Identification of Electron Diffusion Regions with a Machine Learning Approach on MMS Data at the Earth's Magnetopause

Lenouvel, Q.; Génot, Vincent; Garnier, Philippe; Toledo‐Redondo, Sergio; Lavraud, B.; Aunai, N.; Nguyen, Gautier; Gershman, D. J.; Ergun, R. E.; Lindqvist, Per‐Arne; Giles, B. L.; Burch, J. L.

doi:10.1029/2020ea001530

Cited by 17 publications

(17 citation statements)

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“…In the future, we also plan to investigate the use of artificial intelligence techniques to provide automatic catalogs of plasma boundaries and eventually identify complex non‐linear relationships between the boundaries' location and external/internal drivers. These techniques are mature and proved efficient in space physics to detect plasma phenomena (see e.g., Karimabadi et al., 2009; Nguyen et al., 2019) or to identify parameters of influence (see e.g., Al‐Ghraibah et al., 2015; Benvenuto et al., 2018; Lenouvel et al., 2021).…”

Section: Discussionmentioning

confidence: 99%

The Influence of Crustal Magnetic Fields on the Martian Bow Shock Location: A Statistical Analysis of MAVEN and Mars Express Observations

et al. 2022

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Previous missions underlined the complex influence of the crustal magnetic fields on the Martian environment, including the plasma boundaries. Their influence on the bow shock is however poorly constrained, with most studies showing North/South differences attributed to the crustal fields, with various conclusions from little to strong variabilities. We analyze for the first time in detail the influence of crustal fields on the Martian shock location based on a multi‐mission analysis (MAVEN and MEX). We introduce the angular distance to the strongest crustal field region in the southern hemisphere that induces the largest influence (but not unique, with a minimum pressure threshold analyzed). Its impact is at large scale (>40–60° around), is modulated by the local time of the strongest source region (with no influence beyond terminator), and maximizes when the Interplanetary Magnetic field (IMF) is stable during the preceding hours. We introduce a technique, that is, partial correlations, to provide a coherent picture for both MAVEN/MEX due to existing cross correlations with Extreme UltraViolet (EUV). A composite parameter is proposed, that represents the combined influence of EUV, magnetosonic mach number (two major drivers) and crustal fields, the latter having an impact of hundreds of km. The influence of crustal fields on the shock appears seasonal and correlated with the Total Electronic Content, revealing a large scale coupling between the crustal fields, the ionosphere and the shock. The crustal field influence on the shock is thus significant and complex, with a coupling to both the ionosphere below and the IMF above.

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Section: Discussionmentioning

confidence: 99%

The Influence of Crustal Magnetic Fields on the Martian Bow Shock Location: A Statistical Analysis of MAVEN and Mars Express Observations

et al. 2022

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“…Machine learning is typically the emerging solution to dealing with big data in general, with supervised machine learning techniques being applied to a variety of space physics tasks (e.g. Breuillard et al, 2020;Lenouvel et al, 2021). However, current challenges in ULF wave research mean that many simple tasks (e.g.…”

Section: Discussionmentioning

confidence: 99%

Listening to the Magnetosphere: How Best to Make ULF Waves Audible

Archer

Cottingham

Hartinger

et al. 2022

Front. Astron. Space Sci.

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Observations across the heliosphere typically rely on in situ spacecraft observations producing time-series data. While often this data is analysed visually, it lends itself more naturally to our sense of sound. The simplest method of converting oscillatory data into audible sound is audification—a one-to-one mapping of data samples to audio samples—which has the benefit that no information is lost, thus is a true representation of the original data. However, audification can make some magnetospheric ULF waves observations pass by too quickly for someone to realistically be able to listen to effectively. For this reason, we detail various existing audio time scale modification techniques developed for music, applying these to ULF wave observations by spacecraft and exploring how they affect the properties of the resulting audio. Through a public dialogue we arrive at recommendations for ULF wave researchers on rendering these waves audible and discuss the scientific and educational possibilities of these new methods.

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“…To identify EDRs, we first utilize the criteria in Lenouvel et al (2021), with adjustments, to select candidate events. (We are not using the more sophisticated Neural Network techniques as in Lenouvel et al (2021)). We look for data points that indicate electron current layers with electron nongyrotropy.…”

Section: Observationsmentioning

confidence: 99%

“…Applying the above methods to MMS dayside magnetopause crossings from 2015 fall to 2021 spring, we identify 19 EDR events, where 14 are in the list of Webster et al (2018), 1 is in Lenouvel et al (2021), and five are additional events. Other events in the Webster et al (2018) and Lenouvel et al (2021) lists are not included, mainly because they usually do not satisfy our criteria in the manual selection, for example, no positive E N penetrating to the current sheet mid-plane. Thus, these excluded events may be further away from the X-line compared with those included in this study.…”

Section: Observationsmentioning

confidence: 99%

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Whistler Waves Associated With Electron Beams in Magnetopause Reconnection Diffusion Regions

et al. 2022

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Magnetic reconnection involves explosive energy conversion from electromagnetic fields to plasmas. In this process, highly structured particle distribution functions are formed that are unstable to various instabilities and waves to help dissipate energies and accelerate particles. The whistler wave is one example. It has 𝐴𝐴 𝐴𝐴𝑟𝑟 < 𝐴𝐴𝑐𝑐𝑐𝑐 with right-hand polarization, since it is coupled to the electron gyro-motion, where the wave frequency is expressed as 𝐴𝐴 𝐴𝐴= 𝐴𝐴𝑟𝑟 + 𝑖𝑖𝑖𝑖 . Whistlers can be excited through two modes. (a) The cyclotron mode is excited when the electron distribution has a perpendicular anisotropy that overcomes cyclotron damping (e.g., Gurnett & Bhattacharjee, 2005;Kennel, 1966), and the cyclotron resonant velocity is 𝐴𝐴 𝐴𝐴‖,𝑟𝑟𝑟𝑟𝑟𝑟 ≡ 𝑉𝑉𝑔𝑔𝑔𝑔𝑟𝑟𝑔𝑔 = (𝜔𝜔𝑟𝑟 ± 𝜔𝜔𝑐𝑐𝑟𝑟) ∕𝑘𝑘‖ . (b) The Landau mode requires a positive slope in the distribution along v || ( 𝐴𝐴 𝐴𝐴𝐴𝐴 ∕𝐴𝐴𝑑𝑑‖ > 0 ), and the resonant velocity is 𝐴𝐴 𝐴𝐴‖,𝑟𝑟𝑟𝑟𝑟𝑟 ≡ 𝑉𝑉𝑝𝑝𝑝,‖ = 𝜔𝜔𝑟𝑟∕𝑘𝑘‖ .The whistler wave is commonly observed in magnetopause reconnection, and a few wave excitation mechanisms have been analyzed (e.g., review in Khotyaintsev et al., 2019). The first instability source is the anisotropy of hot magnetospheric electrons (

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Identification of Electron Diffusion Regions with a Machine Learning Approach on MMS Data at the Earth's Magnetopause

Cited by 17 publications

References 44 publications

The Influence of Crustal Magnetic Fields on the Martian Bow Shock Location: A Statistical Analysis of MAVEN and Mars Express Observations

The Influence of Crustal Magnetic Fields on the Martian Bow Shock Location: A Statistical Analysis of MAVEN and Mars Express Observations

Listening to the Magnetosphere: How Best to Make ULF Waves Audible

Whistler Waves Associated With Electron Beams in Magnetopause Reconnection Diffusion Regions

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