Cometary Ionospheres: An Updated Tutorial

This chapter aims at providing the tools and knowledge to understand and model the plasma environment surrounding comets in the innermost part near the nucleus. In particular, our goal is to give an updated post-Rosetta view of this ionised environment: what we knew, what we confirmed, what we overturned, and what we still do not understand.Comment: 41 pages, 14 figures, 3 tables; To be published in Comets III (2023), K. J. Meech and M. Combi (Eds.), University of Arizona Press, Tucso

Making waves: Mirror Mode structures around Mars observed by the MAVEN spacecraft

We present an in-depth analysis of a time interval when quasi-linear mirror mode structures were detected by magnetic field and plasma measurements as observed by the NASA/Mars Atmosphere and Volatile EvolutioN (MAVEN) spacecraft. We employ ion and electron spectrometers in tandem to support the magnetic field measurements and confirm that the signatures are indeed mirror modes. Wedged against the magnetic pile-up boundary, the low-frequency signatures last on average $\sim$10 s with corresponding sizes of the order of 15-30 upstream solar wind proton thermal gyroradii, or 10-20 proton gyroradii in the immediate wake of the quasi-perpendicular bow shock. Their peak-to-peak amplitudes are of the order of 30-35 nT with respect to the background field, and appear as a mixture of dips and peaks, suggesting that they may have been at different stages in their evolution. Situated in a marginally stable plasma with $\beta_{||}\sim$1, we hypothesise that these so-called magnetic bottles, containing a relatively higher energy and denser ion population with respect to the background plasma, are formed upstream of the spacecraft behind the quasi-perpendicular shock. These signatures are very reminiscent of magnetic bottles found at other unmagnetised objects such as Venus and comets, also interpreted as mirror modes. Our case study constitutes the first unmistakable identification and characterisation of mirror modes at Mars from the joint points of view of magnetic field, electron and ion measurements. Up until now, the lack of high-temporal resolution plasma measurements has prevented such an in-depth study.Comment: 37 pages, 11 figures, 1 tabl

First investigation of the diamagnetic cavity boundary layer with a 1D3V PIC simulation

Context. Amongst the different features and boundaries encountered around comets, one remains of particular interest to the plasma community: The diamagnetic cavity. Crossed for the first time at 1P/Halley during the Giotto flyby in 1986 and later met more than 700 times by the ESA Rosetta spacecraft around Comet 67P/Churyumov-Gerasimenko, this region, almost free of any magnetic field, surrounds nuclei of active comets. However, previous observations and modelling of this part of the coma have not yet provided a definitive answer as to the origin of such a cavity and on its border, the diamagnetic cavity boundary layer. Aims. We investigate which forces and equilibrium might be at play and balance the magnetic pressure at this boundary down to the spatial and temporal scales of the electrons in the 1D collisionless case. In addition, we scrutinise assumptions made in magneto-hydrodynamic and hybrid simulations of this environment and check for their validity. Methods. We simulated this region at the electron scale by means of 1D3V particle-in-cell simulations and SMILEI code. Results. Across this layer, depending on the magnetic field strength, the electric field is governed by different equilibria, with a thin double-layer forming ahead. In addition, we show that the electron distribution function departs from Maxwellian and/or gyrotropic distributions and that electrons do not behave adiabatically. We demonstrate the need to investigate this region at the electron scale in depth with fully kinetic simulations

Evolution of the ion environment of comet 67P during the Rosetta mission as seen by RPC-ICA

Rosetta has followed comet 67P from low activity at more than 3.6 au heliocentric distance to high activity at perihelion (1.24 au) and then out again. We provide a general overview of the evolution of the dynamic ion environment using data from the RPC-ICA ion spectrometer. We discuss where Rosetta was located within the evolving comet magnetosphere. For the initial observations, the solar wind permeated all of the coma. In 2015 mid-April, the solar wind started to disappear from the observation region, to re-appear again in 2015 December. Low-energy cometary ions were seen at first when Rosetta was about 100 km from the nucleus at 3.6 au, and soon after consistently throughout the mission except during the excursions to farther distances from the comet. The observed flux of low-energy ions was relatively constant due to Rosetta's orbit changing with comet activity. Accelerated cometary ions, moving mainly in the antisunward direction gradually became more common as comet activity increased. These accelerated cometary ions kept being observed also after the solar wind disappeared from the location of Rosetta, with somewhat higher fluxes further away from the nucleus. Around perihelion, when Rosetta was relatively deep within the comet magnetosphere, the fluxes of accelerated cometary ions decreased, as did their maximum energy. The disappearance of more energetic cometary ions at close distance during high activity is suggested to be due to a flow pattern where these ions flow around the obstacle of the denser coma or due to charge exchange losses

Statistical study of linear magnetic hole structures near Earth

The Magnetospheric Multiscale mission (MMS1) data for 8 months in the winter periods of 2017-2018 and 2018-2019, when MMS had its apogee in the upstream solar wind of the Earth's bow shock, are used to study linear magnetic holes (LMHs). These LMHs are characterized by a magnetic depression of more than 50 % and a rotation of the background magnetic field of less then 10g . A total of 406 LMHs are found and, based on their magnetoplasma characteristics, are split into three categories: cold (increase in density, little change in ion temperature), hot (increase in ion temperature, decrease in density) and sign change (at least one magnetic field component changes sign). The occurrence rate of LMHs is 2.3 per day. All LMHs are basically in pressure balance with the ambient plasma. Most of the linear magnetic holes are found in ambient plasmas that are stable against the mirror-mode generation, but only half of the holes are mirror-mode-stable inside

Statistical distribution of mirror-mode-like structures in the magnetosheaths of unmagnetised planets – Part 1: Mars as observed by the MAVEN spacecraft

In this series of papers, we present statistical maps of mirror-mode-like (MM) structures in the magnetosheaths of Mars and Venus and calculate the probability of detecting them in spacecraft data. We aim to study and compare them with the same tools and a similar payload at both planets. We consider their dependence on extreme ultraviolet (EUV) solar flux levels (high and low) and, specific to Mars, on Mars Year (MY) as well as atmospheric seasons (four solar longitudes Ls). We first use magnetic-field-only criteria to detect these structures and present ways to mitigate ambiguities in their nature. In line with many previous studies at Earth, this technique has the advantage of using one instrument (a magnetometer) with good time resolution, facilitating comparisons between planetary and cometary environments. Applied to the magnetometer data of the Mars Atmosphere and Volatile EvolutioN (MAVEN) spacecraft from November 2014 to February 2021 (MY32–MY35), we detect events closely resembling MMs lasting in total more than 170 000 s, corresponding to about 0.1 % of MAVEN's total time spent in the Martian plasma environment. We calculate MM-like occurrences normalised to the spacecraft's residence time during the course of the mission. Detection probabilities are about 1 % at most for any given controlling parameter. In general, MM-like structures appear in two main regions: one behind the shock and the other close to the induced magnetospheric boundary, as expected from theory. Detection probabilities are higher on average in low-solar-EUV conditions, whereas high-solar-EUV conditions see an increase in detections within the magnetospheric tail. We tentatively link the former tendency to two combining effects: the favouring of ion cyclotron waves the closer to perihelion due to plasma beta effects and, possibly, the non-gyrotropy of pickup ion distributions. This study is the first of two on the magnetosheaths of Mars and Venus.</p

Advancing Our Understanding of Martian Proton Aurora through a Coordinated Multi-Model Comparison Campaign

Proton aurora are the most commonly observed yet least studied type of aurora at Mars. In order to better understand the physics and driving processes of Martian proton aurora, we undertake a multi-model comparison campaign. We compare results from four different proton/hydrogen precipitation models with unique abilities to represent Martian proton aurora: Jolitz model (3-D Monte Carlo), Kallio model (3-D Monte Carlo), Bisikalo/Shematovich et al. model (1-D kinetic Monte Carlo), and Gronoff et al. model (1-D kinetic). This campaign is divided into two steps: an inter-model comparison and a data-model comparison. The inter-model comparison entails modeling five different representative cases using similar constraints in order to better understand the capabilities and limitations of each of the models. Through this step we find that the two primary variables affecting proton aurora are the incident solar wind particle flux and velocity. In the data-model comparison, we assess the robustness of each model based on its ability to reproduce a MAVEN/IUVS proton aurora observation. All models are able to effectively simulate the data. Variations in modeled intensity and peak altitude can be attributed to differences in model capabilities/solving techniques and input assumptions (e.g., cross sections, 3-D versus 1-D solvers, and implementation of the relevant physics and processes). The good match between the observations and multiple models gives a measure of confidence that the appropriate physical processes and their associated parameters have been correctly identified and provides insight into the key physics that should be incorporated in future models