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# Fusion

15.11.2018
22:13 ExtremeTech.comChinese Fusion Reactor Gets 6 Times Hotter Than the Sun

The team operating the Experimental Advanced Superconducting Tokamak (EAST) managed to heat the reactor's internal plasma to 100 million degrees Celsius (212 million Fahrenheit).
The post Chinese Fusion Reactor Gets 6 Times Hotter Than the Sun appeared first on ExtremeTech.

15:24 Phys.orgChinese fusion tool pushes past 100 million degrees

The Experimental Advanced Superconducting Tokamak (EAST), nicknamed the "Chinese artificial sun," achieved an electron temperature of over 100 million degrees in its core plasma during a four-month experiment this year. That's about seven times greater than the interior of the sun, which is about 15 million degrees C.

07:30 Gizmag Fusion breakthrough as China's "artificial sun" reaches 100 million degrees

The day of clean, limitless energy from nuclear fusion has taken another step closer after China's Experimental Advanced Superconducting Tokamak (EAST) reached a core plasma temperature of over 100 million degrees Celsius (180 million degrees Fahrenheit). During a four-month experiment, the "Chinese artificial sun" achieved a temperature over six times greater than the interior of the Sun for around 10 seconds.
.. Continue Reading Fusion breakthrough as China's "artificial sun" reaches 100 million degrees Category: Energy Tags: China Fusion Nuclear

03:01 WhatReallyHappened.comReaching for the stars: China creates nuke-powered fake sun that burns hotter than the real deal

Chinese researchers pushing to find a major clean energy source have created an incredible artificial sun that can reach temperatures of 100 million degrees Celsius – a heat so intense it makes the real sun seem merely lukewarm.
The earth-based solar simulator has reached mind-bending temperatures of 100 million degrees Celsius, the research team announced Tuesday. Now, that’s hot. For comparison, the real sun’s core is about 15 million degrees Celsius.
The Institute of Plasma Physics, affiliated with the Chinese Academy of Sciences, said it has been testing an “artificial sun,” known as the Experimental Advanced Superconducting Tokamak (EAST). The sci-fi-sounding contraption has been designed to replicate the way in which the star at the center of our solar system generates its colossal energy.

14.11.2018
08:18 Arxiv.org StatisticsNeuroimaging Modality Fusion in Alzheimer's Classification Using Convolutional Neural Networks. (arXiv:1811.05105v1 [cs.LG])

Automated methods for Alzheimer's disease (AD) classification have the potential for great clinical benefits and may provide insight for combating the disease. Machine learning, and more specifically deep neural networks, have been shown to have great efficacy in this domain. These algorithms often use neurological imaging data such as MRI and PET, but a comprehensive and balanced comparison of these modalities has not been performed. In order to accurately determine the relative strength of each imaging variant, this work performs a comparison study in the context of Alzheimer's dementia classification using the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. Furthermore, this work analyzes the benefits of using both modalities in a fusion setting and discusses how these data types may be leveraged in future AD studies using deep learning.

07:56 Arxiv.org Quantitative BiologyNeuroimaging Modality Fusion in Alzheimer's Classification Using Convolutional Neural Networks. (arXiv:1811.05105v1 [cs.LG])

Automated methods for Alzheimer's disease (AD) classification have the potential for great clinical benefits and may provide insight for combating the disease. Machine learning, and more specifically deep neural networks, have been shown to have great efficacy in this domain. These algorithms often use neurological imaging data such as MRI and PET, but a comprehensive and balanced comparison of these modalities has not been performed. In order to accurately determine the relative strength of each imaging variant, this work performs a comparison study in the context of Alzheimer's dementia classification using the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. Furthermore, this work analyzes the benefits of using both modalities in a fusion setting and discusses how these data types may be leveraged in future AD studies using deep learning.

07:56 Arxiv.org CSFusionStitching: Deep Fusion and Code Generation for Tensorflow Computations on GPUs. (arXiv:1811.05213v1 [cs.DC])

In recent years, there is a surge on machine learning applications in industry. Many of them are based on popular AI frameworks like Tensorflow, Torch, Caffe, or MxNet, etc, and are enpowered by accelerator platforms such as GPUs. One important challenge of running Tensorflow computations on GPUs is the fine granularity problem, namely, FLOPS of individual ops are far from enough to fully exploit the computing power of underlying accelerators. The XLA framework provides a solid foundation to explore this problem further. In this paper, we propose FusionStitching, a novel, comprehensive Op fusion and code generation system to stitch computations into large GPU kernels. Experimental results on four public models and two of our large inhouse applications show another 55% (geometric mean) reduction of GPU kernel launches, compared to the XLA fusion baseline. This increases the E2E performance of

07:56 Arxiv.org CSNeuroimaging Modality Fusion in Alzheimer's Classification Using Convolutional Neural Networks. (arXiv:1811.05105v1 [cs.LG])

Automated methods for Alzheimer's disease (AD) classification have the potential for great clinical benefits and may provide insight for combating the disease. Machine learning, and more specifically deep neural networks, have been shown to have great efficacy in this domain. These algorithms often use neurological imaging data such as MRI and PET, but a comprehensive and balanced comparison of these modalities has not been performed. In order to accurately determine the relative strength of each imaging variant, this work performs a comparison study in the context of Alzheimer's dementia classification using the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. Furthermore, this work analyzes the benefits of using both modalities in a fusion setting and discusses how these data types may be leveraged in future AD studies using deep learning.

13.11.2018
10:35 Arxiv.org PhysicsVacuum Solution for Solov'ev's Equilibrium Configuration in Tokamaks. (arXiv:1811.04443v1 [physics.plasm-ph])

In this work, we have revisited the Solov'ev analytical solution for a tokamak equilibrium. We point out that the vacuum solution in the Solov'ev formulation is inapplicable, since a distributed current density is assumed to fill the vacuum. The realistic vacuum should be current-free. To amend this vacuum solution problem, we use Green's function method to compute the plasma current contribution, together with a homogeneous solution to the Grad-Shafranov equation, to construct the full solution. Matching with the Solov'ev solution on the last closed flux surface is performed to determine the homogeneous solution. The total solution is then extended into the vacuum region to get a realistic vacuum solution. We find that the actual vacuum solution is different from the Solov'ev solution in the vacuum region, especially the X-point structure. The X-point obtained at the last closed flux surface

12.11.2018
06:21 Arxiv.org CSGender Effect on Face Recognition for a Large Longitudinal Database. (arXiv:1811.03680v1 [cs.CV])

Aging or gender variation can affect the face recognition performance dramatically. While most of the face recognition studies are focused on the variation of pose, illumination and expression, it is important to consider the influence of gender effect and how to design an effective matching framework. In this paper, we address these problems on a very large longitudinal database MORPH-II which contains 55,134 face images of 13,617 individuals. First, we consider four comprehensive experiments with different combination of gender distribution and subset size, including: 1) equal gender distribution; 2) a large highly unbalanced gender distribution; 3) consider different gender combinations, such as male only, female only, or mixed gender; and 4) the effect of subset size in terms of number of individuals. Second, we consider eight nearest neighbor distance metrics and also Support Vector

09.11.2018
07:40 Arxiv.org CSAttention Fusion Networks: Combining Behavior and E-mail Content to Improve Customer Support. (arXiv:1811.03169v1 [cs.CL])

Customer support is a central objective at Square as it helps us build and maintain great relationships with our sellers. In order to provide the best experience, we strive to deliver the most accurate and quasi-instantaneous responses to questions regarding our products.
In this work, we introduce the Attention Fusion Network model which combines signals extracted from seller interactions on the Square product ecosystem, along with submitted email questions, to predict the most relevant solution to a seller's inquiry. We show that the innovative combination of two very different data sources that are rarely used together, using state-of-the-art deep learning systems outperforms, candidate models that are trained only on a single source.

07.11.2018
18:52 ExtremeTech.comMIT Plans New Fusion Reactor That Could Actually Generate Power

MIT says it has the tools to make true fusion power happen, and it may be producing energy in a few years.
The post MIT Plans New Fusion Reactor That Could Actually Generate Power appeared first on ExtremeTech.

06.11.2018
08:49 Arxiv.org PhysicsFirst Commissioning Results of the Multicusp Ion Source at MIT (MIST-1) for H$_2^+$. (arXiv:1811.01868v1 [physics.acc-ph])

IsoDAR is an experiment under development to search for sterile neutrinos using the isotope Decay-At-Rest (DAR) production mechanism, where protons impinging on $^9$Be create neutrons which capture on $^7$Li which then beta-decays producing $\bar{\nu}_e$. As this will be an isotropic source of $\bar{\nu}_e$, the primary driver current must be large (10 mA cw) for IsoDAR to have sufficient statistics to be conclusive within 5 years of running. H$_2^+$ was chosen as primary ion to overcome some of the space-charge limitations during low energy beam transport and injection into a compact cyclotron. The H$_2^+$ will be stripped into protons before the target. At MIT, a multicusp ion source (MIST-1) was designed and built to produce a high intensity beam with a high H$_2^+$ fraction. MIST-1 is now operational at the Plasma Science and Fusion Center (PSFC) at MIT and under

05.11.2018
19:56 ScienceDaily.comA faster, cheaper path to fusion energy

Scientists are working to dramatically speed up the development of fusion energy in an effort to deliver power to the electric grid soon enough to help mitigate impacts of climate change. The arrival of a breakthrough technology -- high-temperature superconductors, which can be used to build magnets that produce stronger magnetic fields than previously possible -- could help them achieve this goal. Researchers plan to use this technology to build magnets at the scale required for fusion.

19:56 ScienceDaily.comInside job: A new technique to cool a fusion reactor

Fusion offers the potential of near limitless energy by heating a gas trapped in a magnetic field to incredibly high temperatures where atoms are so energetic that they fuse together when they collide. But if that hot gas, called a plasma, breaks free from the magnetic field, it must be safely put back in place to avoid damaging the fusion device -- this problem has been one of the great challenges of magnetically confined fusion.

19:56 ScienceDaily.comTaming plasmas: Improving fusion using microwaves

We all know microwaves are good for cooking popcorn, but scientists have recently shown they can also prevent dangerous waves in plasmas and help produce clean, nearly limitless energy with fusion. Fusion takes place when fast moving atomic particles slam into each other and stick together. The particles need to be so hot that atoms break down, leaving a gas of charged particles called a plasma.

19:56 ScienceDaily.comPeak performance: New stellarator experiments show promising results

Imagine building a machine so advanced and precise you need a supercomputer to help design it. That's exactly what scientists and engineers in Germany did when building the Wendelstein 7-X experiment. The device is a type of fusion device called a stellarator.

18:41 Phys.orgInside job: A new technique to cool a fusion reactor

Fusion offers the potential of near limitless energy by heating a gas trapped in a magnetic field to incredibly high temperatures where atoms are so energetic that they fuse together when they collide. But if that hot gas, called a plasma, breaks free from the magnetic field, it must be safely put back in place to avoid damaging the fusion device—this problem has been one of the great challenges of magnetically confined fusion.

18:41 Phys.orgTaming plasmas: Improving fusion using microwaves

We all know microwaves are good for cooking popcorn, but scientists have recently shown they can also prevent dangerous waves in plasmas and help produce clean, nearly limitless energy with fusion. Fusion takes place when fast moving atomic particles slam into each other and stick together. The particles need to be so hot that atoms break down, leaving a gas of charged particles called a plasma. The energy given off when plasma particles fuse can be harnessed to make electricity.

18:29 Phys.orgA faster, cheaper path to fusion energy

Scientists are working to dramatically speed up the development of fusion energy in an effort to deliver power to the electric grid soon enough to help mitigate impacts of climate change. The arrival of a breakthrough technology—high-temperature superconductors, which can be used to build magnets that produce stronger magnetic fields than previously possible—could help them achieve this goal. Researchers plan to use this technology to build magnets at the scale required for fusion, followed by construction of what would be the world's first fusion experiment to yield a net energy gain.

18:29 Phys.orgPeak performance: new stellarator experiments show promising results

Imagine building a machine so advanced and precise you need a supercomputer to help design it. That's exactly what scientists and engineers in Germany did when building the Wendelstein 7-X experiment. The device, funded by the German federal and state governments and the European Union, is a type of fusion device called a stellarator. The new experiment's goal is to contain a super-heated gas, called plasma, in a donut-shaped vessel using magnets that twist their way around the donut.

11:37 Arxiv.org StatisticsIndependent Vector Analysis for Data Fusion Prior to Molecular Property Prediction with Machine Learning. (arXiv:1811.00628v1 [stat.ML])

Due to its high computational speed and accuracy compared to ab-initio quantum chemistry and forcefield modeling, the prediction of molecular properties using machine learning has received great attention in the fields of materials design and drug discovery. A main ingredient required for machine learning is a training dataset consisting of molecular features\textemdash for example fingerprint bits, chemical descriptors, etc. that adequately characterize the corresponding molecules. However, choosing features for any application is highly non-trivial. No "universal" method for feature selection exists. In this work, we propose a data fusion framework that uses Independent Vector Analysis to exploit underlying complementary information contained in different molecular featurization methods, bringing us a step closer to automated feature generation. Our approach takes an arbitrary number of

11:26 Arxiv.org CSIndependent Vector Analysis for Data Fusion Prior to Molecular Property Prediction with Machine Learning. (arXiv:1811.00628v1 [stat.ML])

Due to its high computational speed and accuracy compared to ab-initio quantum chemistry and forcefield modeling, the prediction of molecular properties using machine learning has received great attention in the fields of materials design and drug discovery. A main ingredient required for machine learning is a training dataset consisting of molecular features\textemdash for example fingerprint bits, chemical descriptors, etc. that adequately characterize the corresponding molecules. However, choosing features for any application is highly non-trivial. No "universal" method for feature selection exists. In this work, we propose a data fusion framework that uses Independent Vector Analysis to exploit underlying complementary information contained in different molecular featurization methods, bringing us a step closer to automated feature generation. Our approach takes an arbitrary number of

02.11.2018
05:43 Arxiv.org PhysicsApplications of Deep Learning to Nuclear Fusion Research. (arXiv:1811.00333v1 [physics.plasm-ph])

Nuclear fusion is the process that powers the sun, and it is one of the best hopes to achieve a virtually unlimited energy source for the future of humanity. However, reproducing sustainable nuclear fusion reactions here on Earth is a tremendous scientific and technical challenge. Special devices -- called tokamaks -- have been built around the world, with JET (Joint European Torus, in the UK) being the largest tokamak currently in operation. Such devices confine matter and heat it up to extremely high temperatures, creating a plasma where fusion reactions begin to occur. JET has over one hundred diagnostic systems to monitor what happens inside the plasma, and each 30-second experiment (or pulse) generates about 50 GB of data. In this work, we show how convolutional neural networks (CNNs) can be used to reconstruct the 2D plasma profile inside the device based on data coming from those

05:43 Arxiv.org CSApplications of Deep Learning to Nuclear Fusion Research. (arXiv:1811.00333v1 [physics.plasm-ph])

Nuclear fusion is the process that powers the sun, and it is one of the best hopes to achieve a virtually unlimited energy source for the future of humanity. However, reproducing sustainable nuclear fusion reactions here on Earth is a tremendous scientific and technical challenge. Special devices -- called tokamaks -- have been built around the world, with JET (Joint European Torus, in the UK) being the largest tokamak currently in operation. Such devices confine matter and heat it up to extremely high temperatures, creating a plasma where fusion reactions begin to occur. JET has over one hundred diagnostic systems to monitor what happens inside the plasma, and each 30-second experiment (or pulse) generates about 50 GB of data. In this work, we show how convolutional neural networks (CNNs) can be used to reconstruct the 2D plasma profile inside the device based on data coming from those

05:43 Arxiv.org CSHybrid Self-Attention Network for Machine Translation. (arXiv:1811.00253v1 [cs.CL])

The encoder-decoder is the typical framework for Neural Machine Translation (NMT), and different structures have been developed for improving the translation performance. Transformer is one of the most promising structures, which can leverage the self-attention mechanism to capture the semantic dependency from global view. However, it cannot distinguish the relative position of different tokens very well, such as the tokens located at the left or right of the current token, and cannot focus on the local information around the current token either. To alleviate these problems, we propose a novel attention mechanism named Hybrid Self-Attention Network (HySAN) which accommodates some specific-designed masks for self-attention network to extract various semantic, such as the global/local information, the left/right part context. Finally, a squeeze gate is introduced to combine different kinds of

31.10.2018
04:14 Arxiv.org PhysicsThree Dimensional Pseudo-Spectral Compressible Magnetohydrodynamic GPU Code for Astrophysical Plasma Simulation. (arXiv:1810.12707v1 [physics.comp-ph])

This paper presents the benchmarking and scaling studies of a GPU accelerated three dimensional compressible magnetohydrodynamic code. The code is developed keeping an eye to explain the large and intermediate scale magnetic field generation is cosmos as well as in nuclear fusion reactors in the light of the theory given by Eugene Newman Parker. The spatial derivatives of the code are pseudo-spectral method based and the time solvers are explicit. GPU acceleration is achieved with minimal code changes through OpenACC parallelization and use of NVIDIA CUDA Fast Fourier Transform library (cuFFT). NVIDIAs unified memory is leveraged to enable over-subscription of the GPU device memory for seamless out-of-core processing of large grids. Our experimental results indicate that the GPU accelerated code is able to achieve upto two orders of magnitude speedup over a corresponding OpenMP parallel, FFTW

04:13 Arxiv.org CSCross-Modal Attentional Context Learning for RGB-D Object Detection. (arXiv:1810.12829v1 [cs.CV])

Recognizing objects from simultaneously sensed photometric (RGB) and depth channels is a fundamental yet practical problem in many machine vision applications such as robot grasping and autonomous driving. In this paper, we address this problem by developing a Cross-Modal Attentional Context (CMAC) learning framework, which enables the full exploitation of the context information from both RGB and depth data. Compared to existing RGB-D object detection frameworks, our approach has several appealing properties. First, it consists of an attention-based global context model for exploiting adaptive contextual information and incorporating this information into a region-based CNN (e.g., Fast RCNN) framework to achieve improved object detection performance. Second, our CMAC framework further contains a fine-grained object part attention module to harness multiple discriminative object parts inside

04:13 Arxiv.org CSSplitability Annotations: Optimizing Black-Box Function Composition in Existing Libraries. (arXiv:1810.12297v1 [cs.DC])

Data movement is a major bottleneck in parallel data-intensive applications. In response to this problem, researchers have proposed new runtimes and intermediate representations (IRs) that apply optimizations such as loop fusion under existing library APIs. Even though these runtimes generally do no require changes to user code, they require intrusive changes to the library itself: often, all the library functions need to be rewritten for a new IR or virtual machine. In this paper, we propose a new abstraction called splitability annotations (SAs) that enables key data movement optimizations on black-box library functions. SAs only require that users add an annotation for existing, unmodified functions and implement a small API to split data values in the library. Together, this interface describes how to partition values that are passed among functions to enable data pipelining and automatic

30.10.2018
07:13 Arxiv.org StatisticsShort-segment heart sound classification using an ensemble of deep convolutional neural networks. (arXiv:1810.11573v1 [cs.SD])

This paper proposes a framework based on deep convolutional neural networks (CNNs) for automatic heart sound classification using short-segments of individual heart beats. We design a 1D-CNN that directly learns features from raw heart-sound signals, and a 2D-CNN that takes inputs of two- dimensional time-frequency feature maps based on Mel-frequency cepstral coefficients (MFCC). We further develop a time-frequency CNN ensemble (TF-ECNN) combining the 1D-CNN and 2D-CNN based on score-level fusion of the class probabilities. On the large PhysioNet CinC challenge 2016 database, the proposed CNN models outperformed traditional classifiers based on support vector machine and hidden Markov models with various hand-crafted time- and frequency-domain features. Best classification scores with 89.22% accuracy and 89.94% sensitivity were achieved by the ECNN, and 91.55% specificity and 88.82% modified

07:02 Arxiv.org CSShort-segment heart sound classification using an ensemble of deep convolutional neural networks. (arXiv:1810.11573v1 [cs.SD])

This paper proposes a framework based on deep convolutional neural networks (CNNs) for automatic heart sound classification using short-segments of individual heart beats. We design a 1D-CNN that directly learns features from raw heart-sound signals, and a 2D-CNN that takes inputs of two- dimensional time-frequency feature maps based on Mel-frequency cepstral coefficients (MFCC). We further develop a time-frequency CNN ensemble (TF-ECNN) combining the 1D-CNN and 2D-CNN based on score-level fusion of the class probabilities. On the large PhysioNet CinC challenge 2016 database, the proposed CNN models outperformed traditional classifiers based on support vector machine and hidden Markov models with various hand-crafted time- and frequency-domain features. Best classification scores with 89.22% accuracy and 89.94% sensitivity were achieved by the ECNN, and 91.55% specificity and 88.82% modified

26.10.2018
03:39 Arxiv.org Quantitative BiologyInvestigating the Automatic Classification of Algae Using Fusion of Spectral and Morphological Characteristics of Algae via Deep Residual Learning. (arXiv:1810.10889v1 [cs.CV])

Under the impact of global climate changes and human activities, harmful algae blooms in surface waters have become a growing concern due to negative impacts on water related industries. Therefore, reliable and cost effective methods of quantifying the type and concentration of threshold levels of algae cells has become critical for ensuring successful water management. In this work, we present SAMSON, an innovative system to automatically classify multiple types of algae from different phyla groups by combining standard morphological features with their multi-wavelength signals. Two phyla with focused investigation in this study are the Cyanophyta phylum (blue-green algae), and the Chlorophyta phylum (green algae). We use a custom-designed microscopy imaging system which is configured to image water samples at two fluorescent wavelengths and seven absorption wavelengths using

03:39 Arxiv.org CSInvestigating the Automatic Classification of Algae Using Fusion of Spectral and Morphological Characteristics of Algae via Deep Residual Learning. (arXiv:1810.10889v1 [cs.CV])

Under the impact of global climate changes and human activities, harmful algae blooms in surface waters have become a growing concern due to negative impacts on water related industries. Therefore, reliable and cost effective methods of quantifying the type and concentration of threshold levels of algae cells has become critical for ensuring successful water management. In this work, we present SAMSON, an innovative system to automatically classify multiple types of algae from different phyla groups by combining standard morphological features with their multi-wavelength signals. Two phyla with focused investigation in this study are the Cyanophyta phylum (blue-green algae), and the Chlorophyta phylum (green algae). We use a custom-designed microscopy imaging system which is configured to image water samples at two fluorescent wavelengths and seven absorption wavelengths using

25.10.2018
06:21 Arxiv.org PhysicsSimulation of the electromagnetic wall response during Vertical Displacement Events (VDE) in ITER tokamak. (arXiv:1810.10277v1 [physics.plasm-ph])

The key basis for tokamak plasma disruption modeling is to understand how currents flow to the plasma facing surfaces during plasma disruption events. In ITER tokamak, the occurrence of a limited number of major disruptions will definitively damage the chamber with no possibility to restore the device. In the current exchange plasma-wall-plasma, according to the Helmholtz decomposition theorem, our surface current density in the conducting shell - the unknown of our problem - being a vector field twice continuously differentiable in 3D, has been splited into two components: an irrotational (curl-free) vector field and a solenoidal (divergence-free) vector field. Developing a weak formulation form and minimizing the correspondent energy functionals in a Finite Element approach, we have obtained the space and time distribution of the surface currents. We verified successfully our numerical

24.10.2018
20:53 ScienceDaily.comA first 'snapshot' of the complete spectrum of neutrinos emitted by the sun

About 99 percent of the sun's energy emitted as neutrinos is produced through nuclear reaction sequences initiated by proton-proton (pp) fusion in which hydrogen is converted into helium, say scientists.

20:09 Phys.orgA first 'snapshot' of the complete spectrum of neutrinos emitted by the sun

About 99 percent of the Sun's energy emitted as neutrinos is produced through nuclear reaction sequences initiated by proton-proton (pp) fusion in which hydrogen is converted into helium, say scientists including physicist Andrea Pocar at the University of Massachusetts Amherst. Today they report new results from Borexino, one of the most sensitive neutrino detectors on the planet, located deep beneath Italy's Apennine Mountains.

22.10.2018
07:16 Arxiv.org PhysicsStrategy and guidelines for the calibration of the ITER radial neutron camera. (arXiv:1810.08582v1 [physics.ins-det])

A calibration procedure is proposed for the ITER Radial Neutron Camera. No in-vessel calibration using external neutron sources is required: instead, it is proposed to rely on embedded sources, reference ITER pulses and cross-calibration with ITER fission chambers and activation system coupled to Monte Carlo simulations of radiation transport for the validation of the RNC calibration and for its tracking during ITER lifetime.

19.10.2018
15:59 Phys.orgNew simulations confirm efficiency of waste-removal process in plasma device

Just as fire produces ash, the combining of light elements in fusion reactions can produce material that eventually interferes with those same reactions. Now, scientists at the U.S. Department of Energy's (DOE) Princeton Plasma Physics Laboratory (PPPL) have found evidence suggesting that a process could remove the unwanted material and make the fusion processes more efficient within a type of fusion facility known as a field-reversed configuration (FRC) device.

18.10.2018
14:52 CNNHypersonic, nuclear airplanes of the future

From blended wing airliners powered by nuclear fusion to a new generation of spacecraft designed to carry tourists to the moon, it's hard not to be mesmerized by Oscar Viñals' boldly ambitious aircraft designs.

16.10.2018
09:23 Arxiv.org PhysicsLiquid scintillators neutron response function: a tutorial. (arXiv:1810.06263v1 [physics.ins-det])

This tutorial is devoted to the understanding of the different components that are present in the neutron light output pulse height distribution of liquid scintillators in fusion relevant energy ranges. The basic mechanisms for the generation of the scintillation light are briefly discussed. The different elastic collision processed between the incident neutrons and the hydrogen and carbon atoms are described in terms of probability density functions and the overall response function as their convolution. The results from this analytical approach is then compared with those obtained from simplified and full Monte Carlo simulations. Edge effect, finite energy resolution, light output and transport and competing physical processes between neutron and carbon and hydrogen atoms and their impact on the response functions are discussed. Although the analytical treatment here presented allows only

15.10.2018
05:05 Arxiv.org PhysicsDynamics of cold pulses induced by super-sonic molecular beam injection in the EAST tokamak. (arXiv:1810.05352v1 [physics.plasm-ph])

Evolution of electron temperature, electron density and its fluctuation with high spatial and temporal resolutions are presented for the cold pulse propagation induced by super-sonic molecular beam injection (SMBI) in ohmic plasmas in the EAST tokamak. The non-local heat transport occurs for discharges with plasma current $I_p$=450 kA ($q_{95}\sim5.55$), and electron density $n_{e0}$ below a critical value of $(1.35\pm0.25)\times10^{19}~\mathrm{m^{-3}}$. In contrary to the response of core electron temperature and electron density (roughly 10 ms after SMBI), the electron density fluctuation in the plasma core increases promptly after SMBI and reaches its maximum around 15 ms after SMBI. The electron density fluctuation in the plasma core begins to decrease before the core electron temperature reaches its maximum (roughly 30 ms). It was also observed that the turbulence perpendicular velocity

05:05 Arxiv.org PhysicsNonlinear dynamics of Shear Alfv\'en fluctuations in Divertor Tokamak Test facility plasmas. (arXiv:1810.05327v1 [physics.plasm-ph])

Following the analysis on linear spectra of shear Alfv\'en fluctuations excited by energetic particles (EPs) in the Divertor Tokamak Test (DTT) facility plasmas [T. Wang et al., Phys. Plasmas 25, 062509 (2018)], in this work, nonlinear dynamics of the corresponding mode saturation and the fluctuation induced EP transport is studied by hybrid magnetohydrodynamic-gyrokinetic simulations. For the reversed shear Alfv\'en eigenmode driven by magnetically trapped EP precession resonance in the central core region of DTT plasmas, the saturation is mainly due to radial decoupling of resonant trapped EPs. Consistent with the wave-EP resonance structure, EP transport occurs in a similar scale to the mode width. On the other hand, passing EP transport is analyzed in detail for toroidal Alfv\'en eigenmode in the outer core region, with mode drive from both passing and trapped EPs. It is shown that

12.10.2018
21:06 Aljazeera.NetScientists to build a new prototype nuclear fusion reactor

If successful, the project could be the answer to the worldâ€™s clean energy needs.

05:50 Arxiv.org PhysicsAn improved understanding of the roles of atomic processes and power balance in divertor target ion current loss during detachment. (arXiv:1810.04969v1 [physics.plasm-ph])

The physics leading to the decrease of the divertor ion current ($I_t$), or 'roll-over' during detachment for divertor power exhaust in tokamaks is experimentally explored on the TCV tokamak through characterization of the location, magnitude and role of the various divertor ion sinks and sources including a complete measure of particle and power balance. These first measurements of the profiles of divertor ionisation and hydrogenic radiation along the divertor leg are enabled through novel spectroscopic techniques which are introduced.
Over a range in TCV plasma conditions (plasma current, impurity-seeding, density) the $I_t$ roll-over is caused by a drop in the divertor ion source; recombination remains either small or negligible until later in the detachment process. In agreement with simple analytical predictions, this ion source reduction is driven by a reduction in the power

05:50 Arxiv.org PhysicsProperties of a new quasi-axisymmetric configuration. (arXiv:1810.04914v1 [physics.plasm-ph])

A novel, compact, quasi-axisymmetric configuration is presented which exhibits low fast-particle losses and is stable to ideal MHD instabilities. The design has fast-particle loss rates below 8\% for flux surfaces within the half-radius, and is shown to have an MHD-stability limit of a normalised pressure of $\langle\beta\rangle=3\%$ where $\langle\beta\rangle$ is volume averaged. The flux surfaces at various plasma betas and currents as calculated using the SPEC equilibrium code are presented. Neoclassical transport coefficients are shown to be similar to an equivalent tokamak, with a distinct banana regime at half-radius. An initial coil design study is presented to assess the feasibility of this configuration as a fusion-relevant experiment.

11.10.2018
08:32 Arxiv.org PhysicsThe effects of non-uniform drive on plasma filaments. (arXiv:1810.04584v1 [physics.plasm-ph])

Wendelstein 7-X core fueling is primarily achieved through pellet injection. The trajectory of plasmoids from an ablating pellet is an ongoing research question, which is complicated by the complex magnetic geometry of W7-X; curvature drive varies significantly toroidally, including a change in the drift drive direction. Here we use the Hermes model in BOUT++ to simulate cold plasma filaments in slab geometries where the magnetic drift drive is non-uniform along the field line. It is shown that if the field-line-averaged curvature drive is non-zero, a filament will propagate coherently in the direction of average drive. It is also shown that a non-uniform drive will provide a non- uniform propagation; an effect which is reduced at higher temperatures due to an increased sound speed along the field line. Finally, simulations with curvature similar to that found in Wendelstein 7-X are performed

10.10.2018
09:47 Phys.orgNovel design could help shed excess heat in next-generation fusion power plants

A class exercise at MIT, aided by industry researchers, has led to an innovative solution to one of the longstanding challenges facing the development of practical fusion power plants: how to get rid of excess heat that would cause structural damage to the plant.

09:04 Technology.orgA new path to solving a longstanding fusion challenge

A class exercise at MIT, aided by industry researchers, has led to an innovative solution to one of

09.10.2018
06:48 Arxiv.org StatisticsSparse Regression with Multi-type Regularized Feature Modeling. (arXiv:1810.03136v1 [stat.CO])

Within the statistical and machine learning literature, regularization techniques are often used to construct sparse (predictive) models. Most regularization strategies only work for data where all predictors are of the same type, such as Lasso regression for continuous predictors. However, many predictive problems involve different predictor types. We propose a multi-type Lasso penalty that acts on the objective function as a sum of subpenalties, one for each predictor type. As such, we perform predictor selection and level fusion within a predictor in a data-driven way, simultaneous with the parameter estimation process. We develop a new estimation strategy for convex predictive models with this multi-type penalty. Using the theory of proximal operators, our estimation procedure is computationally efficient, partitioning the overall optimization problem into easier to solve subproblems,

06:47 Arxiv.org PhysicsStudies of Reynolds Stress and the Turbulent Generation of Edge Poloidal Flows on the HL-@A Tokamak. (arXiv:1810.03588v1 [physics.plasm-ph])

Several new results in the physics of edge poloidal flows, turbulent stresses and momentum transport are reported. These are based on experiments on the HL-2A tokamak. Significant deviation from neoclassical prediction for mean poloidal flow in Ohmic and L mode discharges is deduced from direct measurements of the turbulent Reynolds stress. The deviation increases with heating power. The turbulent poloidal viscosity is synthesized from fluctuation data, and is found to be comparable to the turbulent particle diffusivity. The intrinsic poloidal torque is deduced from synthesis, for the first time. PDFs of particle flux and Reynolds stress are obtained. Both exhibit fat tails and large kurtosis, suggesting that the momentum transport process represented by the Reynolds stress is not well described by quasilinear calculations.

08.10.2018
09:27 Arxiv.org PhysicsSpatiotemporal evolution of runaway electrons from synchrotron images in Alcator C-Mod. (arXiv:1810.02742v1 [physics.plasm-ph])

In the Alcator C-Mod tokamak, relativistic runaway electron (RE) generation can occur during the flattop current phase of low density, diverted plasma discharges. Due to the high toroidal magnetic field (B = 5.4 T), RE synchrotron radiation is measured by a wide-view camera in the visible wavelength range (~400-900 nm). In this paper, a statistical analysis of over one thousand camera images is performed to investigate the plasma conditions under which synchrotron emission is observed in C-Mod. In addition, the spatiotemporal evolution of REs during one particular discharge is explored in detail via a thorough analysis of the distortion-corrected synchrotron images. To accurately predict RE energies, the kinetic solver CODE [Landreman et al 2014 Comput. Phys. Commun. 185 847-855] is used to evolve the electron momentum-space distribution at six locations throughout the plasma: the magnetic

03.10.2018
08:54 Arxiv.org PhysicsThe role of incidence angle in the laser ablation of planar ICF targets. (arXiv:1810.01004v1 [physics.plasm-ph])

The effect of the laser ray incidence angle on the mass ablation rate and ablation pressure of planar inertial confinement fusion (ICF) targets is explored using an idealized model. Polar direct drive (PDD) on the National Ignition Facility (NIF) requires the repointing of its 192 beams clustered within 50 degrees of the poles to minimize the imparted polar varying payload kinetic energy of the target. Due to this repointing, non-normal incidence angles of the beam centerlines are encountered in any PDD design. The formulation of a PDD scheme that minimizes non-uniformity is a significant challenge that requires an understanding of the induced differences in ablation including those of incidence angle. In this work, a modified version of the textbook model of laser ablation [Manheimer et al. Phys. Fluids 25, 1644 (1982)] is used to demonstrate that the mass ablation rate and ablation pressure

08:54 Arxiv.org CSFusion of Monocular Vision and Radio-based Ranging for Global Scale Estimation and Drift Mitigation. (arXiv:1810.01346v1 [cs.RO])

Monocular vision-based Simultaneous Localization and Mapping (SLAM) is used for various purposes due to its advantages in cost, simple setup, as well as availability in the environments where navigation with satellites is not effective. However, camera motion and map points can be estimated only up to a global scale factor with monocular vision. Moreover, estimation error accumulates over time without bound, if the camera cannot detect the previously observed map points for closing a loop. We propose an innovative approach to estimate a global scale factor and reduce drifts in monocular vision-based localization with an additional single ranging link. Our method can be easily integrated with the back-end of monocular visual SLAM methods. We demonstrate our algorithm with real datasets collected on a rover, and show the evaluation results.

08:54 Arxiv.org CSMarrying Tracking with ELM: A Metric Constraint Guided Multiple Feature Fusion Method. (arXiv:1810.01271v1 [cs.CV])

Object Tracking is one important problem in computer vision and surveillance system. The existing models mainly exploit the single-view feature (i.e. color, texture, shape) to solve the problem, failing to describe the objects comprehensively. In this paper, we solve the problem from multi-view perspective by leveraging multi-view complementary and latent information, so as to be robust to the partial occlusion and background clutter especially when the objects are similar to the target, meanwhile addressing tracking drift. However, one big problem is that multi-view fusion strategy can inevitably result tracking into non-efficiency. To this end, we propose to marry ELM (Extreme learning machine) to multi-view fusion to train the global hidden output weight, to effectively exploit the local information from each view. Following this principle, we propose a novel method to obtain the optimal

02.10.2018
16:03 Phys.orgAttempting to tame plasmas in fusion

Nuclear fusion, the release of energy when light atomic nuclei merge, is touted as a carbon-free solution to global energy requirements. One potential route to nuclear fusion is inertial confinement. Now a KAUST-led team has modeled the complex flow of plasma that could occur in such a fusion reactor.

28.09.2018
08:30 Arxiv.org PhysicsConceptual design study for heat exhaust management in the ARC fusion pilot plant. (arXiv:1809.10555v1 [physics.ins-det])

The ARC pilot plant conceptual design study has been extended beyond its initial scope [B. N. Sorbom et al., FED 100 (2015) 378] to explore options for managing ~525 MW of fusion power generated in a compact, high field (B_0 = 9.2 T) tokamak that is approximately the size of JET (R_0 = 3.3 m). Taking advantage of ARC's novel design - demountable high temperature superconductor toroidal field (TF) magnets, poloidal magnetic field coils located inside the TF, and vacuum vessel (VV) immersed in molten salt FLiBe blanket - this follow-on study has identified innovative and potentially robust power exhaust management solutions.

08:30 Arxiv.org PhysicsQuenching factor measurement for a NaI(Tl) scintillation crystal. (arXiv:1809.10310v1 [physics.ins-det])

Scintillation crystals are commonly used for direct detection of a weakly interacting massive particle (WIMP), which is a good candidate of a particle dark matter. It is well known that scintillation light yields are different between electron recoil and nuclear recoil. To calibrate energies of WIMP-induced nuclear recoil signals, one needs to measure a quenching factor (QF), light yield ratio of nuclear recoil to electron recoil. Measurements of the QFs for Na and I recoils in a small (2 cm x 2 cm x 1.5 cm) NaI(Tl) crystal have been performed with 2.43 MeV mono-energetic neutrons generated from deuteron-deuteron fusion. Depending on the scattering angle of the neutrons, energies of recoiled ions vary from 9 to 150 keV for Na and 19 to 75 keV for I. QFs of Na are measured at 9 points with the values from 10 % to 23 % and those of I are measured at 4 points with the values from 4 % to 6

08:30 Arxiv.org PhysicsDirect construction of optimized stellarator shapes. II. Numerical quasisymmetric solutions. (arXiv:1809.10246v1 [physics.plasm-ph])

Quasisymmetric stellarators are appealing intellectually and as fusion reactor candidates since the guiding center particle trajectories and neoclassical transport are isomorphic to those in a tokamak, despite the lack of true axisymmetry. Previously, quasisymmetric magnetic fields have been identified by applying black-box optimization algorithms to minimize symmetry-breaking Fourier modes of the field strength $B$. Here instead we directly construct magnetic fields in cylindrical coordinates that are quasisymmetric to leading order in distance from the magnetic axis, without using optimization. The method involves solution of a 1-dimensional nonlinear ordinary differential equation, originally derived by Garren and Boozer [Phys. Fluids B 3, 2805 (1991)]. We demonstrate the usefulness and accuracy of this optimization-free approach by providing the results of this construction as input to

08:30 Arxiv.org PhysicsDirect construction of optimized stellarator shapes. I. Theory in cylindrical coordinates. (arXiv:1809.10233v1 [physics.plasm-ph])

The confinement of guiding center trajectories in a stellarator is determined by the variation of the magnetic field strength $B$ in Boozer coordinates $(r, \theta, \varphi)$, but $B(r,\theta,\varphi)$ depends on the flux surface shape in a complicated way. Here we derive equations relating $B(r,\theta,\varphi)$ in Boozer coordinates and the rotational transform to the shape of flux surfaces in cylindrical coordinates, using an expansion in distance from the magnetic axis. A related expansion was done by Garren and Boozer [Phys. Fluids B 3, 2805 (1991)] based on the Frenet-Serret frame, which can be discontinuous anywhere the magnetic axis is straight, a situation that occurs in the interesting case of omnigenity with poloidally closed $B$ contours. Our calculation in contrast does not use the Frenet-Serret frame. The transformation between the Garren-Boozer approach and cylindrical

26.09.2018
07:05 Arxiv.org PhysicsLow-shear three-dimensional equilibria and vacuum magnetic fields with flux surfaces. (arXiv:1809.09225v1 [physics.plasm-ph])

Stellarators are generically small current and relatively low plasma beta ($\beta= p/B^2\ll1$) devices. Often the construction of vacuum magnetic fields with relatively good magnetic surfaces is the starting point for an equilibrium calculation. Although in cases with some continuous spatial symmetry flux functions can always be found for vacuum magnetic fields, an analogous function does not, in general, exist in three dimensions. This work examines several relatively simple equilibrium and vacuum magnetic field problems with the intent of demonstrating the possibilities and limitations in the construction of such states. Starting with a very simple vacuum magnetic field with closed field lines in a topological torus, we obtain a self-consistent formal perturbation series using the amplitude of the non-symmetric vacuum fields as a small parameter. We show that systems possessing

25.09.2018
09:39 Arxiv.org MathSpectrum and Energy Efficient Multiple Access for Detection in Wireless Sensor Networks. (arXiv:1809.08468v1 [cs.IT])

We consider a binary hypothesis testing problem using Wireless Sensor Networks (WSNs). The decision is made by a fusion center and is based on received data from the sensors. We focus on a spectrum and energy efficient transmission scheme used to reduce the spectrum usage and energy consumption during the detection task. We propose a Spectrum and Energy Efficient Multiple Access (SEEMA) transmission protocol that performs a censoring-type transmission based on the density of observations using multiple access channels (MAC). Specifically, in SEEMA, only sensors with highly informative observations transmit their data in each data collection. The sensors transmit a common shaping waveform and the fusion center receives a superposition of the analog transmitted signals. SEEMA has important advantages for detection tasks in WSNs. First, it is highly energy and bandwidth efficient due to

09:39 Arxiv.org CSSpectrum and Energy Efficient Multiple Access for Detection in Wireless Sensor Networks. (arXiv:1809.08468v1 [cs.IT])

We consider a binary hypothesis testing problem using Wireless Sensor Networks (WSNs). The decision is made by a fusion center and is based on received data from the sensors. We focus on a spectrum and energy efficient transmission scheme used to reduce the spectrum usage and energy consumption during the detection task. We propose a Spectrum and Energy Efficient Multiple Access (SEEMA) transmission protocol that performs a censoring-type transmission based on the density of observations using multiple access channels (MAC). Specifically, in SEEMA, only sensors with highly informative observations transmit their data in each data collection. The sensors transmit a common shaping waveform and the fusion center receives a superposition of the analog transmitted signals. SEEMA has important advantages for detection tasks in WSNs. First, it is highly energy and bandwidth efficient due to

21.09.2018
09:42 Phys.orgNeutrons produce first direct 3-D maps of water during cell membrane fusion

New 3-D maps of water distribution during cellular membrane fusion are accelerating scientific understanding of cell development, which could lead to new treatments for diseases associated with cell fusion. Using neutron diffraction at the Department of Energy's Oak Ridge National Laboratory, researchers have made the first direct observations of water in lipid bilayers used to model cell membrane fusion.

20.09.2018
09:16 Arxiv.org PhysicsDependence of Alfv\'en eigenmode linear stability on device magnetic field strength and consequences for next-generation tokamaks. (arXiv:1809.07278v1 [physics.plasm-ph])

Recently-proposed tokamak concepts use magnetic fields up to 12 T, far higher than in conventional devices, to reduce size and cost. Theoretical and computational study of trends in plasma behavior with increasing field strength is critical to such proposed devices. This paper considers trends in Alfv\'en eigenmode (AE) stability. Energetic particles, including alphas from D-T fusion, can destabilize AEs, possibly causing loss of alpha heat and damage to the device. AEs are sensitive to device magnetic field via the field dependence of resonances, alpha particle beta, and alpha orbit width. We describe the origin and effect of these dependences analytically and by using recently-developed numerical techniques (Rodrigues et al. 2015 Nucl. Fusion 55 083003). The work suggests high-field machines where fusion-born alphas are sub-Alfv\'enic or nearly sub-Alfv\'enic may partially cut off AE

18.09.2018
07:48 Arxiv.org CSHierarchical Graphical Models for Context-Aware Hybrid Brain-Machine Interfaces. (arXiv:1809.05635v1 [cs.HC])

We present a novel hierarchical graphical model based context-aware hybrid brain-machine interface (hBMI) using probabilistic fusion of electroencephalographic (EEG) and electromyographic (EMG) activities. Based on experimental data collected during stationary executions and subsequent imageries of five different hand gestures with both limbs, we demonstrate feasibility of the proposed hBMI system through within session and online across sessions classification analyses. Furthermore, we investigate the context-aware extent of the model by a simulated probabilistic approach and highlight potential implications of our work in the field of neurophysiologically-driven robotic hand prosthetics.

02:45 ScienceDaily.comNew world record magnetic field

Researchers have recorded the highest magnetic field ever achieved indoors -- a discovery that may open doors for materials science and fusion energy research.

12.09.2018
10:20 Arxiv.org MathEnergy-efficient Decision Fusion for Distributed Detection in Wireless Sensor Networks. (arXiv:1809.03653v1 [cs.IT])

This paper proposes an energy-efficient counting rule for distributed detection by ordering sensor transmissions in wireless sensor networks. In the counting rule-based detection in an $N-$sensor network, the local sensors transmit binary decisions to the fusion center, where the number of all $N$ local-sensor detections are counted and compared to a threshold. In the ordering scheme, sensors transmit their unquantized statistics to the fusion center in a sequential manner; highly informative sensors enjoy higher priority for transmission. When sufficient evidence is collected at the fusion center for decision making, the transmissions from the sensors are stopped. The ordering scheme achieves the same error probability as the optimum unconstrained energy approach (which requires observations from all the $N$ sensors) with far fewer sensor transmissions. The scheme proposed in this paper

10:20 Arxiv.org CS3D Inception-based CNN with sMRI and MD-DTI data fusion for Alzheimer's Disease diagnostics. (arXiv:1809.03972v1 [cs.CV])

In the last decade, computer-aided early diagnostics of Alzheimer's Disease (AD) and its prodromal form, Mild Cognitive Impairment (MCI), has been the subject of extensive research. Some recent studies have shown promising results in the AD and MCI determination using structural and functional Magnetic Resonance Imaging (sMRI, fMRI), Positron Emission Tomography (PET) and Diffusion Tensor Imaging (DTI) modalities. Furthermore, fusion of imaging modalities in a supervised machine learning framework has shown promising direction of research.
In this paper we first review major trends in automatic classification methods such as feature extraction based methods as well as deep learning approaches in medical image analysis applied to the field of Alzheimer's Disease diagnostics. Then we propose our own design of a 3D Inception-based Convolutional Neural Network (CNN) for Alzheimer's Disease

10:20 Arxiv.org CSEnergy-efficient Decision Fusion for Distributed Detection in Wireless Sensor Networks. (arXiv:1809.03653v1 [cs.IT])

This paper proposes an energy-efficient counting rule for distributed detection by ordering sensor transmissions in wireless sensor networks. In the counting rule-based detection in an $N-$sensor network, the local sensors transmit binary decisions to the fusion center, where the number of all $N$ local-sensor detections are counted and compared to a threshold. In the ordering scheme, sensors transmit their unquantized statistics to the fusion center in a sequential manner; highly informative sensors enjoy higher priority for transmission. When sufficient evidence is collected at the fusion center for decision making, the transmissions from the sensors are stopped. The ordering scheme achieves the same error probability as the optimum unconstrained energy approach (which requires observations from all the $N$ sensors) with far fewer sensor transmissions. The scheme proposed in this paper

11.09.2018
22:49 ScienceDaily.comSeparating the sound from the noise in hot plasma fusion

For fusion power plants to be effective, scientists must find a way to trigger the low-to-high confinement transition, associated with zonal flows of plasma. Theoretically, these consist of both a stationary flow and one that oscillates at the geodesic acoustic mode. For the first time, researchers have detected GAM at two different points simultaneously within the reactor. This experimental setup will aid investigating the physics of zonal flows, and their role in the L-H transition.

18:08 Phys.orgSeparating the sound from the noise in hot plasma fusion

In the search for abundant clean energy, scientists around the globe look to fusion power, where isotopes of hydrogen combine to form a larger particle, helium, and release large amounts of energy in the process. For fusion power plants to be effective, however, scientists must find a way to trigger the low-to-high confinement transition, or "L-H transition" for short. After a L-H transition, the plasma temperature and density increase, producing more power.

05:55 Arxiv.org PhysicsFirst Investigation on the Radiation Field of the Gas-Filled Three-Axis Cylindrical Hohlraum. (arXiv:1809.03284v1 [physics.plasm-ph])

A novel ignition hohlraum named three-axis cylindrical hohlraum (TACH) is designed for indirect-drive inertial confinement fusion. TACH is a kind of 6 laser entrance holes (LEHs) hohlraum, which is orthogonally jointed of three cylindrical hohlraums. The first experiment on the radiation field of TACH was performed on Shenguang III laser facility. 24 laser beams were elected and injected into 6 LEHs quasi-symmetrically. Total laser energy was about 59 kJ, and the peak radiation temperature reached about 192 eV. Radiation temperature and pinhole images in gas-filled hohlraum are largely identical but with minor differences with those in vacuum hohlraum. All laser energy can be totally delivered into hohlraum in 3 ns duration even without filled gas in the hohlraum of 1.4 mm diameter. Plasma filling cannot be obviously suppressed even with 0.5 atm pressure gas in the small hohlraum.

05:55 Arxiv.org PhysicsThe conceptual design of 100-kA pulsed magnetic field generator for magnetized high-energy-density plasma experiments. (arXiv:1809.03278v1 [physics.plasm-ph])

This paper presents the conceptual design of a high-voltage pulser intended to generate 30-T magnetic fields for magneto-inertial fusion experiments at the OMEGA facility. The pulser uses a custom capacitor bank and two externally triggered spark gaps to drive a multi-turn coil. This new high-voltage pulser is capable of storing 10 times more energy than the previous system, using a higher charge voltage (from 20 to 30 kV) and a larger capacitance (from 1 {\mu}F to 5 {\mu}F). Circuit simulations show that this pulser can deliver 100 kA into a 60-nH, 14-m{\Omega} coil with a rise time of 1 {\mu}s. For a coil with 2 turns with an average coil diameter of 7.8 mm, this current translates into a 32-T peak magnetic field at coil center. This is a factor of three increase in the peak magnetic field compared to the present generator magnetic field capabilities.

10.09.2018
18:09 Phys.orgDiscovered: Optimal magnetic fields for suppressing instabilities in tokamaks

Fusion, the power that drives the sun and stars, produces massive amounts of energy. Scientists here on Earth seek to replicate this process, which merges light elements in the form of hot, charged plasma composed of free electrons and atomic nuclei, to create a virtually inexhaustible supply of power to generate electricity in what may be called a "star in a jar."

08:32 Arxiv.org CSPredicting Lung Nodule Malignancies by Combining Deep Convolutional Neural Network and Handcrafted Features. (arXiv:1809.02333v1 [cs.CV])

To predict lung nodule malignancy with a high sensitivity and specificity, we propose a fusion algorithm that combines handcrafted features (HF) into the features learned at the output layer of a 3D deep convolutional neural network (CNN). First, we extracted twenty-nine handcrafted features, including nine intensity features, eight geometric features, and twelve texture features based on grey-level co-occurrence matrix (GLCM) averaged from thirteen directions. We then trained 3D CNNs modified from three state-of-the-art 2D CNN architectures (AlexNet, VGG-16 Net and Multi-crop Net) to extract the CNN features learned at the output layer. For each 3D CNN, the CNN features combined with the 29 handcrafted features were used as the input for the support vector machine (SVM) coupled with the sequential forward feature selection (SFS) method to select the optimal feature subset and construct the

08.09.2018
01:28 WhatReallyHappened.comPluto SHOULD be a planet: Astronomers claim controversial demotion was based on 'since-disproven reasoning'

Scientists have proposed a new way to define planets based on 'the physics of the world itself.'
By the proposed geophysical definition: 'A planet is a sub-stellar mass body that has never undergone nuclear fusion and that has sufficient self-gravitation to assume a spheroidal shape adequately described by a triaxial ellipsoid regardless of its orbital parameters.'
Or, simply put, 'round objects in space that are smaller than stars.'

05.09.2018
07:39 Arxiv.org MathTowards an Intelligent Edge: Wireless Communication Meets Machine Learning. (arXiv:1809.00343v1 [cs.IT])

The recent revival of artificial intelligence (AI) is revolutionizing almost every branch of science and technology. Given the ubiquitous smart mobile gadgets and Internet of Things (IoT) devices, it is expected that a majority of intelligent applications will be deployed at the edge of wireless networks. This trend has generated strong interests in realizing an "intelligent edge" to support AI-enabled applications at various edge devices. Accordingly, a new research area, called edge learning, emerges, which crosses and revolutionizes two disciplines: wireless communication and machine learning. A major theme in edge learning is to overcome the limited computing power, as well as limited data, at each edge device. This is accomplished by leveraging the mobile edge computing (MEC) platform and exploiting the massive data distributed over a large number of edge devices. In such systems,

07:38 Arxiv.org CSTowards an Intelligent Edge: Wireless Communication Meets Machine Learning. (arXiv:1809.00343v1 [cs.IT])

The recent revival of artificial intelligence (AI) is revolutionizing almost every branch of science and technology. Given the ubiquitous smart mobile gadgets and Internet of Things (IoT) devices, it is expected that a majority of intelligent applications will be deployed at the edge of wireless networks. This trend has generated strong interests in realizing an "intelligent edge" to support AI-enabled applications at various edge devices. Accordingly, a new research area, called edge learning, emerges, which crosses and revolutionizes two disciplines: wireless communication and machine learning. A major theme in edge learning is to overcome the limited computing power, as well as limited data, at each edge device. This is accomplished by leveraging the mobile edge computing (MEC) platform and exploiting the massive data distributed over a large number of edge devices. In such systems,

07:38 Arxiv.org CSSimple Fusion: Return of the Language Model. (arXiv:1809.00125v1 [cs.CL])

Neural Machine Translation (NMT) typically leverages monolingual data in training through backtranslation. We investigate an alternative simple method to use monolingual data for NMT training: We combine the scores of a pre-trained and fixed language model (LM) with the scores of a translation model (TM) while the TM is trained from scratch. To achieve that, we train the translation model to predict the residual probability of the training data added to the prediction of the LM. This enables the TM to focus its capacity on modeling the source sentence since it can rely on the LM for fluency. We show that our method outperforms previous approaches to integrate LMs into NMT while the architecture is simpler as it does not require gating networks to balance TM and LM. We observe gains of between +0.24 and +2.36 BLEU on all four test sets (English-Turkish, Turkish-English, Estonian-English,

03.09.2018
05:57 Arxiv.org CSMMDF2018 Workshop Report. (arXiv:1808.10721v1 [cs.OH])

Driven by the recent advances in smart, miniaturized, and mass produced sensors, networked systems, and high-speed data communication and computing, the ability to collect and process larger volumes of higher veracity real-time data from a variety of modalities is expanding. However, despite research thrusts explored since the late 1990's, to date no standard, generalizable solutions have emerged for effectively integrating and processing multimodal data, and consequently practitioners across a wide variety of disciplines must still follow a trial-and-error process to identify the optimum procedure for each individual application and data sources. A deeper understanding of the utility and capabilities (as well as the shortcomings and challenges) of existing multimodal data fusion methods as a function of data and challenge characteristics has the potential to deliver better data analysis

31.08.2018
07:05 Arxiv.org PhysicsA Facility for Production and Laser Cooling of Cesium Isotopes and Isomers. (arXiv:1808.10280v1 [physics.ins-det])

We report on the design, installation, and test of an experimental facility for the production of ultra-cold atomic isotopes and isomers of cesium. The setup covers a broad span of mass numbers and nuclear isomers, allowing one to directly compare chains of isotopes and isotope/isomer pairs. Cesium nuclei are produced by fission or fusion-evaporation reactions using primary proton beams from a 130 MeV cyclotron impinging upon a suitable target. The species of interest is ejected from the target in ionic form, electrostatically accelerated, mass separated, and routed to a science chamber. Here, ions are neutralized by implantation in a thin foil, and extracted by thermal diffusion. A neutral vapor at room temperature is thus formed and trapped in a magneto-optical trap. Real-time fluorescence imaging and destructive absorption imaging provide information on the number of trapped atoms, their

30.08.2018
09:37 Arxiv.org PhysicsFuel Pellet Alignment in Heavy-Ion Inertial Fusion Reactor. (arXiv:1808.09671v1 [physics.plasm-ph])

In inertial confinement fusion, the scientific issues include the generation and transport of driver energy, the pellet design, the uniform target implosion physics, the realistic nuclear fusion reactor design, etc. In this paper, we present a pellet injection into a power reactor in heavy ion inertial fusion. We employ a magnetic correction method to reduce the pellet alignment error in heavy ion inertial fusion reactor chamber, including the gravity, the reactor gas drag force and the injection errors. We found that the magnetic correction device proposed in this paper is effective to construct a robust pellet injection system with a sufficiently small pellet alignment error.

28.08.2018
07:54 Arxiv.org PhysicsFluid simulations of plasma filaments in stellarator geometries with BSTING. (arXiv:1808.08899v1 [physics.plasm-ph])

Here we present first results simulating plasma filaments in non-axisymmetric geometries, using a fluid turbulence extension of the \boutxx~framework. This is made possible by the implementation of the Flux Coordinate Independent scheme for parallel derivatives, an extension of the metric tensor components which allows them to vary in three dimensions, and development of grid generation. Tests have been performed to confirm that the extension to three dimensional metric tensors does not compromise the accuracy and stability of the associated numerical operators. Recent changes to the FCI grid generator in \boutxx, including a curvilinear grid system which allows for potentially more efficient computation, are also presented. Initial simulations of seeded plasma filaments in a non-axisymmetric geometry are reported. We characterize filaments propagating in the closed-field-line region of a

07:54 Arxiv.org PhysicsLandau damping of Alfv\'enic modes in stellarators. (arXiv:1808.08862v1 [physics.plasm-ph])

It is found that the presence of the so-called non-axisymmetric resonances of wave-particle interaction in stellarators [which are associated with the lack of axial symmetry of the magnetic configuration, Kolesnichenko et al., Phys. Plasmas 9 (2002) 517] may have a strong stabilizing influence through Landau mechanism on the Toroidicity-induced Alfv\'en Eigenmodes (TAE) and isomon modes (Alfv\'enic modes with equal poloidal and toroidal mode numbers and frequencies in the continuum region) destabilized by the energetic ions. These resonances involve largest harmonics of the equilibrium magnetic field of stellarators and lead to absorption of the mode energy by thermal ions in medium pressure plasma, in which case the effect is large. On the other hand, at the high pressure attributed to, e.g., a Helias reactor, thermal ions can interact also with high frequency Alfv\'en gap modes

27.08.2018
19:39 Phys.orgArtificial intelligence project to help bring the power of the sun to Earth is picked for first U.S. exascale system

To capture and control the process of fusion that powers the sun and stars in facilities on Earth called tokamaks, scientists must confront disruptions that can halt the reactions and damage the doughnut-shaped devices. Now an artificial intelligence system under development at the U.S. Department of Energy's (DOE) Princeton Plasma Physics Laboratory (PPPL) and Princeton University to predict and tame such disruptions has been selected as an Aurora Early Science project by the Argonne Leadership Computing Facility, a DOE Office of Science User Facility.

03:47 Arxiv.org CSDecision fusion with multiple spatial supports by conditional random fields. (arXiv:1808.08024v1 [eess.IV])

Classification of remotely sensed images into land cover or land use is highly dependent on geographical information at least at two levels. First, land cover classes are observed in a spatially smooth domain separated by sharp region boundaries. Second, land classes and observation scale are also tightly intertwined: they tend to be consistent within areas of homogeneous appearance, or regions, in the sense that all pixels within a roof should be classified as roof, independently on the spatial support used for the classification. In this paper, we follow these two observations and encode them as priors in an energy minimization framework based on conditional random fields (CRFs), where classification results obtained at pixel and region levels are probabilistically fused. The aim is to enforce the final maps to be consistent not only in their own spatial supports (pixel and region) but also

24.08.2018
16:29 Phys.orgPushing the plasma density limit

For decades, researchers have been exploring ways to replicate on Earth the physical process of fusion that occurs naturally in the sun and other stars. Confined by its own strong gravitational field, the sun's burning plasma is a sphere of fusing particles, producing the heat and light that makes life possible on earth. But the path to a creating a commercially viable fusion reactor, which would provide the world with a virtually endless source of clean energy, is filled with challenges.

23.08.2018
07:51 Arxiv.org MathPosition Locationing for Millimeter Wave Systems. (arXiv:1808.07094v1 [cs.IT])

The vast amount of spectrum available for millimeter wave (mmWave) wireless communication systems will support accurate real-time positioning concurrent with communication signaling. This paper demonstrates that accurate estimates of the position of an unknown node can be determined using estimates of time of arrival (ToA), angle of arrival (AoA), as well as data fusion or machine learning. Real-world data at 28 GHz and 73 GHz is used to show that AoA-based localization techniques will need to be augmented with other positioning techniques. The fusion of AoA-based positioning with received power measurements for RXs in an office which has dimensions of 35 m by 65.5 m is shown to provide location accuracies ranging from 16 cm to 3.25 m, indicating promise for accurate positioning capabilities in future networks. Received signal strength intensity (RSSI) based positioning techniques that

07:51 Arxiv.org PhysicsA generalized Grad-Shafranov equation with plasma flow under a conformal coordinate transformation. (arXiv:1808.07291v1 [physics.plasm-ph])

We employ a conformal mapping transformation to solve a generalized Grad-Shafranov equation with incompressible plasma flow of arbitrary direction and construct particular up-down asymmetric D-shaped and diverted tokamak equilibria. The proposed method can also be employed as an alternative quasi-analytic method to solving two dimensional elliptic partial differential equations.

07:51 Arxiv.org CSPosition Locationing for Millimeter Wave Systems. (arXiv:1808.07094v1 [cs.IT])

The vast amount of spectrum available for millimeter wave (mmWave) wireless communication systems will support accurate real-time positioning concurrent with communication signaling. This paper demonstrates that accurate estimates of the position of an unknown node can be determined using estimates of time of arrival (ToA), angle of arrival (AoA), as well as data fusion or machine learning. Real-world data at 28 GHz and 73 GHz is used to show that AoA-based localization techniques will need to be augmented with other positioning techniques. The fusion of AoA-based positioning with received power measurements for RXs in an office which has dimensions of 35 m by 65.5 m is shown to provide location accuracies ranging from 16 cm to 3.25 m, indicating promise for accurate positioning capabilities in future networks. Received signal strength intensity (RSSI) based positioning techniques that

22.08.2018
22:56 ScienceDaily.comSteady as she goes: Scientists tame damaging plasma instabilities in fusion facilities

In a set of recent experiments, scientists have tamed a damaging plasma instability in a way that could lead to the efficient and steady-state operation of ITER, the international tokamak experiment under construction in France to demonstrate the practicality of fusion power.

20:10 Phys.orgSteady as she goes: Scientists tame damaging plasma instabilities in fusion facilities

Before scientists can capture and recreate the fusion process that powers the sun and stars to produce virtually limitless energy on Earth, they must first learn to control the hot plasma gas that fuels fusion reactions. In a set of recent experiments, scientists have tamed a plasma instability in a way that could lead to the efficient and steady state operation of ITER, the international experiment under construction in France to demonstrate the feasibility of fusion power. Such continuous operation will be essential for future fusion devices.

03:32 Arxiv.org PhysicsGyrokinetic GENE simulations of DIII-D near-edge L-mode plasmas. (arXiv:1808.06607v1 [physics.plasm-ph])

We present gyrokinetic simulations with the GENE code addressing the near-edge region of an L-mode discharge in the DIII-D tokamak. At radial position $\rho=0.80$, we find that radial ion transport is nonlinearly quenched by a strong poloidal zonal flow with a clear Dimits shift. Simulations with the ion temperature gradient increased by $\sim40\%$ above the nominal value give electron and ion heat fluxes that are in simultaneous agreement with the experiment. This gradient increase is within the uncertainty of the Charge Exchange Recombination (CER) diagnostic measurements at the $1.6 \sigma$ level. Multi-scale simulations are carried out with realistic mass ratio and geometry for the first time in the near-edge. These suggest that highly unstable ion temperature gradient driven modes of the flux-matched ion-scale simulations strongly suppress electron-scale transport, such that ion-scale

21.08.2018
18:08 Phys.orgHigher plasma densities, more efficient tokamaks

When the density of the hot, ionized gas (known as a plasma) in a tokamak exceeds a certain limit, it usually leads to a rapid loss of heat and plasma currents. The currents are required to confine the plasma. Such events can seriously damage the tokamak. Before the disruption, scientists often observe large magnetic islands. Magnetic islands are thermally isolated, small "bubbles" of plasma. Recent investigations confirmed that scientists could use these islands to correctly predict the density limit. The team showed that when the island becomes large enough, the hot plasma core mixes with the cool plasma and causes the disruption. They can use this information to control the disruptions.

15.08.2018
08:24 Arxiv.org PhysicsTwo-Fluid Nonlinear Theory of Response of Tokamak Plasma to Resonant Magnetic Perturbation. (arXiv:1808.04482v1 [physics.plasm-ph])

A comprehensive two-fluid nonlinear theory of magnetic reconnection driven at a single, tearing-stable, rational surface embedded in an H-mode tokamak plasma is presented. The surface is assumed to be resonant with one of the dominant helical harmonics of an applied resonant magnetic perturbation (RMP). The theory described in this paper is highly relevant to the problem of understanding the physics of RMP-induced edge localized mode (ELM) suppression in tokamak plasmas.

11.08.2018
19:40 WhatReallyHappened.comUK nuclear fusion reactor could supply the grid with clean power

10.08.2018
08:11 Arxiv.org PhysicsDesign and measurement methods for a lithium vapor box similarity experiment. (arXiv:1808.02908v1 [physics.ins-det])

The lithium vapor box divertor is a concept for handling the extreme divertor heat fluxes in magnetic fusion devices. In a baffled slot divertor, plasma interacts with a dense cloud of Li vapor which radiates and cools the plasma, leading to recombination and detachment. Before testing on a tokamak the concept should be validated: we plan to study detachment and heat redistribution by a Li vapor cloud in laboratory experiments. Mass changes and temperatures are measured to validate a Direct Simulation Monte Carlo model of neutral Li. The initial experiment involves a 5 cm diameter steel box containing 10 g of Li held at 650 degrees C as vapor flows out a wide nozzle into a similarly-sized box at a lower temperature. Diagnosis is made challenging by the required material compatibility with lithium vapor. Vapor pressure a steep function of temperature, so to validate mass flow models to within

09.08.2018
17:04 Phys.orgDiamond capsules improve performance of laser fusion

Osaka University-led researchers demonstrated that the perturbation of laser imprinting on a capsule for nuclear fusion fuel made from stiff and heavy materials was mitigated. Using the latest chemical vapor deposition (CVD) method, they also produced high-precision diamond fuel capsules, a key technology applicable for fusion fuel.

08.08.2018
06:40 Arxiv.org CSLearning-Aided Physical Layer Authentication as an Intelligent Process. (arXiv:1808.02456v1 [cs.CR])

Performance of the existing physical layer authentication schemes could be severely affected by the imperfect estimates and variations of the communication link attributes used. The commonly adopted static hypothesis testing for physical layer authentication faces significant challenges in time-varying communication channels due to the changing propagation and interference conditions, which are typically unknown at the design stage. To circumvent this impediment, we propose an adaptive physical layer authentication scheme based on machine-learning as an intelligent process to learn and utilize the complex and time-varying environment, and hence to improve the reliability and robustness of physical layer authentication. Explicitly, a physical layer attribute fusion model based on a kernel machine is designed for dealing with multiple attributes without requiring the knowledge of their

07.08.2018
09:23 Arxiv.org PhysicsIntrinsic rotation driven by turbulent acceleration. (arXiv:1808.01429v1 [physics.plasm-ph])

Differential rotation is induced in tokamak plasmas when an underlying symmetry of the governing gyrokinetic-Maxwell system of equations is broken. One such symmetry-breaking mechanism is considered here: the turbulent acceleration of particles along the mean magnetic field. This effect, often referred to as the `parallel nonlinearity', has been implemented in the $\delta f$ gyrokinetic code $\texttt{stella}$ and used to study the dependence of turbulent momentum transport on the plasma size and on the strength of the turbulence drive. For JET-like parameters with a wide range of driving temperature gradients, the momentum transport induced by the inclusion of turbulent acceleration is similar to or smaller than the ratio of the ion Larmor radius to the plasma minor radius. This low level of momentum transport is explained by demonstrating an additional symmetry that prohibits momentum

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