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15.11.2021
05:08 Arxiv.org CS Sequential Aggregation and Rematerialization: Distributed Full-batch Training of Graph Neural Networks on Large Graphs. (arXiv:2111.06483v1 [cs.LG])

We present the Sequential Aggregation and Rematerialization (SAR) scheme for distributed full-batch training of Graph Neural Networks (GNNs) on large graphs. Large-scale training of GNNs has recently been dominated by sampling-based methods and methods based on non-learnable message passing. SAR on the other hand is a distributed technique that can train any GNN type directly on an entire large graph. The key innovation in SAR is the distributed sequential rematerialization scheme which sequentially re-constructs then frees pieces of the prohibitively large GNN computational graph during the backward pass. This results in excellent memory scaling behavior where the memory consumption per worker goes down linearly with the number of workers, even for densely connected graphs. Using SAR, we report the largest applications of full-batch GNN training to-date, and demonstrate large memory savings as the number of workers increases. We also present a general technique based on kernel fusion

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11.11.2021
16:56 Phys.org Radio-frequency wave scattering improves fusion simulations

In the quest for fusion energy, understanding how radio-frequency (RF) waves travel (or "propagate") in the turbulent interior of a fusion furnace is crucial to maintaining an efficient, continuously operating power plant. Transmitted by an antenna in the doughnut-shaped vacuum chamber common to magnetic confinement fusion devices called tokamaks, RF waves heat the plasma fuel and drive its current around the toroidal interior. The efficiency of this process can be affected by how the wave's trajectory is altered (or "scattered") by conditions within the chamber.

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10.11.2021
11:34 Arxiv.org CS Machine Learning for Multimodal Electronic Health Records-based Research: Challenges and Perspectives. (arXiv:2111.04898v1 [cs.LG])

Background: Electronic Health Records (EHRs) contain rich information of patients' health history, which usually include both structured and unstructured data. There have been many studies focusing on distilling valuable information from structured data, such as disease codes, laboratory test results, and treatments. However, relying on structured data only might be insufficient in reflecting patients' comprehensive information and such data may occasionally contain erroneous records. Objective: With the recent advances of machine learning (ML) and deep learning (DL) techniques, an increasing number of studies seek to obtain more accurate results by incorporating unstructured free-text data as well. This paper reviews studies that use multimodal data, i.e. a combination of structured and unstructured data, from EHRs as input for conventional ML or DL models to address the targeted tasks. Materials and Methods: We searched in the Institute of Electrical and Electronics Engineers (IEEE)

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11:34 Arxiv.org CS Equilibrium reconstruction for ITER. (arXiv:2111.04841v1 [physics.plasm-ph])

In this short paper we present the first application of the IMAS compatible code NICE to equilibrium reconstrution for ITER geometry. The inverse problem is formulated as a least square problem and the numerical methods implemented in NICE in order to solve it are presented. The results of a numerical experiment are shown: a reference equilibrium is computed from which a set of synthetic magnetic measurements are extracted. Then these measurements are used successfully to reconstruct the equilibrium of the plasma.

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10:24 Arxiv.org Physics Equilibrium reconstruction for ITER. (arXiv:2111.04841v1 [physics.plasm-ph])

In this short paper we present the first application of the IMAS compatible code NICE to equilibrium reconstrution for ITER geometry. The inverse problem is formulated as a least square problem and the numerical methods implemented in NICE in order to solve it are presented. The results of a numerical experiment are shown: a reference equilibrium is computed from which a set of synthetic magnetic measurements are extracted. Then these measurements are used successfully to reconstruct the equilibrium of the plasma.

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10:02 Arxiv.org Math Equilibrium reconstruction for ITER. (arXiv:2111.04841v1 [physics.plasm-ph])

In this short paper we present the first application of the IMAS compatible code NICE to equilibrium reconstrution for ITER geometry. The inverse problem is formulated as a least square problem and the numerical methods implemented in NICE in order to solve it are presented. The results of a numerical experiment are shown: a reference equilibrium is computed from which a set of synthetic magnetic measurements are extracted. Then these measurements are used successfully to reconstruct the equilibrium of the plasma.

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09.11.2021
07:08 Arxiv.org CS Inferring untrained complex dynamics of delay systems using an adapted echo state network. (arXiv:2111.03706v1 [cs.LG])

Caused by finite signal propagation velocities, many complex systems feature time delays that may induce high-dimensional chaotic behavior and make forecasting intricate. Here, we propose an echo state network adaptable to the physics of systems with arbitrary delays. After training the network to forecast a system with a unique and sufficiently long delay, it already learned to predict the system dynamics for all other delays. A simple adaptation of the network's topology allows us to infer untrained features such as high-dimensional chaotic attractors, bifurcations, and even multistabilities, that emerge with shorter and longer delays. Thus, the fusion of physical knowledge of the delay system and data-driven machine learning yields a model with high generalization capabilities and unprecedented prediction accuracy.

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05:52 Arxiv.org Physics Experiments conducted in the burning plasma regime with inertial fusion implosions. (arXiv:2111.04640v1 [physics.plasm-ph])

An experimental program is currently underway at the National Ignition Facility (NIF) to compress deuterium and tritium (DT) fuel to densities and temperatures sufficient to achieve fusion and energy gain. The primary approach being investigated is indirect drive inertial confinement fusion (ICF), where a high-Z radiation cavity (a hohlraum) is heated by lasers, converting the incident energy into x-ray radiation which in turn drives the DT fuel filled capsule causing it to implode. Previous experiments reported DT fuel gain exceeding unity [O.A. Hurricane et al., Nature 506, 343 (2014)] and then exceeding the kinetic energy of the imploding fuel [S. Le Pape et al., Phys. Rev. Lett. 120, 245003 (2018)]. We report on recent experiments that have achieved record fusion neutron yields on NIF, greater than 100 kJ with momentary fusion powers exceeding 1PW, and have for the first time entered the burning plasma regime where fusion alpha-heating of the fuel exceeds the energy delivered to

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05:52 Arxiv.org Physics Carbon Dioxide, Fusion, and Stellarators. (arXiv:2111.04213v1 [physics.plasm-ph])

The importance of stopping the increase in atmospheric carbon dioxide is more broadly appreciated than is the need for rational planning in order to achieve desired results. The November 5, 2021 statement by the U.S. Secretary of Energy on constructing a system for the direct removal of CO$_2$ from the air may have broader implications. Even if CO$_2$ emissions are stopped by 2050, such a system is required to restore the CO$_2$ concentration to its present level in less than three centuries. Perhaps this statement will increase the recognition of the importance of reason relative to emotion in obtaining a solution to the CO$_2$ problem. When reason dominates, the importance of fusion and the rapid development stellarators becomes manifest.

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05:33 Arxiv.org Math Magnetic confinement for the 2D axisymmetric relativistic Vlasov-Maxwell system in an annulus. (arXiv:2111.04583v1 [math.AP])

Although the nuclear fusion process has received a great deal of attention in recent years, the amount of mathematical analysis that supports the stability of the system seems to be relatively insufficient. This paper deals with the mathematical analysis of the magnetic confinement of the plasma via kinetic equations. We prove the global wellposedness of the Vlasov-Maxwell system in a two-dimensional annulus when a huge (but finite-in-time) external magnetic potential is imposed near the boundary. We assume that the solution is axisymmetric. The authors hope that this work is a step towards a more generalized work on the three-dimensional Tokamak structure. The highlight of this work is the physical assumptions on the external magnetic potential well which remains finite within a finite time interval and from that, we prove that the plasma never touches the boundary. In addition, we provide a sufficient condition on the magnitude of the external magnetic potential to guarantee that the

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08.11.2021
19:58 WhatReallyHappened.com Helium-3: How The Moon Could Solve All Of Earth's Energy Problems

Thirty, 20, or even 10 years ago, there was neither the political will, the technology nor the money needed to mine space resources, but things are changing, and they are changing fast, an ex-CIA space analyst warns. Solar space power, multi-billion asteroid mining, and the Moon’s Helium-3 resources are up for grab. As a result, the U.S., China, Russia, Europe, the U.K. and other countries are playing into this silent war. If today the world were to switch entirely to green energy — plugging out of fossil fuels, the electric grids would collapse in a final dying effort to meet demand. Helium-3 fusion has been presented as the “Holy Grail” of energy. Helium-3 fusion is what powers our Sun and stars. It produces no radioactive waste, and just 25 tons of it could power an entire country for a year. The catch? There are only 100 kilos of Helium-3 on our planet.

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15:10 Phys.org Calling all 'fusioneers'! New US fusion energy website launches

The U.S. Fusion Outreach Team, a grassroots organization in the fusion community focused on reducing barriers to outreach efforts, has launched a new centralized website to engage an expanding workforce, media, educators, and the public in the journey toward a world powered by fusion energy.

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15:10 Phys.org Visualizing the microscopic world of fast ions in fusion devices

The U.S. scientific community is currently conceptualizing the first nuclear fusion power plants, which will revolutionize energy production. Like the sun and stars, a fusion power plant will produce energy by fusing light elements, like hydrogen, into heavier ones, like helium, at temperatures higher than 25 million F. Fusing hydrogen to produce helium releases about 4 million times more energy than a chemical reaction, such as the burning of coal, oil, or gas. Yet, the fusion reaction neither releases carbon dioxide in the atmosphere, nor results in radioactive biproducts, which makes it one of the most promising ways to produce clean energy on Earth.

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15:10 Phys.org Unveiling the steady progress toward fusion energy gain

The march towards fusion energy gain, required for commercial fusion energy, is not always visible. Progress occurs in fits and starts through experiments in national laboratories, universities, and more recently at private companies. Sam Wurzel, a Technology-to-Market Advisor at the Advanced Research Projects Agency-Energy (ARPA-E), details and highlights this progress over the last 60 years by extracting and cataloging the performance of over 70 fusion experiments in this time span. The work illustrates the history and development of different approaches including magnetic-fusion devices such as tokamaks, stellarators and other "alternate concepts," laser-driven devices such as inertial confinement fusion (ICF), and hybrid approaches including liner-imploded and z-pinch concepts.

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15:10 Phys.org Harnessing hot helium ash to drive rotation in fusion reactors

In controlled nuclear fusion, heavy isotopes of hydrogen fuse into helium, releasing a huge amount of energy in the process. A large portion of the energy released by a laboratory fusion reaction goes into hot helium ash (an impurity in the plasma that bears no resemblance to ash from a fire). This ash is around 30 billion degrees Celsius, compared to 200 million degrees for the bulk plasma. For context, the temperature at the core of the sun is 15 million C. The ash energy may be captured by a plasma wave, via wave-particle interaction known as alpha channeling. The energy in the wave can then be absorbed by fuel ions, powering the fusion reaction.

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15:10 Phys.org Feeling the heat: Fusion reactors used to test spacecraft heat shields

Spacecraft have long used heat shields for protection during entry into planetary atmospheres. Future missions to the outer solar system will need more sophisticated materials than currently exist. The extreme heating conditions needed to study new shield materials are, however, very difficult to achieve experimentally on Earth. Scientists working at the DIII-D National Fusion Facility at General Atomics (GA) recently developed an innovative approach that uses the conditions inside a fusion reactor for testing heat shield materials.

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15:10 Phys.org Neutral particles a drag on disruptive plasma blobs

For decades, scientists have been working to harness clean, renewable fusion energy, which occurs naturally in stars like our sun. Using strong magnetic fields to confine hot plasmas within a donut-shaped device called a tokamak, researchers can generate conditions necessary to induce fusion reactions.

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15:10 Phys.org Upgraded code reveals a source of damaging fusion disruptions

Researchers at the U.S. Department of Energy's Princeton Plasma Physics Laboratory (PPPL) and Los Alamos National Laboratory have uncovered a key process behind a major challenge called thermal quenches, the rapid heat loss in hot plasmas that can occur in doughnut-shaped tokamak fusion devices. Such quenches are sudden drops of electron heat in the plasma that fuels fusion reactions, drops that can create damaging disruptions inside the tokamak. Understanding the physics behind these quenches, caused by powerful perturbations in the magnetic fields that confine the plasma in tokamaks, could lead to methods to mitigate or prevent them.

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15:10 Phys.org Passive-aggressive: New coil stands ready to tame runaway electrons

In the race toward practical fusion energy, tokamaks (donut-shaped plasma devices) are the leading concept—they have achieved better confinement and higher plasma temperatures than any other configuration. Two major magnetic fields are used to contain the plasma: a toroidal field (along the axes of the donut) produced by external coils and the field from a ring current flowing in the plasma itself. The performance of a tokamak, however, comes with an Achilles heel—the possibility of disruptions, a sudden termination of the plasma driven by instabilities in the plasma current. Since the plasma current provides the equilibrium and confinement for the tokamak, the challenge of taming disruptions must be addressed and solved.

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09:08 Arxiv.org CS RASEC: Rescaling Acquisition Strategy with Energy Constraints under SE-OU Fusion Kernel for Active Trachea Palpation and Incision Recommendation in Laryngeal Region. (arXiv:2111.03235v1 [cs.RO])

A novel palpation-based incision detection strategy in the laryngeal region, potentially for robotic tracheotomy, is proposed in this letter. A tactile sensor is introduced to measure tissue hardness in the specific laryngeal region by gentle contact. The kernel fusion method is proposed to combine the Squared Exponential (SE) kernel with Ornstein-Uhlenbeck (OU) kernel to figure out the drawbacks that the existing kernel functions are not sufficiently optimal in this scenario. Moreover, we further regularize exploration factor and greed factor, and the tactile sensor's moving distance and the robotic base link's rotation angle during the incision localization process are considered as new factors in the acquisition strategy. We conducted simulation and physical experiments to compare the newly proposed algorithm - Rescaling Acquisition Strategy with Energy Constraints (RASEC) in trachea detection with current palpation-based acquisition strategies. The result indicates that the

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07:51 Arxiv.org Physics Quantification of systematic errors in the electron density and temperature measured with Thomson scattering at W7-X. (arXiv:2111.03562v1 [physics.plasm-ph])

The electron density and temperature profiles measured with Thomson scattering at the stellarator Wendelstein 7-X show features which seem to be unphysical, but so far could not be associated with any source of error considered in the data processing. A detailed Bayesian analysis reveals that errors in the spectral calibration cannot explain the features observed in the profiles. Rather, it seems that small fluctuations in the laser position are sufficient to affect the profile substantially. The impact of these fluctuations depends on the laser position itself, which, in turn, provides a method to find the optimum laser alignment in the future.

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06.11.2021
22:38 TechInvestorNews.com The buzz about fusion energy: Expert explains industry’s ‘reinvigoration’ as tech attracts VC dollar (Lisa Stiffler/GeekWire)

Lisa Stiffler / GeekWireThe buzz about fusion energy: Expert explains industry’s ‘reinvigoration’ as tech attracts VC dollar - For decades, the promise of harnessing the power of fusion on a commercial scale to create vast amounts of carbon-free energy has hovered just out of reach for scientists. At last that tantalizing dream appears closer to reality and the cash is starting to flow. This week, fusion energy startup ...

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05.11.2021
15:31 TechInvestorNews.com Silicon Valley exec Sam Altman puts $375 million, his biggest investment ever, into fusion start-up (CNBC: Top News)

CNBC: Top NewsSilicon Valley exec Sam Altman puts $375 million, his biggest investment ever, into fusion start-up - Its part of Altmans three-part utopian vision, which is focused on growing abundance through technological innovation. ...

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14:20 CNBC technology Silicon Valley exec Sam Altman puts $375 million, his biggest investment ever, into fusion start-up Helion Energy

It's part of Altman's three-part utopian vision, which is focused on growing abundance through technological innovation.

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14:20 CNBC top news Silicon Valley exec Sam Altman puts $375 million, his biggest investment ever, into fusion start-up Helion Energy

It's part of Altman's three-part utopian vision, which is focused on growing abundance through technological innovation.

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10:12 Arxiv.org CS Earthquake detection at the edge: IoT crowdsensing network. (arXiv:2111.02869v1 [cs.DC])

Earthquake Early Warning state of the art systems rely on a network of sensors connected to a fusion center in a client-server paradigm. Instead, we propose moving computation to the edge, with detector nodes that probe the environment and process information from nearby probes to detect earthquakes locally. Our approach tolerates multiple node faults and partial network disruption and keeps all data locally, enhancing privacy. This paper describes our proposal's rationale and explains its architecture. We then present an implementation using Raspberry, NodeMCU, and the Crowdquake machine learning model.

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10:12 Arxiv.org CS Improving Pose Estimation through Contextual Activity Fusion. (arXiv:2111.02500v1 [cs.CV])

This research presents the idea of activity fusion into existing Pose Estimation architectures to enhance their predictive ability. This is motivated by the rise in higher level concepts found in modern machine learning architectures, and the belief that activity context is a useful piece of information for the problem of pose estimation. To analyse this concept we take an existing deep learning architecture and augment it with an additional 1x1 convolution to fuse activity information into the model. We perform evaluation and comparison on a common pose estimation dataset, and show a performance improvement over our baseline model, especially in uncommon poses and on typically difficult joints. Additionally, we perform an ablative analysis to indicate that the performance improvement does in fact draw from the activity information.

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08:54 Arxiv.org Physics Production of 177Lu with deuterons at IFMIF-DONES facility. (arXiv:2111.02469v1 [physics.ins-det])

The International Fusion Materials Irradiation Facility - Demo Oriented NEutron Source (IFMIF-DONES) is a single-sited novel Research Infrastructure for testing, validation and qualification of the materials to be used in a fusion reactor. The main purpose of IFMIF-DONES is related to fusion technology and neutron irradiation of the materials to be used in the future fusion power plants. However, there is an important effort to take advantage of the outstanding characteristics of the facility in terms of neutrons and deuterons. One of the applications could be radioisotopes production with deuterons and neutrons. We discuss here the possible production of radioisotopes with deuterons at DONES. In this work, we have focused on the production of 177Lu with deuterons. The study has been carried out through the design and simulation of a device as cooling system for the sample producing the radioisotope. The results show the viability of using DONES for such production. In addition, the

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04.11.2021
06:00 Arxiv.org CS ML-PersRef: A Machine Learning-based Personalized Multimodal Fusion Approach for Referencing Outside Objects From a Moving Vehicle. (arXiv:2111.02327v1 [cs.HC])

Over the past decades, the addition of hundreds of sensors to modern vehicles has led to an exponential increase in their capabilities. This allows for novel approaches to interaction with the vehicle that go beyond traditional touch-based and voice command approaches, such as emotion recognition, head rotation, eye gaze, and pointing gestures. Although gaze and pointing gestures have been used before for referencing objects inside and outside vehicles, the multimodal interaction and fusion of these gestures have so far not been extensively studied. We propose a novel learning-based multimodal fusion approach for referencing outside-the-vehicle objects while maintaining a long driving route in a simulated environment. The proposed multimodal approaches outperform single-modality approaches in multiple aspects and conditions. Moreover, we also demonstrate possible ways to exploit behavioral differences between users when completing the referencing task to realize an adaptable

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03.11.2021
07:50 Arxiv.org Math Non-Invertible Duality Defects in 3+1 Dimensions. (arXiv:2111.01139v1 [hep-th])

For any quantum system invariant under gauging a higher-form global symmetry, we construct a non-invertible topological defect by gauging in only half of spacetime. This generalizes the Kramers-Wannier duality line in 1+1 dimensions to higher spacetime dimensions. We focus on the case of a one-form symmetry in 3+1 dimensions, and determine the fusion rule. From modular invariance and a direct analysis of one-form symmetry protected topological phases, we show that the existence of certain kinds of duality defects is intrinsically incompatible with a trivially gapped phase. By further assuming time-reversal symmetry, we find that the presence of certain duality defects implies that the low-energy phase has to be gapless unless the one-form symmetry is spontaneously broken. We give an explicit realization of this duality defect in the free Maxwell theory, both in the continuum and in a modified Villain lattice model. The duality defect is realized by a Chern-Simons coupling between the

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02.11.2021
10:17 Arxiv.org Physics Characterization of Pedestal Burst Instabilities during I-mode to H-mode Transition in the EAST Tokamak. (arXiv:2111.00753v1 [physics.plasm-ph])

Quasi-periodic Pedestal Burst Instabilities (PBIs), which features alternative turbulence suppression and bursts, had been clearly identified by various edge diagnostics during I-mode to H-mode transition in the EAST Tokamak. Prior to each PBI, a significant increase of density gradient close to the pedestal top can be clearly distinguished, then the turbulence burst is generated, accompanied by the relaxation of the density profile, which suggests that the turbulence is probably driven by the density gradient and then generated outward particle flux. The relative density perturbation caused by PBIs is about $1.5\% - 10\%$. Statistic analysis show that the pedestal normalized density gradient $R/L_n$ triggering the first PBI has a threshold, mostly in the range of $22 - 24$. $R/L_n$ triggering the last PBI is about $30 - 40$ and seems to increase with the loss power and the chord-averaged density. In addition, the frequency of PBI is likely to be inversely proportional to the

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29.10.2021
17:08 Phys.org Integrated edge localized mode suppression and divertor power flux control for ITER

Using Resonant Magnetic Perturbations (RMP), researchers led by Prof. Sun Youwen from the Institute of Plasma Physics of the Chinese Academy of Sciences took the lead in demonstrating the integrated Edge Localized Mode (ELM) and divertor power flux control in target plasmas with parameters close to International Thermonuclear Experimental Reactor (ITER) high fusion gain (Q) operation.

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08:05 Arxiv.org CS Model-based electron density profile estimation and control, applied to ITER. (arXiv:2110.14975v1 [physics.plasm-ph])

In contemporary magnetic confinement devices, the density distribution is sensed with interferometers and actuated with feedback controlled gas injection and open-loop pellet injection. This is at variance with the density control for ITER and DEMO, that will depend mainly on pellet injection as an actuator in feed-back control. This paper presents recent developments in state estimation and control of the electron density profile for ITER using relevant sensors and actuators. As a first step, Thomson scattering is included in an existing dynamic state observer. Second, model predictive control is developed as a strategy to regulate the density profile while avoiding limits associated with the total density (Greenwald limit) or gradients in the density distribution (e.g. neo-classical impurity transport). Simulations show that high quality density profile estimation can be achieved with Thomson Scattering and that the controller is capable of regulating the distribution as desired.

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06:59 Arxiv.org Physics Polychromatic drivers for inertial fusion energy. (arXiv:2110.15100v1 [physics.optics])

Although tremendous achievements have been made toward inertial confinement fusion, laser plasma instabilities (LPIs) remain to be the inevitable problem for current drive schemes. To mitigate these instabilities, here we propose the design of polychromatic drivers for the generation of multicolor beams based upon optical parametric amplification and frequency conversion technologies. Each polychromatic light has four colors of monochromatic beamlets with a full spectrum width of 3\%, and the beamlet colors of any two adjacent flanges are different. The suppression effects of such polychromatic lights have been investigated via particle-in-cell simulations, which indicate that more than 35\% of the incident energies can be saved from the LPIs compared with monochromatic lasers for the direct drive scheme, or high-density filled target for the indirect drive scheme. The proposed polychromatic drivers are based on the matured technologies, and thus may pave the way towards realization of

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06:59 Arxiv.org Physics Model-based electron density profile estimation and control, applied to ITER. (arXiv:2110.14975v1 [physics.plasm-ph])

In contemporary magnetic confinement devices, the density distribution is sensed with interferometers and actuated with feedback controlled gas injection and open-loop pellet injection. This is at variance with the density control for ITER and DEMO, that will depend mainly on pellet injection as an actuator in feed-back control. This paper presents recent developments in state estimation and control of the electron density profile for ITER using relevant sensors and actuators. As a first step, Thomson scattering is included in an existing dynamic state observer. Second, model predictive control is developed as a strategy to regulate the density profile while avoiding limits associated with the total density (Greenwald limit) or gradients in the density distribution (e.g. neo-classical impurity transport). Simulations show that high quality density profile estimation can be achieved with Thomson Scattering and that the controller is capable of regulating the distribution as desired.

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00:05 Technology.org How Close is Nuclear Fusion Power?

Fusion power should replace many of our traditional sources of energy. This technology promises to generate power to

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28.10.2021
10:48 Arxiv.org CS NIDA-CLIFGAN: Natural Infrastructure Damage Assessment through Efficient Classification Combining Contrastive Learning, Information Fusion and Generative Adversarial Networks. (arXiv:2110.14518v1 [cs.LG])

During natural disasters, aircraft and satellites are used to survey the impacted regions. Usually human experts are needed to manually label the degrees of the building damage so that proper humanitarian assistance and disaster response (HADR) can be achieved, which is labor-intensive and time-consuming. Expecting human labeling of major disasters over a wide area gravely slows down the HADR efforts. It is thus of crucial interest to take advantage of the cutting-edge Artificial Intelligence and Machine Learning techniques to speed up the natural infrastructure damage assessment process to achieve effective HADR. Accordingly, the paper demonstrates a systematic effort to achieve efficient building damage classification. First, two novel generative adversarial nets (GANs) are designed to augment data used to train the deep-learning-based classifier. Second, a contrastive learning based method using novel data structures is developed to achieve great performance. Third, by using

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09:41 Arxiv.org Physics Subpicosecond dynamics of pre-plasma on a solid, formed by a ultra-high contrast, relativistic intensity pulse. (arXiv:2110.14595v1 [physics.plasm-ph])

Using spectral interferometry technique, we measured subpicosecond time-resolved pre-plasma scale lengths and early expansion ($

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09:41 Arxiv.org Physics Proton deflectometry with in situ x-ray reference for absolute measurement of electromagnetic fields in high-energy-density plasmas. (arXiv:2110.14510v1 [physics.plasm-ph])

We report a technique of proton deflectometry which uses a grid and an in situ reference x-ray grid image for precise measurements of magnetic fields in high-energy density plasmas. A D$^3$He fusion implosion provides a bright point-source of both protons and x-rays, which is split into beamlets by a mesh grid. The protons undergo deflections as they propagate through the plasma region of interest, whereas the x-rays travel along straight lines. The x-ray image therefore provides a zero-deflection reference image. The line-integrated magnetic fields are inferred from the shifts of beamlets between the deflected (proton) and reference (x-ray) images. We developed a system for analysis of this data, including automatic algorithms to find beamlet locations and calculate their deflections from the reference image. The technique is verified in an experiment performed at OMEGA to measure a non-uniform magnetic field in vacuum, then applied to observe the interaction of an expanding plasma

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27.10.2021
19:59 Phys.org New research looks at process of magnetic flux generation in ICF implosions

Lawrence Livermore National Laboratory (LLNL) researchers now have a better understanding on how strong the magnetic fields are in an inertial confinement fusion (ICF) implosion at the National Ignition Facility (NIF), the world's most energetic laser.

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05:18 Arxiv.org Physics A self-consistent multi-component model of plasma turbulence and kinetic neutral dynamics for the simulation of the tokamak boundary. (arXiv:2110.13335v1 [physics.plasm-ph])

A self-consistent model is presented for the simulation of a multi-component plasma in the tokamak boundary. A deuterium plasma is considered, with the plasma species that include electrons, deuterium atomic ions and deuterium molecular ions, while the deuterium atoms and molecules constitute the neutral species. The plasma and neutral models are coupled via a number of collisional interactions, which include dissociation, ionization, charge-exchange and recombination processes. The derivation of the three-fluid drift-reduced Braginskii equations used to describe the turbulent plasma dynamics is presented, including its boundary conditions. The kinetic advection equations for the neutral species are also derived, and their numerical implementation discussed. The first results of multi-component plasma simulations carried out by using the GBS code are then presented and analyzed, being compared with results obtained with the single-component plasma model.

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26.10.2021
15:56 Phys.org Researchers report argon fluoride laser fusion research findings

U.S. Naval Research Laboratory experts race toward sustainable clean energy with advances in fusion energy. Steve Obenschain, Ph.D., a research physicist at NRL, said nuclear fusion would be a valuable addition to clean energy sources because it can provide baseload electrical power when the sun does not shine and the wind does not blow. The baseload is the minimum level of demand on an electrical grid over a span of time, for example, one week.

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07:59 Arxiv.org Physics Edge plasma relaxations due to diamagnetic stabilization. (arXiv:2110.12847v1 [physics.plasm-ph])

A new mechanism for pressure profile relaxations in an edge tokamak plasma is derived from simulations within the two-fluid three-dimensional turbulence code EMEDGE3D. The relaxation is due to diamagnetic coupling in the resistive ballooning/drift wave dynamics: unstable modes experience explosive growth at high pressure gradients after a phase in which they are stabilized by the diamagnetic coupling leading to the onset of a transport barrier. The sheared $E\times B$ flow does not play any significant role. After relaxation the transport barrier forms again and it sets the conditions for a novel relaxation, resulting in an oscillatory behavior. We find that energy flux into the scrape of layer decreases with increasing oscillation frequency and that the oscillations are tamed by increasing plasma temperature. This behavior is reminiscent of so-called type III Edge Localized Modes. A one-dimensional model reproducing the relaxations is also derived.

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07:59 Arxiv.org Physics A quasi-continuous exhaust scenario for a fusion reactor: the renaissance of small edge localized modes. (arXiv:2110.12664v1 [physics.plasm-ph])

Tokamak operational regimes with small edge localized modes (ELMs) could be a solution to the problem of large transient heat loads in future fusion reactors because they provide quasi-continuous exhaust while keeping a good plasma confinement. A ballooning mode mechanism near the last closed flux surface (LCFS) governed by an interplay of the pressure gradient and the magnetic shear there has been proposed for small ELMs in high density ASDEX Upgrade and TCV discharges. In this manuscript we explore different factors relevant for plasma edge stability in a wide range of edge safety factors by changing the connection length between the good and the bad curvature side. Simultaneously this influences the stabilizing effect of the local magnetic shear close to the LCFS as well as the $E \times B$ flow shear. Ideal ballooning stability calculations with the HELENA code reveal that small ELM plasmas are indeed unstable against ballooning modes very close to the LCFS but can exhibit second

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07:59 Arxiv.org Physics Machine learning accelerated particle-in-cell plasma simulations. (arXiv:2110.12444v1 [physics.plasm-ph])

Particle-In-Cell (PIC) methods are frequently used for kinetic, high-fidelity simulations of plasmas. Implicit formulations of PIC algorithms feature strong conservation properties, up to numerical round-off errors, and are not subject to time-step limitations which make them an attractive candidate to use in simulations fusion plasmas. Currently they remain prohibitively expensive for high-fidelity simulation of macroscopic plasmas. We investigate how amortized solvers can be incorporated with PIC methods for simulations of plasmas. Incorporated into the amortized solver, a neural network predicts a vector space that entails an approximate solution of the PIC system. The network uses only fluid moments and the electric field as input and its output is used to augment the vector space of an iterative linear solver. We find that this approach reduces the average number of required solver iterations by about 25% when simulating electron plasma oscillations. This novel approach may allow

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07:59 Arxiv.org Physics Growing Neoclassical Tearing Modes Seeded via Transient-Induced-Multimode Interactions. (arXiv:2110.12068v1 [physics.plasm-ph])

Nonlinear extended MHD simulations demonstrating seeding of neoclassical tearing modes (NTMs) via MHD-transient-induced multimode interactions are presented. Simulations of NTMs are enabled by two recent NIMROD code developments: the implementation of heuristic neoclassical stresses and the application of transient magnetic perturbations (MPs) at the boundary. NTMs are driven unstable by the inherently pressure driven kinetic bootstrap current, which arises due to collisional viscosity between passing and trapped electrons. These simulations use heuristic closures that model the neoclassical electron and ion stresses. NTM growth requires a seed island, which is generated by a transiently applied MP in simulations. The capability is demonstrated using kinetic-based reconstructions with flow of a DIII-D ITER Baseline Scenario discharge [R.J. La Haye, et al., Proceedings IAEA FEC 2020]. The applied MP seeds a 2/1 NTM that grows in two phases: a slow growth phase followed by a faster

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25.10.2021
19:17 Phys.org Neutron star collisions are 'goldmine' of heavy elements, study finds

Most elements lighter than iron are forged in the cores of stars. A star's white-hot center fuels the fusion of protons, squeezing them together to build progressively heavier elements. But beyond iron, scientists have puzzled over what could give rise to gold, platinum, and the rest of the universe's heavy elements, whose formation requires more energy than a star can muster.

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10:40 Arxiv.org Physics High-Order Curvilinear Finite Element Magneto-Hydrodynamics I: A Conservative Lagrangian Scheme. (arXiv:2110.11669v1 [physics.comp-ph])

Magneto-hydrodynamics is one of the foremost models in plasma physics with applications in inertial confinement fusion, astrophysics and elsewhere. Advanced numerical methods are needed to get an insight into the complex physical phenomena. The classical Lagrangian methods are typically limited to the low orders of convergence and suffer from violation of the divergence-free condition for magnetic field or conservation of the invariants. In this paper, a multi-dimensional conservative high-order resistive magneto-hydrodynamic method based on curvilinear finite elements is presented. The condition on zero divergence of magnetic field and conservation of mass, momentum, magnetic flux and the total energy are satisfied exactly. The curvilinear elements prevent entangling of the computational mesh and its imprinting into the solution. A high-order conservative time integration is applied, where an arbitrary order of convergence is attained for problems of ideal magneto-hydrodynamics.

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04:42 Arxiv.org CS Mechanistic Interpretation of Machine Learning Inference: A Fuzzy Feature Importance Fusion Approach. (arXiv:2110.11713v1 [cs.LG])

With the widespread use of machine learning to support decision-making, it is increasingly important to verify and understand the reasons why a particular output is produced. Although post-training feature importance approaches assist this interpretation, there is an overall lack of consensus regarding how feature importance should be quantified, making explanations of model predictions unreliable. In addition, many of these explanations depend on the specific machine learning approach employed and on the subset of data used when calculating feature importance. A possible solution to improve the reliability of explanations is to combine results from multiple feature importance quantifiers from different machine learning approaches coupled with re-sampling. Current state-of-the-art ensemble feature importance fusion uses crisp techniques to fuse results from different approaches. There is, however, significant loss of information as these approaches are not context-aware and reduce

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22.10.2021
04:54 Arxiv.org Math Low regularity ill-posedness and shock formation for 3D ideal compressible MHD. (arXiv:2110.10647v1 [math.AP])

The study of magnetohydrodynamics (MHD) significantly boosts the understanding and development of solar physics, planetary dynamics and controlled nuclear fusion. Dynamical properties of the MHD system involve nonlinear interactions of waves with multiple travelling speeds (the fast and slow magnetosonic waves, the Alfv\'{e}n wave and the entropy wave). One intriguing topic is the shock phenomena accompanied by the magnetic field, which have been affirmed by astronomical observations. However, permitting the residence of all above multi-speed waves, mathematically, whether one can prove shock formation for 3D MHD is still open. The multiple-speed nature of the MHD system makes it fascinating and challenging. In this paper, we give an affirmative answer to the above question. For 3D ideal compressible MHD, we construct examples of shock formation allowing the presence of all characteristic waves with multiple wave speeds. Building on our construction, we further prove that the Cauchy

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04:54 Arxiv.org Physics Shaping Magnetic Fields with Zero-Magnetic-Permeability Media. (arXiv:2110.11257v1 [physics.app-ph])

Some of the most important technological challenges of today's society, such as fusion reactors for future clean unlimited energy or the next generation of medical imaging techniques, require precise spatial shapes of strong magnetic fields. Achieving these high fields is currently hindered by limitations such as large forces damaging the wires in coils or the saturation of ferromagnets at high fields. Here we demonstrate a novel paradigm for creating magnetic landscapes. By enclosing magnetic sources within zero-magnetic-permeability (ZMP) media, a set of novel properties is unveiled. The magnetic field shape directly results from the contour of the outer surface of the ZMP enclosure, which allows the realization of basically any imaginable field landscape. Also, currents embedded in ZMP media can be fully magnetically isolated, which eliminates the forces in the wires, one of the main factors that currently impedes achieving very high magnetic fields. We confirm these properties,

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04:54 Arxiv.org Physics Low regularity ill-posedness and shock formation for 3D ideal compressible MHD. (arXiv:2110.10647v1 [math.AP])

The study of magnetohydrodynamics (MHD) significantly boosts the understanding and development of solar physics, planetary dynamics and controlled nuclear fusion. Dynamical properties of the MHD system involve nonlinear interactions of waves with multiple travelling speeds (the fast and slow magnetosonic waves, the Alfv\'{e}n wave and the entropy wave). One intriguing topic is the shock phenomena accompanied by the magnetic field, which have been affirmed by astronomical observations. However, permitting the residence of all above multi-speed waves, mathematically, whether one can prove shock formation for 3D MHD is still open. The multiple-speed nature of the MHD system makes it fascinating and challenging. In this paper, we give an affirmative answer to the above question. For 3D ideal compressible MHD, we construct examples of shock formation allowing the presence of all characteristic waves with multiple wave speeds. Building on our construction, we further prove that the Cauchy

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04:54 Arxiv.org Physics Modeling the complete prevention of disruption-generated runaway electron beam formation with a passive 3D coil in SPARC. (arXiv:2110.10598v1 [physics.plasm-ph])

The potential formation of multi-mega-ampere beams of relativistic "runaway" electrons (REs) during sudden terminations of tokamak plasmas poses a significant challenge to the tokamak's development as a fusion energy source. Here, we use state-of-the-art modeling of disruption magnetohydrodynamics coupled with a self-consistent evolution of RE generation and transport to show that a non-axisymmetric in-vessel coil will passively prevent RE beam formation during disruptions in the SPARC tokamak, a compact, high-field, high-current device capable of achieving a fusion gain Q > 2 in deuterium-tritium plasmas.

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20.10.2021
19:19 Phys.org New insights into heat pathways improve understanding of fusion plasma

A high-tech fusion facility is like a thermos—both keep their contents as hot as possible. Fusion facilities confine electrically charged gas known as plasma at temperatures 10 times hotter than the sun, and keeping it hot is crucial to stoking the fusion reactions that scientists seek to harness to create a clean, plentiful source of energy for producing electricity.

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19.10.2021
06:04 Arxiv.org Physics Characterization of plastic scintillator bars using fast neutrons from D-D and D-T reactions. (arXiv:2110.08299v1 [physics.ins-det])

We report results of fast neutron response in plastic scintillator (PS) bars from deuterium-deuterium (D-D) and deuterium-tritium (D-T) reactions using Purnima Neutron Generator Facility, BARC, Mumbai. These measurements are useful in context of Indian Scintillator Matrix for Reactor Anti-Neutrino (ISMRAN) detection, an array of 10x10 PS bars, used to measure reactor anti-neutrinos through inverse beta decay (IBD) signal. ISMRAN detector, an above-ground experiment close to the reactor core (~13m), deals with an active fast neutron background inside the reactor hall. A good understanding of fast neutron response in PS bars is an essential pre-requisite for suppression and discrimination of fast neutron background from IBD events. A monoenergetic neutron beam from the fusion reaction of D-D at 2.45 MeV and D-T at 14.1 MeV are used to characterize the energy response in these bars. The neutron energy response function has been simulated using the GEANT4 package and are compared with the

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05:22 Arxiv.org Statistics Prediction of liquid fuel properties using machine learning models with Gaussian processes and probabilistic conditional generative learning. (arXiv:2110.09360v1 [stat.ML])

Accurate determination of fuel properties of complex mixtures over a wide range of pressure and temperature conditions is essential to utilizing alternative fuels. The present work aims to construct cheap-to-compute machine learning (ML) models to act as closure equations for predicting the physical properties of alternative fuels. Those models can be trained using the database from MD simulations and/or experimental measurements in a data-fusion-fidelity approach. Here, Gaussian Process (GP) and probabilistic generative models are adopted. GP is a popular non-parametric Bayesian approach to build surrogate models mainly due to its capacity to handle the aleatory and epistemic uncertainties. Generative models have shown the ability of deep neural networks employed with the same intent. In this work, ML analysis is focused on a particular property, the fuel density, but it can also be extended to other physicochemical properties. This study explores the versatility of the ML models to

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18.10.2021
18:30 NYT Technology Nuclear Fusion Edges Toward the Mainstream

Long-shot money is flowing into start-ups that seek the energy of the stars. Driving the investments is a rising alarm about global warming.

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12:59 NewYork Times Nuclear Fusion Edges Toward the Mainstream

Long-shot money is flowing into start-ups that seek the energy of the stars. Driving the investments is a rising alarm about global warming.

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12:06 NYT Science Nuclear Fusion Edges Toward the Mainstream

Long-shot money is flowing into start-ups that seek the energy of the stars. Driving the investments is a rising alarm about global warming.

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08:49 Arxiv.org Physics MHD simulations of small ELMs at low triangularity in ASDEX Upgrade. (arXiv:2110.07908v1 [physics.plasm-ph])

The development of small- and no-ELM regimes for ITER is a high priority topic due to the risks associated to type-I ELMs. By considering non-linear extended MHD simulations of the ASDEX Upgrade tokamak with the JOREK code, we probe a regime that avoids type-I ELMs completely provided that the separatrix density is high enough. The dynamics of the pedestal in this regime are observed to be qualitatively similar to the so-called quasi-continuous exhaust (QCE) regime in several ways. Repetitive type-I ELMs are substituted by roughly constant levels of outwards transport caused by peeling-ballooning modes (with dominant ballooning characteristics) which are localised in the last 5\% of the confined region (in normalised poloidal flux). The simulated low triangularity plasma transitions to a type-I ELMy H-mode if the separatrix density is sufficiently reduced or if the input heating power is sufficiently increased. The stabilising factors that play a role in the suppression of the small

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15.10.2021
17:31 Phys.org Fast flows prevent buildup of impurities on the edge of tokamak plasmas

Impurities in the plasmas in fusion tokamaks can reduce performance. These impurities are created by interactions between the hot plasma and the metal tokamak walls. These walls are often armored with tungsten. This material resists heat, but degrades over time, releasing impurities into the plasma. Simulations predict how these impurities behave, but they are difficult to measure directly because many impurities only emit weak levels of radiation. The experiment detailed here used a collector probe to sample the plasma. It determined that detrimental impurities accumulate in the region just outside the plasma edge only when the tokamak magnetic fields rotate around the donut-shaped tokamak in a counter-clockwise direction. This is the opposite direction that the plasma current moves. Clockwise rotation causes fast flows that remove the impurities.

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17:31 Phys.org Working to make measurements of plasma disruption mitigation methods more accurate

A team of fusion researchers at the Department of Energy's Oak Ridge National Laboratory used datasets from measurements on the Joint European Torus, or JET, tokamak to model an improved method for quantifying the amount of plasma-radiated power during a disruption of normal operations.

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13:34 TheStar.com The Weekend Playlist: A sprawling epic from Toronto jazz trio BadBadNotGood, a shot of nostalgia from synth-pop revivalists Magdalena Bay and more

Keeping up with new music releases can be a difficult task. Your Weekend Playlist offers a brief introduction to a broad range of the most interesting new tracks and emerging artists. This week’s playlist features new music from BadBadNotGood, Magdalena Bay, Bizarrap and a collaboration between Hamilton Leithauser and Kevin Morby. Plus, new music from Cate Le Bon and Roc Marciano. Click here for the Spotify link. BadBadNotGood: Signal From The Noise In a recent podcast, music critic Kelefa Sanneh describes how, in the late 60s and early 70s, two groups —The Velvet Underground and Yes — offered competing visions for the future of rock and roll. Of course, The Velvet Underground’s vision proved triumphant — their laid-back and loose sound became the template and a key influence for punk music, alt-rock and indie. As for the prog-rock/jazz fusion wizards in Yes, despite their technical prowess and grand ambitions, the music today sounds

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09:45 Arxiv.org Physics Global Stochastic Optimization of Stellarator Coil Configurations. (arXiv:2110.07464v1 [physics.plasm-ph])

In the construction of a stellarator, the manufacturing and assembling of the coil system is a dominant cost. These coils need to satisfy strict engineering tolerances, and if those are not met the project could be canceled as in the case of the National Compact Stellarator Experiment (NCSX) project [25]. Therefore, our goal is to find coil configurations that increase construction tolerances without compromising the performance of the magnetic field. In this paper, we develop a gradient-based stochastic optimization model which seeks robust stellarator coil configurations in high dimensions. In particular, we design a two-step method: first, we perform an approximate global search by a sample efficient trust-region Bayesian optimization; second, we refine the minima found in step one with a stochastic local optimizer. To this end, we introduce two stochastic local optimizers: BFGS applied to the Sample Average Approximation and Adam, equipped with a control variate for variance

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14.10.2021
23:27 WhatReallyHappened.com The world's first working nuclear fusion reactor could be coming soon near your town: Five UK sites including Ardeer, Moorside and Severn Edge have been shortlisted for a plant – with operations as early as 2040

The UK's first prototype fusion power plant is a step closer to reality today, after five sites were shortlisted as the potential home for the pioneering technology. Ardeer in North Ayrshire, Goole in Yorkshire, Moorside in Cumbria, Ratcliffe-on-Soar in Nottinghamshire and Severn Edge in Gloucestershire are all vying to be the location for what could be the world's first working nuclear fusion reactor. The UK's first prototype fusion power plant is a step closer to reality today, after five sites were shortlisted as the potential home for the pioneering technology. Ardeer in North Ayrshire, Goole in Yorkshire, Moorside in Cumbria, Ratcliffe-on-Soar in Nottinghamshire and Severn Edge in Gloucestershire are all vying to be the location for what could be the world's first working nuclear fusion reactor.

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21:24 WhatReallyHappened.com The world's first working nuclear fusion reactor could be coming soon near your town: Five UK sites including Ardeer, Moorside and Severn Edge have been shortlisted for a plant – with operations as early as 2040

The UK's first prototype fusion power plant is a step closer to reality today, after five sites were shortlisted as the potential home for the pioneering technology.

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12.10.2021
14:23 Nature.Com Publisher Correction: Demonstration of reduced neoclassical energy transport in Wendelstein 7-X

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10:43 Arxiv.org Physics First Proof-of-Concept Prototype of an Additive-Manufactured Radio Frequency Quadrupole. (arXiv:2110.05233v1 [physics.acc-ph])

Continuous developments in Additive Manufacturing (AM) technologies are opening opportunities in novel machining, and improving design alternatives for modern particle accelerator components. One of the most critical, complex, and delicate accelerator elements to manufacture and assemble is the Radio Frequency Quadrupole (RFQ) linear accelerator, used as an injector for all large modern proton and ion accelerator systems. For this reason, the RFQ has been selected by a wide European collaboration participating in the AM developments of the I.FAST (Innovation Fostering in Accelerator Science and Technology) Horizon 2020 project. RFQ is as an excellent candidate to show how sophisticated pure-copper accelerator components can be manufactured by AM and how their functionalities can be boosted by this evolving technology. To show the feasibility of the AM process, a prototype RFQ section has been designed, corresponding to one-quarter of a 750 MHz 4-vane RFQ, which was optimised for

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11.10.2021
06:32 Arxiv.org CS Construction Cost Index Forecasting: A Multi-feature Fusion Approach. (arXiv:2108.10155v2 [cs.LG] UPDATED)

The construction cost index is an important indicator of the construction industry. Predicting CCI has important practical significance. This paper combines information fusion with machine learning, and proposes a multi-feature fusion (MFF) module for time series forecasting. Compared with the convolution module, the MFF module is a module that extracts certain features. Experiments have proved that the combination of MFF module and multi-layer perceptron has a relatively good prediction effect. The MFF neural network model has high prediction accuracy and efficient prediction efficiency. At the same time, MFF continues to improve the potential of prediction accuracy, which is a study of continuous attention.

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06:32 Arxiv.org CS MilliTRACE-IR: Contact Tracing and Temperature Screening via mm-Wave and Infrared Sensing. (arXiv:2110.03979v1 [eess.SP])

In this work, we present milliTRACE-IR, a joint mm-wave radar and infrared imaging sensing system performing unobtrusive and privacy preserving human body temperature screening and contact tracing in indoor spaces. Social distancing and fever detection have been widely employed to counteract the COVID-19 pandemic, sparking great interest from academia, industry and public administrations worldwide. While most solutions have dealt with the two aspects separately, milliTRACE-IR combines, via a robust sensor fusion approach, mm-wave radars and infrared thermal cameras. The system achieves fully automated measurement of distancing and body temperature, by jointly tracking the faces of the subjects in the thermal camera image plane and the human motion in the radar reference system. It achieves decimeter-level accuracy in distance estimation, inter-personal distance estimation (effective for subjects getting as close as 0.2 m), and accurate temperature monitoring (max. errors of 0.5 C).

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05:59 Arxiv.org Physics Multi-fidelity information fusion with concatenated neural networks. (arXiv:2110.04170v1 [physics.flu-dyn])

Recently, computational modeling has shifted towards the use of deep learning, and other data-driven modeling frameworks. Although this shift in modeling holds promise in many applications like design optimization and real-time control by lowering the computational burden, training deep learning models needs a huge amount of data. This big data is not always available for scientific problems and leads to poorly generalizable data-driven models. This gap can be furnished by leveraging information from physics-based models. Exploiting prior knowledge about the problem at hand, this study puts forth a concatenated neural network approach to build more tailored, effective, and efficient machine learning models. For our analysis, without losing its generalizability and modularity, we focus on the development of predictive models for laminar and turbulent boundary layer flows. In particular, we combine the self-similarity solution and power-law velocity profile (low-fidelity models) with the

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05:59 Arxiv.org Physics A conservative implicit-PIC scheme for the hybrid kinetic-ion fluid-electron plasma model on curvilinear meshes. (arXiv:2110.03886v1 [physics.plasm-ph])

The hybrid kinetic-ion fluid-electron plasma model is widely used to study challenging multi-scale problems in space and laboratory plasma physics. Here, a novel conservative scheme for this model employing implicit particle-in-cell techniques is extended to arbitrary coordinate systems via curvilinear maps from logical to physical space. The scheme features a fully non-linear electromagnetic formulation with a multi-rate time advance - including sub-cycling and orbit-averaging for the kinetic ions. By careful choice of compatible particle-based kinetic-ion and mesh-based fluid-electron discretizations in curvilinear coordinates, as well as particle-mesh interpolations and implicit midpoint time advance, the scheme is proven to conserve total energy for arbitrary curvilinear meshes. In the electrostatic limit, the method is also proven to conserve total momentum for arbitrary curvilinear meshes. Although momentum is not conserved for arbitrary curvilinear meshes in the electromagnetic

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08.10.2021
16:45 Phys.org Researchers propose novel permanent magnet design methods for quasi-axisymmetric stellarator

A new permanent magnet design of quasi-axisymmetric stellarator was made by researchers led by Prof. Xu Guosheng from the Hefei Institutes of Physical Science (HFIPS) of the Chinese Academy of Sciences.

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05.10.2021
08:33 Arxiv.org CS The Second DiCOVA Challenge: Dataset and performance analysis for COVID-19 diagnosis using acoustics. (arXiv:2110.01177v1 [eess.AS])

The Second DiCOVA Challenge aims at accelerating the research in diagnosing COVID-19 using acoustics (DiCOVA), a topic at the intersection of acoustics signal processing, machine learning, and healthcare. This challenge is an open call to researchers to analyze a dataset of audio recordings, collected from individuals with and without COVID-19, for a two-class classification. The development set audio recordings correspond to breathing, cough, and speech sound samples collected from 965 (172 COVID) individuals. The challenge features four tracks, one associated with each sound category and a fourth fusion track allowing experimentation with combination of the individual sound categories. In this paper, we introduce the challenge and provide a detailed description of the task and a baseline system.

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08:10 Arxiv.org Quantitative Biology The Second DiCOVA Challenge: Dataset and performance analysis for COVID-19 diagnosis using acoustics. (arXiv:2110.01177v1 [eess.AS])

The Second DiCOVA Challenge aims at accelerating the research in diagnosing COVID-19 using acoustics (DiCOVA), a topic at the intersection of acoustics signal processing, machine learning, and healthcare. This challenge is an open call to researchers to analyze a dataset of audio recordings, collected from individuals with and without COVID-19, for a two-class classification. The development set audio recordings correspond to breathing, cough, and speech sound samples collected from 965 (172 COVID) individuals. The challenge features four tracks, one associated with each sound category and a fourth fusion track allowing experimentation with combination of the individual sound categories. In this paper, we introduce the challenge and provide a detailed description of the task and a baseline system.

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04.10.2021
03:54 Arxiv.org Physics Discharge modeling in EAST using bidirectional LSTM. (arXiv:2110.00346v1 [physics.plasm-ph])

An improved discharge model based on a bidirectional neural network was developed. The bidirectional LSTM model was used, and it was trained by the experimental data from the Experimental Advanced Superconducting Tokamak (EAST) campaign 2010-2020 discharges. Compared to our previous works (Chenguang Wan et al 2021 Nucl. Fusion \textbf{61} 066015), the present work reproduces the discharge evolution process through more key diagnostic signals, including the electron density $n_{e}$, store energy $W_{mhd}$, loop voltage $V_{loop}$, actual plasma current $I_{p}$, normalized beta $\beta_{n}$, toroidal beta $\beta_{t}$, beta poloidal $\beta_{p}$, elongation at plasma boundary $\kappa$, internal inductance $l_{i}$, q at magnetic axis $q_{0}$, and q at 95% flux surface $q_{95}$. The similarity of electron density $n_{e}$ and loop voltage $V_{loop}$ is improved by 1%, and 5%. The average similarity of all the selected key diagnostic signals between modeling results and the experimental data

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03:54 Arxiv.org Physics On the role of density fluctuations in the core turbulent transport of Wendelstein 7-X. (arXiv:2110.00277v1 [physics.plasm-ph])

A recent characterization of core turbulence carried out with a Doppler reflectometer in the optimized stellarator Wendelstein 7-X (W7-X) found that discharges achieving high ion temperatures at the core featured an ITG-like suppression of density fluctuations driven by a reduction of the gradient ratio $\eta_i = L_n/L_{T_i}$ [D. Carralero et al., Nucl. Fusion, 2021]. In order to confirm the role of ITG turbulence in this process, we set out to establish experimentally the relation between core density fluctuations, turbulent heat flux and global confinement. With this aim, we consider the scenarios found in the previous work and carry out power balance analysis for a number of representative ones, including some featuring high ion temperature. As well, we evaluate the global energy confinement time and discuss it in the context of the ISS04 inter-stellarator scaling. We find that, when turbulence is suppressed as a result of a reduction of $\eta_i$, there is a reduction of ion

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01.10.2021
17:11 CNBC top news The race is on to replicate the power of the sun with fusion energy

With a number of recent breakthroughs, the race is on to prove that nuclear fusion is not only possible, but integral to a clean energy future

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04:38 Arxiv.org Physics Physics design point of high-field stellarator reactors. (arXiv:2109.15189v1 [physics.plasm-ph])

The ongoing development of electromagnets based on High Temperature Superconductors has led to the conceptual exploration of high-magnetic-field fusion reactors of the tokamak type, operating at on-axis fields above 10 T. In this work we explore the consequences of the potential future availability of high-field three-dimensional electromagnets on the physics design point of a stellarator reactor. We find that, when an increase in the magnetic field strength $B$ is used to maximally reduce the device linear size $R\sim B^{-4/3}$ (with otherwise fixed magnetic geometry), the physics design point is largely independent of the chosen field strength/device size. A similar degree of optimization is to be imposed on the magnetohydrodynamic, transport and fast ion confinement properties of the magnetic configuration of that family of reactor design points. Additionally, we show that the family shares an invariant operation map of fusion power output as a function of the auxiliary power and

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04:38 Arxiv.org Physics Effects of collisional ion orbit loss on neoclassical tokamak radial electric fields. (arXiv:2109.14758v1 [physics.plasm-ph])

Ion orbit loss is considered important for the radial electric field $E_r$ in tokamak edge plasmas. In neoclassical equilibria, collisions can scatter ions onto loss orbits and generate a steady-state radial current. The latter could potentially drive the edge $E_r$ away from its neoclassical value. To quantitatively measure this effect, an ion-orbit-flux diagnostic has been implemented in the axisymmetric version of the gyrokinetic particle-in-cell code XGC. The validity of the diagnostic is demonstrated by studying the collisional relaxation of $E_r$ in the core plasma. After this verification, the ion orbit-loss effect is numerically measured in the edge for an H-mode plasma in DIII-D geometry. In quasisteady state, the edge $E_r$ is found to be mainly determined by the radial ion force balance condition, in which the radial electric force on ions balances the large ion pressure gradient associated with the given density pedestal. In this quasisteady state, the collisional

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29.09.2021
10:32 Arxiv.org CS Turning old models fashion again: Recycling classical CNN networks using the Lattice Transformation. (arXiv:2109.13885v1 [cs.CV])

In the early 1990s, the first signs of life of the CNN era were given: LeCun et al. proposed a CNN model trained by the backpropagation algorithm to classify low-resolution images of handwritten digits. Undoubtedly, it was a breakthrough in the field of computer vision. But with the rise of other classification methods, it fell out fashion. That was until 2012, when Krizhevsky et al. revived the interest in CNNs by exhibiting considerably higher image classification accuracy on the ImageNet challenge. Since then, the complexity of the architectures are exponentially increasing and many structures are rapidly becoming obsolete. Using multistream networks as a base and the feature infusion precept, we explore the proposed LCNN cross-fusion strategy to use the backbones of former state-of-the-art networks on image classification in order to discover if the technique is able to put these designs back in the game. In this paper, we showed that we can obtain an increase of accuracy up to

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10:32 Arxiv.org CS An Efficient Epileptic Seizure Detection Technique using Discrete Wavelet Transform and Machine Learning Classifiers. (arXiv:2109.13811v1 [eess.SP])

This paper presents an epilepsy detection method based on discrete wavelet transform (DWT) and Machine learning classifiers. Here DWT has been used for feature extraction as it provides a better decomposition of the signals in different frequency bands. At first, DWT has been applied to the EEG signal to extract the detail and approximate coefficients or different sub-bands. After the extraction of the coefficients, principal component analysis (PCA) has been applied on different sub-bands and then a feature level fusion technique is used to extract the important features in low dimensional feature space. Three classifiers namely: Support Vector Machine (SVM) classifier, K-Nearest-Neighbor (KNN) classifier, and Naive Bayes (NB) Classifiers have been used in the proposed work for classifying the EEG signals. The proposed method is tested on Bonn databases and provides a maximum of 100% recognition accuracy for KNN, SVM, NB classifiers.

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28.09.2021
17:07 WhatReallyHappened.com Cold nuclear fusion in lithium compound alloy

The experiments were performed in vacuum chamber in order precise measurements to be achieved and due to the relatively low concentrations of the interacting gases the amounts of the generated helium and of the generated energy (heat) were relatively low. In fact D2 gas in environment of H/H2 gas in the chamber was directed to a specimen of lithium compound alloy placed on sample holder and significant generation of both 3He and 4He was observed in all experiments as it was supported by the following facts: i) Mass analysis shows relatively high amount of 3He; ii) Mass analysis shows relatively high amount of 4He/D2 and relatively significant amount of 4HeH that confirms relatively high amount of 4He; iii) Mass analysis shows absence of H3+ (stable positive ion of three hydrogen molecule), DH (deuterium hydride) and D2H+ (stable positive ion of deuterium-deuterium hydride molecule); and iv) DC plasma spectroscopy shows peaks typical for both 3He and 4He. Based on the

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11:00 Technology.org Funding boost will help deliver low-carbon fusion energy

Bristol researchers will lead one of six new projects looking at novel ways to reduce the UK’s greenhouse

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05:46 Arxiv.org Physics Learning Transport Processes with Machine Intelligence. (arXiv:2109.13096v1 [physics.plasm-ph])

We present a machine learning based approach to address the study of transport processes, ubiquitous in continuous mechanics, with particular attention to those phenomena ruled by complex micro-physics, impractical to theoretical investigation, yet exhibiting emergent behavior describable by a closed mathematical expression. Our machine learning model, built using simple components and following a few well established practices, is capable of learning latent representations of the transport process substantially closer to the ground truth than expected from the nominal error characterising the data, leading to sound generalisation properties. This is demonstrated through an idealized study of the long standing problem of heat flux suppression under conditions relevant for fusion and cosmic plasmas. A simple analysis shows that the result applies beyond those case specific assumptions and that, in particular, the accuracy of the learned representation is controllable through knowledge

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05:46 Arxiv.org Physics Neural network tokamak equilibria with incompressible flows. (arXiv:2109.12850v1 [physics.plasm-ph])

We present several numerical results concerning the solution of a Generalized Grad-Shafranov Equation (GGSE), which governs axisymmetric plasma equilibria with incompressible flows of arbitrary direction, using fully connected, feed-forward deep neural networks, also known as multi-layer perceptrons. Solutions to the GGSE in a Tokamak-relevant D-Shaped domain are approximated by such artificial neural networks (ANNs) upon minimizing the GGSE mean squared residual in the plasma volume and the poloidal flux function on the plasma boundary. Solutions for the Solovev and the general linearizing ansatz for the free functions involved in the GGSE are obtained and benchmarked against known analytic solutions. We also construct a non-linear equilibrium incorporating characteristics relevant to the H-mode confinement. In our numerical experiments it was observed that changing the radial distribution of the training points had no appreciable effect on the accuracy of the trained solution. In

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27.09.2021
08:27 Arxiv.org Physics Multiscale study of high energy attosecond pulse interaction with matter and application to proton-Boron fusion. (arXiv:2109.12017v1 [physics.plasm-ph])

For several decades, the interest of the scientific community in aneutronic fusion reactions such as proton-Boron fusion has grown because of potential applications in different fields. Recently, many scientific teams in the world have worked experimentally on the possibility to trigger proton-Boron fusion using intense lasers demonstrating an important renewal of interest of this field. It is now possible to generate ultra-short high intensity laser pulses at high repetition rate. These pulses also have unique properties that can be leveraged to produce proton-Boron fusion reactions. In this article, we investigate the interaction of a high energy attosecond pulse with a solid proton-Boron target and the associated ion acceleration supported by numerical simulations. We demonstrate the efficiency of single-cycle attosecond pulses in comparison to multi-cycle attosecond pulses in ion acceleration and magnetic field generation. Using these results we also propose a path to proton-Boron

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24.09.2021
09:41 Arxiv.org Physics Hierarchical approach for energetic particle transport in 1-dimensional uniform plasmas. (arXiv:2109.11254v1 [physics.plasm-ph])

The importance of the beam-plasma system in fusion physics relies on its capability in reproducing relevant features of energetic particles interacting with the Alfv\'enic spectrum. We analyze here a multi-level hierarchy of the Vlasov-Poisson induced transport in order to characterize the underlying physical processes.

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09:41 Arxiv.org Physics Beam model of Doppler backscattering. (arXiv:2109.10973v1 [physics.plasm-ph])

We use beam tracing -- implemented with a newly-written code, Scotty -- and the reciprocity theorem to derive a model for the linear backscattered power of the Doppler Backscattering (DBS) diagnostic. Our model works for both the O-mode and X-mode in tokamak geometry (and certain regimes of stellarators). We present the analytical derivation of our model and its implications on the DBS signal localisation and the wavenumber resolution. To determine these two quantities, we find that it is the curvature of the field lines that is important, rather than the curvature of the cut-off surface. We proceed to shed light on the hitherto poorly-understood quantitative effect of the mismatch angle. Consequently, one can use this model to correct for the attenuation due to mismatch, avoiding the need for empirical optimisation. This is especially important in spherical tokamaks, since the magnetic pitch angle is large and varies both spatially and temporally.

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23.09.2021
18:53 Phys.org Researchers simulate compact fusion power plant concept

Fusion power plants use magnetic fields to hold a ball of current-carrying gas (called a plasma). This creates a miniature sun that generates energy through nuclear fusion. The Compact Advanced Tokamak (CAT) concept uses state-of-the-art physics models to potentially improve fusion energy production. The models show that by carefully shaping the plasma and the distribution of current in the plasma, fusion plant operators can suppress turbulent eddies in the plasma. These eddies can cause heat loss. This will enable operators to achieve higher pressures and fusion power with lower current. This advance could help achieve a state where the plasma sustains itself and drives most of its own current.

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05:42 Arxiv.org CS Hierarchical Multimodal Transformer to Summarize Videos. (arXiv:2109.10559v1 [cs.CV])

Although video summarization has achieved tremendous success benefiting from Recurrent Neural Networks (RNN), RNN-based methods neglect the global dependencies and multi-hop relationships among video frames, which limits the performance. Transformer is an effective model to deal with this problem, and surpasses RNN-based methods in several sequence modeling tasks, such as machine translation, video captioning, \emph{etc}. Motivated by the great success of transformer and the natural structure of video (frame-shot-video), a hierarchical transformer is developed for video summarization, which can capture the dependencies among frame and shots, and summarize the video by exploiting the scene information formed by shots. Furthermore, we argue that both the audio and visual information are essential for the video summarization task. To integrate the two kinds of information, they are encoded in a two-stream scheme, and a multimodal fusion mechanism is developed based on the hierarchical

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05:42 Arxiv.org CS AI in Osteoporosis. (arXiv:2109.10478v1 [cs.CV])

In this chapter we explore and evaluate methods for trabecular bone characterization and osteoporosis diagnosis with increased interest in sparse approximations. We first describe texture representation and classification techniques, patch-based methods such as Bag of Keypoints, and more recent deep neural networks. Then we introduce the concept of sparse representations for pattern recognition and we detail integrative sparse analysis methods and classifier decision fusion methods. We report cross-validation results on osteoporosis datasets of bone radiographs and compare the results produced by the different categories of methods. We conclude that advances in the AI and machine learning fields have enabled the development of methods that can be used as diagnostic tools in clinical settings.

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22.09.2021
08:32 Arxiv.org CS MESSFN : a Multi-level and Enhanced Spectral-Spatial Fusion Network for Pan-sharpening. (arXiv:2109.09937v1 [cs.CV])

Dominant pan-sharpening frameworks simply concatenate the MS stream and the PAN stream once at a specific level. This way of fusion neglects the multi-level spectral-spatial correlation between the two streams, which is vital to improving the fusion performance. In consideration of this, we propose a Multi-level and Enhanced Spectral-Spatial Fusion Network (MESSFN) with the following innovations: First, to fully exploit and strengthen the above correlation, a Hierarchical Multi-level Fusion Architecture (HMFA) is carefully designed. A novel Spectral-Spatial (SS) stream is established to hierarchically derive and fuse the multi-level prior spectral and spatial expertise from the MS stream and the PAN stream. This helps the SS stream master a joint spectral-spatial representation in the hierarchical network for better modeling the fusion relationship. Second, to provide superior expertise, consequently, based on the intrinsic characteristics of the MS image and the PAN image, two feature

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07:59 Arxiv.org Physics Verification and validation of gyrokinetic and kinetic-MHD simulations for internal kink instability in DIII-D tokamak. (arXiv:2109.09891v1 [physics.plasm-ph])

Verification and validation of the internal kink instability in tokamak have been performed for both gyrokinetic (GTC) and kinetic-MHD codes (GAM-solver, M3D-C1-K, NOVA, XTOR-K). Using realistic magnetic geometry and plasma profiles from the same equilibrium reconstruction of the DIII-D shot #141216, these codes exhibit excellent agreement for the growth rate and mode structure of the internal kink mode when all kinetic effects are suppresed. The simulated radial mode structures agree quantitatively with the electron cyclotron emission measurement after adjusting, within the experimental uncertainty, the safety factor q=1 flux-surface location in the equilibrium reconstruction. Compressible magnetic perturbations strongly destabilize the kink, while poloidal variations of the equilibrium current density reduce the growth rate of the kink. Furthermore, kinetic effects of thermal ions are found to decrease the kink growth rate in kinetic-MHD simulations, but increase the kink growth rate

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21.09.2021
11:05 Arxiv.org CS Scenario adaptive disruption prediction study for next generation burning-plasma tokamaks. (arXiv:2109.08956v1 [physics.plasm-ph])

Next generation high performance (HP) tokamaks risk damage from unmitigated disruptions at high current and power. Achieving reliable disruption prediction for a device's HP operation based on its low performance (LP) data is key to success. In this letter, through explorative data analysis and dedicated numerical experiments on multiple existing tokamaks, we demonstrate how the operational regimes of tokamaks can affect the power of a trained disruption predictor. First, our results suggest data-driven disruption predictors trained on abundant LP discharges work poorly on the HP regime of the same tokamak, which is a consequence of the distinct distributions of the tightly correlated signals related to disruptions in these two regimes. Second, we find that matching operational parameters among tokamaks strongly improves cross-machine accuracy which implies our model learns from the underlying scalings of dimensionless physics parameters like q_{95}, \beta_{p} and confirms the

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10:31 Arxiv.org Physics Impact of Surface and Pore Characteristics on Fatigue Life of Laser Powder Bed Fusion Ti-6Al-4V Alloy Described by Neural Network Models. (arXiv:2109.09655v1 [cond-mat.mtrl-sci])

In this study, the effects of surface roughness and pore characteristics on fatigue lives of laser powder bed fusion (LPBF) Ti-6Al-4V parts were investigated. The 197 fatigue bars were printed using the same laser power but with varied scanning speeds. These actions led to variations in the geometries of microscale pores, and such variations were characterized using micro-computed tomography. To generate differences in surface roughness in fatigue bars, half of the samples were grit-blasted and the other half machined. Fatigue behaviors were analyzed with respect to surface roughness and statistics of the pores. For the grit-blasted samples, the contour laser scan in the LPBF strategy led to a pore-depletion zone isolating surface and internal pores with different features. For the machined samples, where surface pores resemble internal pores, the fatigue life was highly correlated with the average pore size and projected pore area in the plane perpendicular to the stress direction.

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10:31 Arxiv.org Physics Plasma screening of nuclear fusion reactions in liquid layers of compact degenerate stars: a first-principle study. (arXiv:2109.09445v1 [astro-ph.HE])

A reliable description of nuclear fusion reactions in inner layers of white dwarfs and envelopes of neutron stars is important for realistic modelling of a wide range of observable astrophysical phenomena from accreting neutron stars to type Ia supernovae. We study the problem of screening of the Coulomb barrier impeding the reactions, by a plasma surrounding the fusing nuclei. Numerical calculations of the screening factor are performed from the first principles with the aid of quantum-mechanical path integrals in the model of a one-component plasma of atomic nuclei for temperatures and densities typical for dense liquid layers of compact degenerate stars. We do not rely on various quasiclassic approximations widely used in the literature, such as factoring-out the tunneling process, tunneling in an average spherically symmetric mean-force potential, usage of classic free energies and pair correlation functions, linear mixing rule and so on. In general, a good agreement with earlier

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10:31 Arxiv.org Physics Scenario adaptive disruption prediction study for next generation burning-plasma tokamaks. (arXiv:2109.08956v1 [physics.plasm-ph])

Next generation high performance (HP) tokamaks risk damage from unmitigated disruptions at high current and power. Achieving reliable disruption prediction for a device's HP operation based on its low performance (LP) data is key to success. In this letter, through explorative data analysis and dedicated numerical experiments on multiple existing tokamaks, we demonstrate how the operational regimes of tokamaks can affect the power of a trained disruption predictor. First, our results suggest data-driven disruption predictors trained on abundant LP discharges work poorly on the HP regime of the same tokamak, which is a consequence of the distinct distributions of the tightly correlated signals related to disruptions in these two regimes. Second, we find that matching operational parameters among tokamaks strongly improves cross-machine accuracy which implies our model learns from the underlying scalings of dimensionless physics parameters like q_{95}, \beta_{p} and confirms the

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10:31 Arxiv.org Physics Fusion Driven Transmutation of Transuranics in a Molten Salt. (arXiv:2109.08741v1 [nucl-th])

A first set of computational studies of transmutation of spent nuclear fuel using compact tunable 14 MeV D-T fusion driven neutron sources is presenter. Where we study the controllability, time evolution, as well as effects of spatial distribution of the neutronics in the transmutation in the subcritical operations regime of a transmutator, in which our neutron sources are small, distributed, and can be monitored. Source neutrons are generated via beam-target fusion whereas a deuteron beam is created by laser irradiation of nanometric foils, through the Coherent Acceleration of Ions by Laser (CAIL) process, onto a tritium soaked target. This can be accomplished using relatively cheap fiber lasers terminating onto small scale targets which makes possible the use of multiple tunable and distributable neutron sources. This source is then combined with a molten salt core whose liquid state allows: homogeneity by mixing, safety, in-situ processing, and monitoring. Such a source and molten

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20.09.2021
17:21 SingularityHub.Com The Race for Fusion Power Heats Up as Multiple Projects Hit New Milestones

Fusion power could be a silver bullet for the world’s energy and environmental woes, but it’s famously always 30 years away. A recent flurry of announcements are raising hopes that maybe the timeline has started to tighten. The technology has huge potential because it promises to generate enormous amounts of energy from abundant fuel that […]

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