Search

MESSENGER has observed a lot of dawn‐dusk asymmetries in Mercury's magnetotail, such as the asymmetries of the cross‐tail current sheet thickness and the occurrence of flux ropes, dipolarization events, and energetic electron injections. In order to obtain a global pictures of Mercury's magnetotail dynamics and the relationship between these asymmetries, we perform global simulations with the magnetohydrodynamics with embedded particle‐in‐cell (MHD‐EPIC) model, where Mercury's magnetotail region is covered by a PIC code. Our simulations show that the dawnside current sheet is thicker, the plasma density is larger, and the electron pressure is higher than the duskside. Under a strong interplanetary magnetic field driver, the simulated reconnection sites prefer the dawnside. We also found the dipolarization events and the planetward electron jets are moving dawnward while they are moving toward the planet, so that almost all dipolarization events and high‐speed plasma flows concentrate in the dawn sector. The simulation results are consistent with MESSENGER observations. Dawnside current sheet is thicker than the dusksideMagnetic reconnection prefers dawnside under strong IMF drivingAlmost all dipolarization events, high‐speed proton and electron planetward flows concentrate on the dawnside

The largest moon in the solar system, Ganymede, is also the only moon known to possess a strong intrinsic magnetic field and a corresponding magnetosphere. Using the new version of Hall magnetohydrodynamic with embedded particle‐in‐cell model with a self‐consistently coupled resistive body representing the electrical properties of the moon's interior, improved inner boundary conditions, and the flexibility of coupling different grid geometries, we achieve better match of magnetic field with measurements for all six Galileo flybys. The G2 flyby comparisons of plasma bulk flow velocities with the Galileo Plasma Subsystem data support the oxygen ion assumption inside Ganymede's magnetosphere. Crescent shape, nongyrotropic, and nonisotropic ion distributions are identified from the coupled model. Furthermore, we have derived the energy fluxes associated with the upstream magnetopause reconnection of ∼10−7W/cm2based on our model results and found a maximum of 40% contribution to the total peak auroral emissions. Hall MHD‐EPIC model of Ganymede's magnetosphere uses realistic inner boundary conditions and energy‐conserving PIC schemeIon‐scale kinetics at upstream magnetopause are fully resolved, shown by the nongyrotropic/anisotropic distributionsElectron precipitation of ∼10−7W/cm2shows up to half of the peak emission brightness contributed by upstream reconnection

Mars Atmosphere and Volatile EvolutioN (MAVEN) mission observations show clear evidence of the occurrence of the magnetic reconnection process in the Martian plasma tail. In this study, we use sophisticated numerical models to help us understand the effects of magnetic reconnection in the plasma tail. The numerical models used in this study are (a) a multispecies global Hall‐magnetohydrodynamic (HMHD) model and (b) a global HMHD model two‐way coupled to an embedded fully kinetic particle‐in‐cell code. Comparison with MAVEN observations clearly shows that the general interaction pattern is well reproduced by the global HMHD model. The coupled model takes advantage of both the efficiency of the MHD model and the ability to incorporate kinetic processes of the particle‐in‐cell model, making it feasible to conduct kinetic simulations for Mars under realistic solar wind conditions for the first time. Results from the coupled model show that the Martian magnetotail is highly dynamic due to magnetic reconnection, and the resulting Mars‐ward plasma flow velocities are significantly higher for the lighter ion fluid, which are quantitatively consistent with MAVEN observations. The HMHD with Embedded Particle‐in‐Cell model predicts that the ion loss rates are more variable but with similar mean values as compared with HMHD model results. Model results show that the Martian magnetotail is highly dynamic due to magnetic reconnectionThe numerical simulations predict that the Mars‐ward plasma flow, due to magnetic reconnection, is faster for lighter ions, consistent with MAVEN observationsThe HMHD EPIC model simulations predict that the ion loss rates are more variable but with similar mean values as compared with HMHD model

A detailed understanding of the solar wind interaction with lunar magnetic anomalies (LMAs) is essential to identify its implications for lunar exploration and to enhance our physical understanding of the particle dynamics in a magnetized plasma. We present the first three‐dimensional full‐kinetic electromagnetic simulation case study of the solar wind interaction with a vertical dipole, resembling a medium‐size LMA. In contrast to a horizontal dipole, we show that a vertical dipole twists its field lines and cannot form a minimagnetosphere. Instead, it creates a ring‐shaped weathering pattern and reflects up to 21% (four times more as compared to the horizontal case) of the incoming solar wind ions electrostatically through the normal electric field formed above the electron shielding region surrounding the cusp. This work delivers a vital piece to fully comprehend and interpret lunar observations, as we find the amount of reflected ions to be a tracer for the underlying field structure. In contrast to a horizontal dipolar LMA, a vertical dipole cannot form a minimagnetosphereA ring‐shaped weathering pattern is created and reflects up to 21% of the incoming solar wind ionsThe amount of reflected ions is a tracer for the underlying magnetic field structure

We present a general model of the solar wind interaction with a dipolar lunar crustal magnetic anomaly (LMA) using three‐dimensional full‐kinetic and electromagnetic simulations. We confirm that LMAs may indeed be strong enough to stand off the solar wind from directly impacting the lunar surface, forming a so‐called “minimagnetosphere,” as suggested by spacecraft observations and theory. We show that the LMA configuration is driven by electron motion because its scale size is small with respect to the gyroradius of the solar wind ions. We identify a population of back‐streaming ions, the deflection of magnetized electrons via the E× Bdrift motion, and the subsequent formation of a halo region of elevated density around the dipole source. Finally, it is shown that the presence and efficiency of the processes are heavily impacted by the upstream plasma conditions and, on their turn, influence the overall structure and evolution of the LMA system. Understanding the detailed physics of the solar wind interaction with LMAs, including magnetic shielding, particle dynamics and surface charging is vital to evaluate its implications for lunar exploration. LMA strong enough to stand off the solar windThe LMA configuration is driven by electron motionKinetic processes and plasma conditions influence structure of LMA system

Abstract: The implicit Particle-in-Cell method for the computer simulation of plasma, and its implementation in a three-dimensional parallel code, called iPIC3D, are presented. The implicit integration in time of the Vlasov–Maxwell system, removes the numerical stability constraints and it enables kinetic plasma simulations at magnetohydrodynamics time scales. Simulations of magnetic reconnection in plasma are presented to show the effectiveness of the algorithm. [Copyright &y& Elsevier]

We simulate the acceleration of electrons to relativistic energies due to the interaction of electrons with waves generated by longitudinal (i.e., electrostatic) streaming instabilities in plasmas. Two equal systems undergoing a streaming instability evolve, one according to the classical Newton's law and one according to the special relativity dynamics equation. The system that obeys Newton's law relaxes to a Maxwellian equilibrium distribution. In the case of the relativistic dynamics, the equilibrium distribution exhibits peaks in the phase space at high momenta and a larger number of particles at high energies. This steady electron population at higher energies could explain power-law energy distribution in many plasma physics and astrophysical systems.

We investigate the properties of the ion sky maps produced by the Dual Ion Spectrometers (DIS) from the Fast Plasma Investigation (FPI). We have trained a convolutional neural network classifier to predict four regions crossed by the Magnetospheric Multiscale Mission (MMS) on the dayside magnetosphere: solar wind, ion foreshock, magnetosheath, and magnetopause using solely DIS spectrograms. The accuracy of the classifier is >98%. We use the classifier to detect mixed plasma regions, in particular to find the bow shock regions. A similar approach can be used to identify the magnetopause crossings and reveal regions prone to magnetic reconnection. Data processing through the trained classifier is fast and efficient and thus can be used for classification for the whole MMS database. Magnetospheric Multiscale Mission (MMS) has been traversing the Earth's magnetosphere to help scientists understand how the tremendous amounts of energy are released through the phenomenon known as magnetic reconnection. The spacecraft can transfer to the Earth only 4% of its measurements due to link limitations. The success of the mission relies on the selection of the most relevant measurement intervals to be sent down to the science operation center. We have trained a small deep convolutional neural network which identifies the kind of plasma the spacecraft is traversing at each measurement interval with an excellent accuracy >98%. We have used our model to identify some of the most interesting regions, bow shocks. It took only a day for the model to process all observations collected by the MMS within 3 years. The model can save a substantial amount of time for the scientists in the loop whose role is to locate such regions manually. The proposed model is suitable for the hierarchy of models being built to fully automate the on‐ground data processing. Moreover, it is small enough to be embedded in the on‐board software of future missions. We develop a technique for automated classification of plasma regions traversed by the Magnetospheric Multiscale Mission spacecraftOur model distinguishes solar wind, megnetosheath, magnetosphere, and ion foreshock with 98% accuracyIt can be used to detect mixed plasma regions, bow shock and magnetopause crossings We develop a technique for automated classification of plasma regions traversed by the Magnetospheric Multiscale Mission spacecraft Our model distinguishes solar wind, megnetosheath, magnetosphere, and ion foreshock with 98% accuracy It can be used to detect mixed plasma regions, bow shock and magnetopause crossings

We investigate the use of artificially increased ion and electron kinetic scales in global plasma simulations. We argue that as long as the global and ion inertial scales remain well separated, (1) the overall global solution is not strongly sensitive to the value of the ion inertial scale, while (2) the ion inertial scale dynamics will also be similar to the original system, but it occurs at a larger spatial scale, and (3) structures at intermediate scales, such as magnetic islands, grow in a self‐similar manner. To investigate the validity and limitations of our scaling hypotheses, we carry out many simulations of a two‐dimensional magnetosphere with the magnetohydrodynamics with embedded particle‐in‐cell (MHD‐EPIC) model. The PIC model covers the dayside reconnection site. The simulation results confirm that the hypotheses are true as long as the increased ion inertial length remains less than about 5% of the magnetopause standoff distance. Since the theoretical arguments are general, we expect these results to carry over to three dimensions. The computational cost is reduced by the third and fourth powers of the scaling factor in two‐ and three‐dimensional simulations, respectively, which can be many orders of magnitude. The present results suggest that global simulations that resolve kinetic scales for reconnection are feasible. This is a crucial step for applications to the magnetospheres of Earth, Saturn, and Jupiter and to the solar corona. The effects of artificially increased kinetic scales are studied with MHD‐EPIC simulationsChanging the kinetic scales does not change the global solution significantlyIncreasing the kinetic scales makes global simulations with embedded kinetic regions feasible

We perform a three‐dimensional (3‐D) global simulation of Earth's magnetosphere with kinetic reconnection physics to study the flux transfer events (FTEs) and dayside magnetic reconnection with the recently developed magnetohydrodynamics with embedded particle‐in‐cell model. During the 1 h long simulation, the FTEs are generated quasi‐periodically near the subsolar point and move toward the poles. We find that the magnetic field signature of FTEs at their early formation stage is similar to a “crater FTE,” which is characterized by a magnetic field strength dip at the FTE center. After the FTE core field grows to a significant value, it becomes an FTE with typical flux rope structure. When an FTE moves across the cusp, reconnection between the FTE field lines and the cusp field lines can dissipate the FTE. The kinetic features are also captured by our model. A crescent electron phase space distribution is found near the reconnection site. A similar distribution is found for ions at the location where the Larmor electric field appears. The lower hybrid drift instability (LHDI) along the current sheet direction also arises at the interface of magnetosheath and magnetosphere plasma. The LHDI electric field is about 8 mV/m, and its dominant wavelength relative to the electron gyroradius agrees reasonably with Magnetospheric Multiscale (MMS) observations. We performed a 1 h long global simulation of Earth's magnetosphere with kinetic modeling of the dayside reconnectionCrater FTE is found at the early stage of a flux rope formationKinetic phenomena are found from the global simulation

Computational fluid dynamics (CFD), in particular applied to turbulent flows, is a research area with great engineering and fundamental physical interest. However, already at moderately high Reynolds numbers the computational cost becomes prohibitive as the range of active spatial and temporal scales is quickly widening. Specifically scale-resolving simulations, including large-eddy simulation (LES) and direct numerical simulations (DNS), thus need to rely on modern efficient numerical methods and corresponding software implementations. Recent trends and advancements, including more diverse and heterogeneous hardware in High-Performance Computing (HPC), are challenging software developers in their pursuit for good performance and numerical stability. The well-known maxim "software outlives hardware" may no longer necessarily hold true, and developers are today forced to re-factor their codebases to leverage these powerful new systems. In this paper, we present Neko, a new portable framework for high-order spectral element discretization, targeting turbulent flows in moderately complex geometries. Neko is fully available as open software. Unlike prior works, Neko adopts a modern object-oriented approach in Fortran 2008, allowing multi-tier abstractions of the solver stack and facilitating hardware backends ranging from general-purpose processors (CPUs) down to exotic vector processors and FPGAs. We show that Neko's performance and accuracy are comparable to NekRS, and thus on-par with Nek5000's successor on modern CPU machines. Furthermore, we develop a performance model, which we use to discuss challenges and opportunities for high-order solvers on emerging hardware. • We introduce Neko, a modernized framework for high-fidelity CFD simulations. • We reveal Neko's inner implementation details and design decisions. • We develop a performance model, which we validate and use to project performance. [ABSTRACT FROM AUTHOR]

AllScale is a programming environment targeting simplified development of highly scalable parallel applications by dividing development responsibilities into silos. The front-end AllScale API provides a simple C++ development environment through a suite of parallel constructs expressions denoting tasks operating concurrently. This interfaces with the other components of the toolchain (core-level API, compiler and runtime) which manages tasks related to the machine and system level, hidden to the user. The paper describes the development of two large-scale parallel applications within the AllScale API, namely, an advection– diffusion model with data assimilation and a Lagrangian space-weather simulation model based on a particle-in-cell method. We present mathematical formulations and implementations and evaluate parallel constructs developed using the AllScale API. The performance of the applications from the perspective of both parallel scalability, and more importantly productivity are assessed. We demonstrate how the AllScale API can greatly improve developer productivity while maintaining parallel performance in two applications with distinct numerical characteristics. Code complexity metrics demonstrate reduction in application specific implementations of up to 30% while performance tests on three different compute systems demonstrate comparable parallel scalability to an MPI version of the code. • Presents a programming environment for simplified development of HPC applications. • Separation of responsibilities between the domain scientist and HPC expert or developer. • Applied to two pilot applications related to data assimilation and particle in cell code. • Enhances developer productivity while maintaining parallel scalability of applications. [ABSTRACT FROM AUTHOR]