Study of PVI-based diagnostics for 1D time-series in space plasma

¹ Dipartimento di Fisica, Università di Pisa, 56127 Pisa, Italy
e-mail: francesco.finelli@phd.unipi.it
² Dipartimento di Fisica, Universitá della Calabria, Via P. Bucci, 87036 Rende, Italy
³ Aix-Marseille University, CNRS, PIIM UMR 7345, 13007 Marseille, France

Received: 1 July 2021
Accepted: 7 September 2021

Abstract

Context. In the last few decades, increasing evidence has been found in both numerical studies and high-resolution in situ data that magnetic turbulence spontaneously generates coherent structures over a broad range of scales. Those structures play a key role in energy conversion because they are sites where magnetic energy is locally dissipated in plasma heating and particle energization. How much turbulent energy is dissipated via processes such as magnetic reconnection of thin coherent structures, namely current sheets, remains an open question.

Aims. We aim to develop semi-automated methods for detecting reconnection sites over multiple spatial scales. This is indeed pivotal in advancing our knowledge of plasma dissipation mechanisms and for future applications to space data.

Methods. By means of hybrid–Vlasov–Maxwell 2D–3V simulations, we combine three methods based on the partial variance of increments measured at a broad range of spatial scales and on the current density, which together, and in a synergistic way, provide indications as to the presence of sites of magnetic reconnection. We adopt the virtual satellite method, which in upcoming works will allow us to easily extend this analysis to in situ time-series.

Results. We show how combining standard threshold analysis to a 2D scalogram based on magnetic field increments represents an efficient diagnostic for recognizing reconnecting structure in 1D spatial- and time-series. This analysis can serve as input to automated machine-learning algorithms.