcrafted is mainly based on Local Binary Pattern variants, for each descriptor a different Support Vector Machine is trained, then the set of classifiers is combined by sum rule. The deep learning approach is a densenet201 pretrained on ImageNet and then tuned in the virus dataset, the net is used as features extractor for feeding another Support Vector Machine, in particular the last average pooling layer is used as feature extractor. Finally, classifiers trained on handcrafted features and classifier trained on deep learning features are combined by sum rule. The proposed fusion strongly boosts the performance obtained by each stand-alone approach, obtaining state of the art performance.

00:14 Advancing fusion energy through improved understanding of fast plasma particles

Scientists have developed a unique program to track the zig-zagging dance of hot, charged plasma particles that fuel fusion reactions.