MIST

By Oliver Allanson (University of Birmingham; University of Exeter)

Quasilinear theories have been shown to well describe a range of transport phenomena in magnetospheric, space, astrophysical and laboratory plasma “weak turbulence” scenarios. It is well known that the resonant diffusion quasilinear theory for the case of a uniform background field may formally describe particle dynamics when the electromagnetic wave amplitude and growth rates are sufficiently “small”, and the bandwidth is sufficiently “large”.

However, it is important to note that for a given wave spectrum that would be expected to give rise to quasilinear transport, the theory may apply for a given range of resonant pitch-angles and energies, but may not apply for some smaller, or larger, values of resonant pitch-angle and energy. That is to say that the applicability of the quasilinear theory can be pitch-angle dependent, even in the case of a uniform background magnetic field. If indeed the quasilinear theory does apply, the motion of particles with different pitch-angles are still characterised by different timescales.

Using a high-performance test-particle code, we present a detailed analysis of the applicability of quasilinear theory to a range of different wave spectra that would otherwise “appear quasilinear” if presented by e.g., satellite survey mode data. We present these analyses as a function of wave amplitude, wave coherence and resonant particle velocities (energies and pitch-angles). In doing so, we identify and classify five different transport regimes (see figure) that are a function of particle pitch-angle.

The results in our paper demonstrate that there can be a significant variety of particle responses (as a function of pitch angle) for very similar looking survey-mode electromagnetic wave products, even if they appear to satisfy all appropriate quasilinear criteria.

In recent years there have been a sequence of very interesting and important results in this domain, and we argue in favour of continuing efforts on: (i) the development of new transport theories to understand the importance of these, and other, diverse electron responses; (ii) which are informed by statistical analyses of the relationship between burst- and survey-mode spacecraft data.

For full details see https://doi.org/10.3389/fspas.2024.1332931

By Andy Smith (Northumbria University)

We often have large, unlabelled datasets in space physics, where the phenomenon of interest only appears rarely. Understanding the underlying physics of the system from rare observations is a challenge, and locating complementary, similar observations in large datasets can be prohibitively time consuming.

In this work we present an automated, self-supervised method by which the key information from two dimensional data can be encoded into a smaller vector representation. This representation (encoding/embedding) contains the key information describing the data; we can then use the distance between vectors to assess the similarity of the observations.

We showed the potential of this method with two example datasets – spacecraft in situ electron velocity distributions and auroral all sky images. For both datasets we provided the method with a library of over five thousand images, which were then effectively and automatically summarized by the model.

In the case of the electron distributions, we tested a “seed” image of a rare phenomena – corresponding to the region of space near the site of magnetic reconnection. In this region the electron distribution takes a characteristic crescent or arc-like shape [Figure 1, centre]. We can then extract the six closest partners of this image, using the distance between the embedding vectors. The two closest neighbours of the seed image (A and B in Figure 1) represent two separate previously published case study examples known to be close to the site of magnetic reconnection.

This method promises to be a useful tool in locating interesting phenomena in large datasets, providing an efficient method for moving from case studies to thorough statistical surveys. Code to train an example model is available at: https://github.com/SmithAndy005/SpaceSSL .

See publication for details:
Smith, A. W., Rae, I. J., Stawarz, J. E., Sun, W. J., Bentley, S., & Koul, A. (2024). Automatic encoding of unlabeled two dimensional data enabling similarity searches: Electron diffusion regions and auroral arcs. Journal of Geophysical Research: Space Physics, 129, e2023JA032096. https://doi.org/10.1029/2023JA032096

By Daniel Ratliff (Northumbria University)

Whistler-Mode Chorus (WMC) waves remain a key contributor to the processes underpinning space weather modelling and have garnered considerable interest for their unique frequency properties (known as tones, where the frequency will rise or fall coherently). This role and phenomena are in no small part due to the interplay between these waves and the electrons present in the magnetosphere. At present, these wave particle interactions are difficult to model simultaneously effectively, and we normally restrict ourselves to the effect of one on the other – either a known wave is used to develop a particle distribution, or a supplied particle distribution generates WMC waves. Can we develop models that do both? And furthermore, can we develop a model that can reproduce this interesting set of frequency dynamics?

In our paper, we use formal perturbation techniques to derive a reduced, nonlinear model for (parallel propagating) WMC that is driven by wave-particle interactions via ponderomotive effects. Our first attempt, the famous Nonlinear Schrodinger equation, fails to generate tones – and so we dig a little deeper to find a term responsive for nonlinear frequency shifts. Surprisingly, this new term responsible for tones vanishes precisely at the WMC band gap at half the electron gyrofrequency, and provides a theoretical basis for why such a bandgap exists. By exploring this model numerically, we also find that there are cases where this tonal behaviour comes with a significant enhancement of the electron kinetic energy – so maybe the magnetosphere’s dawn chorus is at times a swan song in disguise?

See publication for further information:

Ratliff DJ, Allanson O. The nonlinear evolution of whistler-mode chorus: modulation instability as the source of tones. Journal of Plasma Physics. 2023;89(6):905890607. doi:10.1017/S0022377823001265

By Rosie Hodnett (University of Leicester)

The Ionospheric Alfvén Resonator (IAR) occurs when Alfvén waves partially reflect from boundaries in the ionosphere, towards the bottom of the ionosphere and above the F-region peak. The frequencies of the IAR are strongly controlled by the plasma mass density in the ionosphere, which is not uniform.

We have observed IAR in induction coil magnetometer data at Eskdalemuir, UK (BGS site), and extracted the harmonic frequencies for nine years of data. To model the harmonic frequencies, we used the International Reference Ionosphere and the International Geomagnetic Reference Field to model Alfvén velocity profiles. By solving a one-dimensional wave equation, we modelled the first five harmonics of the IAR for times where we had data. The wave structure of the electric field for a uniform case is shown in panel (a), and the resulting modelled harmonics for a non-uniform case is shown in panel (b). We modelled the frequencies with the lower boundary condition of the electric field of the wave being a node (shown in the figure below) and an antinode. By looking at the percentage difference between the fundamental frequency and the average separation of the harmonics (ζ) for both the node and antinode models and comparing this with the data, we find that the lower boundary is closest to being a node. ζ is presented for the node case, with UT, in panels (c) and (d), which show the data and the model respectively, binned by UT. The trend of increasing ζ towards midnight is due to changing Alfvén velocity profiles (shown in panel (e)), and suggests that the ionosphere is becoming more non-uniform. As such, measurements of IAR could be used to gain insight into the shape of the Alfvén velocity profile of the ionosphere.

BGS induction coil magnetometer data, search for 'induction coil': https://webapps.bgs.ac.uk/services/ngdc/
accessions/index.html

See publication for further information:

Hodnett, R. M., Yeoman, T. K., Beggan, C. D., & Wright, D. M. (2024). Modeling and observations of the effects of the Alfvén velocity profile on the Ionospheric Alfvén Resonator. Journal of Geophysical Research: Space Physics, 129, e2023JA032308. https://doi.org/10.1029/2023JA032308