arXiv subjects

Matthew R. Argall

Publications and source records attributed to Matthew R. Argall.

6 recordsLinked to original sources

arXiv2026

MMS Insights into CME Driven Sub-Alfv\'enic Solar Wind at 1 AU

We report the properties of electron distributions and turbulence during a Coronal Mass Ejection (CME) in April 2023 observed by Magnetospheric Multiscale (MMS). The CME exhibits a clear sheath and magnetic cloud (MC), and within the MC, the solar wind becomes sub-Alfv\'enic for two hours. We investigate plasma and turbulence properties of the sub-Alfv\'enic CME wind and compare them with those in the super-Alfv\'enic solar wind in the MC and CME sheath. Electrons within the sub-Alfv\'enic MC show significantly higher temperatures than those in the CME sheath and the super-Alfv\'enic MC, with their one-dimensional distributions revealing super-thermal tail and a depletion in electron populations between 15-50 eV. Within the CME sheath, isolated regions of electron heating are observed, where parallel energy flux is enhanced up to ~1 keV. Magnetic field fluctuations within the sub-Alfv\'enic MC interval exhibit negligible cross helicity and steeper-than-Kolmogorov scaling in the inertial range, with no clear spectral break. These fluctuations also show reduced intermittency at ion and sub-ion scales, emerging intermittency at electron scales, and weak magnetic compressibility. Together, these observations point to the presence of weak magnetohydrodynamic (MHD) turbulence within the sub-Alfv\'enic MC, resembling conditions commonly observed in planetary magnetospheres such as Jupiter's.

physics.space-ph↗

arXiv2025

The evolution of CME sheath turbulence from L1 to Earth: Wind and MMS observations of the 2023-04-23 CME

An interplanetary shock driven by a coronal mass ejection (CME) containing an interval of sub-Alfv\'enic flow impacted Earth on April 23, 2024. In this article, we analyze the turbulence in the sheath region between the shock and CME to determine how it evolves from L1 (as observed by Wind) to Earth (as observed by MMS, upstream of the bow shock). Wind and MMS were separated by $55\,\mathrm{R_{E}}$ in the dawn-dusk direction, but the shock normals differ by only $2.8^{\circ}$ and the Pearson correlation coefficient between time-shifted magnetic field components is $\rho=0.93$. We observe a shift in the break point of the magnetic power spectral density between inertial and ion kinetic scales toward the ion inertial length and a steepening of the spectral slope, indicating more active energy cascade closer to Earth. The distribution of increments becomes more non-Gaussian near Earth, particularly at ion kinetic scales, indicating the turbulence becomes more intermittent. Finally, the correlation length at Earth is 25\% longer than at L1, indicating that the turbulence is smoothing out the magnetic field. The results present an example of substantial evolution of CME sheath turbulence from L1 to Earth.

physics.space-ph↗

arXiv2024

Turbulence properties and kinetic signatures of electron in Kelvin-Helmholtz waves during a geomagnetic storm

We present a comprehensive study of Magnetospheric Multiscale (MMS) spacecraft encounter with KHI during a geomagnetic storm, focusing on elucidating key turbulence properties and reconnection signatures observed at the edges of KH vortices. The spectral slope for electric field stays approximately constant for frequencies below the ion cyclotron frequency and exhibits a break around the lower hybrid frequency, indicating wave activity. Furthermore, MMS observes a current sheet accompanied by intense electron jets and features consistent with strong guide-field asymmetric reconnection across the magnetopause. Substantial agyrotropy (by a factor of 10) in electron distribution functions is observed in the reconnecting current sheet and at the edges of KH. Our observation presents a multi-scale view into KH turbulence under strongly driven conditions and into the dynamics occurring at electron dissipation scales.

physics.space-ph↗

arXiv2024

Higher-order nonequilibrium term: Effective power density quantifying evolution towards or away from local thermodynamic equilibrium

A common approach to assess the nature of energy conversion in a classical fluid or plasma is to compare power densities of the various possible energy conversion mechanisms. A forefront research area is quantifying energy conversion for systems that are not in local thermodynamic equilibrium (LTE), as is common in a number of fluid and plasma systems. Here, we introduce the ``higher-order non-equilibrium term'' (HORNET) effective power density that quantifies the rate of change of departure of a phase space density from LTE. It has dimensions of power density, which allows for quantitative comparisons with standard power densities. We employ particle-in-cell simulations to calculate HORNET during two processes, namely magnetic reconnection and decaying kinetic turbulence in collisionless magnetized plasmas, that inherently produce non-LTE effects. We investigate the spatial variation of HORNET and the time evolution of its spatial average. By comparing HORNET with power densities describing changes to the internal energy (pressure dilatation, $\rm{Pi-D}$, and divergence of the vector heat flux density), we find that HORNET can be a significant fraction of these other measures (8\% and 35\% for electrons and ions, respectively, for reconnection; up to 67\% for both electrons and ions for turbulence), meaning evolution of the system towards or away from LTE can be dynamically important. Applications to numerous plasma phenomena are discussed.

physics.plasm-ph↗

arXiv2023

Quantifying Energy Conversion in Higher Order Phase Space Density Moments in Plasmas

Weakly collisional and collisionless plasmas are typically far from local thermodynamic equilibrium (LTE), and understanding energy conversion in such systems is a forefront research problem. The standard approach is to investigate changes in internal (thermal) energy and density, but this omits energy conversion that changes any higher order moments of the phase space density. In this study, we calculate from first principles the energy conversion associated with all higher moments of the phase space density for systems not in LTE. Particle-in-cell simulations of collisionless magnetic reconnection reveal that energy conversion associated with higher order moments can be locally significant. The results may be useful in numerous plasma settings, such as reconnection, turbulence, shocks, and wave-particle interactions in heliospheric, planetary, and astrophysical plasmas.

physics.plasm-ph↗

arXiv2020

MMS SITL Ground Loop: Automating the burst data selection process

Global-scale energy flow throughout Earth's magnetosphere (MSP) is catalyzed by processes that occur at Earth's magnetopause (MP). Magnetic reconnection is one process responsible for solar wind entry into and global convection within the MSP, and the MP location, orientation, and motion have an impact on the dynamics. Statistical studies that focus on these and other MP phenomena and characteristics inherently require MP identification in their event search criteria, a task that can be automated using machine learning. We introduce a Long-Short Term Memory (LSTM) Recurrent Neural Network model to detect MP crossings and assist studies of energy transfer into the MSP. As its first application, the LSTM has been implemented into the operational data stream of the Magnetospheric Multiscale (MMS) mission. MMS focuses on the electron diffusion region of reconnection, where electron dynamics break magnetic field lines and plasma is energized. MMS employs automated burst triggers onboard the spacecraft and a Scientist-in-the-Loop (SITL) on the ground to select intervals likely to contain diffusion regions. Only low-resolution data is available to the SITL, which is insufficient to resolve electron dynamics. A strategy for the SITL, then, is to select all MP crossings. Of all 219 SITL selections classified as MP crossings during the first five months of model operations, the model predicted 166 (76%) of them, and of all 360 model predictions, 257 (71%) were selected by the SITL. Most predictions that were not classified as MP crossings by the SITL were still MP-like; the intervals contained mixed magnetosheath and magnetospheric plasmas. The LSTM model and its predictions are public to ease the burden of arduous event searches involving the MP, including those for EDRs. For MMS, this helps free up mission operation costs by consolidating manual classification processes into automated routines.

physics.space-ph↗