Four‐Spacecraft Measurements of the Shape and Dimensionality of Magnetic Structures in the Near‐Earth Plasma Environment

Abstract

We present a new method for determining the main relevant features of the local magnetic field configuration, based entirely on the knowledge of the magnetic field gradient four‐spacecraft measurements. The method, named “magnetic configuration analysis” (MCA), estimates the spatial scales on which the magnetic field varies locally. While it directly derives from the well‐known magnetic directional derivative and magnetic rotational analysis procedures (Shi et al., 2005, htpps://doi.org/10.1029/2005GL022454; Shen et al., 2007, https://doi.org/10.1029/2005JA011584), MCA was specifically designed to address the actual magnetic field geometry. By applying MCA to multispacecraft data from the Magnetospheric Multiscale (MMS) satellites, we perform both case and statistical analyses of local magnetic field shape and dimensionality at very high cadence and small scales. We apply this technique to different near‐Earth environments and define a classification scheme for the type of configuration observed. While our case studies allow us to benchmark the method with those used in past works, our statistical analysis unveils the typical shape of magnetic configurations and their statistical distributions. We show that small‐scale magnetic configurations are generally elongated, displaying forms of cigar and blade shapes, but occasionally being planar in shape like thin pancakes (mostly inside current sheets). Magnetic configurations, however, rarely show isotropy in their magnetic variance. The planar nature of magnetic configurations and, most importantly, their scale lengths strongly depend on the plasma β parameter. Finally, the most invariant direction is statistically aligned with the electric current, reminiscent of the importance of electromagnetic forces in shaping the local magnetic configuration.

Characterizing current structures in 3D hybrid-kinetic simulations of plasma turbulence

“…Turbulent, magnetised plasmas permeate a wide range of space and astrophysical environments, and plasma turbulence naturally develops coherent structures characterized by high current density and strong magnetic shear. These features are indeed present in practically any turbulence simulation employing the most disparate plasma models and regimes (e.g., Zhdankin et al 2013;Passot et al 2014;Navarro et al 2016;Zhdankin et al 2017;Cerri et al 2019;Comisso and Sironi 2019, and references therein), as well as routinely observed via in-situ measurements in space plasmas such as the solar wind and the near-Earth environment (e.g., Podesta 2017;Greco et al 2018;Fadanelli et al 2019;Pecora et al 2019;Gingell et al 2020;Khabarova et al 2021, and references therein). The characterization of current structures in turbulent plasmas is of particular interest not only because magnetic reconnection and/or different dissipation processes can occur inside (or close to) these regions, thus enabling energy conversion and plasma heating (e.g., Gosling and Phan 2013;TenBarge and Howes 2013;Osman et al 2014;Zhdankin et al 2014;Navarro et al 2016;Grošelj et al 2017;Matthaeus et al 2020;Agudelo Rueda et al 2021, and references therein), but also because reconnection processes occurring within such structures can in turn feed back onto turbulence itslef by playing a major role in the scale-to-scale energy transfer (e.g., Carbone et al 1990;Cerri and Califano 2017;Loureiro and Boldyrev 2017;Franci et al 2017;Mallet et al 2017;Camporeale et al 2018;Dong et al 2018;Vech et al 2018;Papini et al 2019).…”

“…We remind the reader that the work by Fadanelli et al (2019) is focused only on satellite data and thus on local measurements, providing point by point value for E and P along spacecrafts' trajectories. On the contrary here, taking advantage of the 3D data of a simulation, we can also give an overall/non-local picture of current structures (via E and P).…”

“…We will investigate the magnetic configuration shape factors (planarity and elongation), the characteristic eigenvalues (proportional to the characteristic scale lengths) and the orientation of magnetic field and current density. We will use the N tensor and its eigenvalues, but without restricting our analysis to points owning to the current structures, as for NB and AV methods, thus we will essentially apply the MCA method as described first in Fadanelli et al (2019). The aim is to determine what are the statistical characteristics of magnetic configurations that emerge in our simulations and whether there is any appreciable difference between the configurations found inside and outside current structures.…”

Energy Transfer Between Hot Protons and Electromagnetic Ion Cyclotron Waves in Compressional Pc5 Ultra‐low Frequency Waves

“…Because the fluctuations of the magnetic field gradient (grad B 0_EMIC ) were dominated by the y component in FAC (Figure S1g) the troughs of magnetic field intensity in the compressional ULF wave probably had been elongated along the magnetic field and radial directions (knife-blade or pancake shape (Figure 1 of Fadanelli et al, (2019)). This characteristic of the compressional ULF wave is similar to some other spacecraft observations in the magnetosphere (Korotova et al, 2009(Korotova et al, , 2013Tian et al, 2020).…”

Nonlinear Magnetic Gradients and Complete Magnetic Geometry From Multispacecraft Measurements

“…Actually, the third eigenvalue  3 is zero Fadanelli et al (2019). has presented one verification on this property of the magnetic rotational tensor.…”