3D MHD simulations of coronal loops heated via magnetic braiding II. Automatic detection of reconnection outflows and statistical analysis of their properties

TL;DR

This work addresses how reconnection outflows from component reconnection in magnetically braided coronal loops can diagnose nanoflare heating. It introduces ROAD, a 4D cube–based clustering algorithm, and applies it to a fully 3D MHD loop model from Paper I, identifying fast outflows tied to current sheets with thresholds |J| > J_{tr} and |v_⊥| > V_{tr} (V_{tr} ≈ 45 km s^{-1}). The detected jets are slender, sheet-like structures with temperatures >1.5 MK up to ∼3 MK, speeds of 45–150 km s^{-1}, and durations of tens of seconds, with internal energy dominating the energy budget and correlating with Ohmic heating. The results support reconnection outflows as a diagnostic of nanoflare heating, and the paper outlines future steps to compare with observations via forward modeling and cross-code validation to tighten links between simulations and solar data.

Abstract

Recent observations of fast and bursty ``nanojets'' suggest novel diagnostics of nanoflare heating in the solar corona. The aim of this work is to investigate the presence and properties of reconnection outflows, similar to observed nanojets, in numerical simulations, and explore their relationship with the nanoflare properties. This work explores their potential as diagnostics for nanoflare heating in observations. We developed an algorithm of Reconnection Outflows Automatic Detection (ROAD) in 3D MHD simulations of coronal loops. We applied the algorithm to a 3D MHD stratified coronal loop model heated by magnetic reconnection and analyzed the statistical properties of the jets produced at reconnection sites, over about one solar hour. The magnetic structure is maintained at high temperature and for an indefinite time by intermittent episodes of local magnetic energy release due to reconnection.

Figures (15)

• Figure 1: Schematic representation of component magnetic reconnection. Step A: Photospheric random motions drag the footpoints of two bundles of field lines. Step B: The two sets of field lines are tilted in opposite directions and a current sheet builds up between them. Step C: the magenta and blue field lines reconnects and accelerates two outflows in opposite direction, perpendicularly to the guide field.
• Figure 2: 3D rendering of the magnetically braided coronal flux tubes. Left panel: Stratification of the plasma density at the lower footpoints from the dense chromosphere ($n > 10^{10}\,\mathrm{cm}^{-3}$, reds) to the tenuous corona ($n < 10^{9}\,\mathrm{cm}^{-3}$, blues). Four coloured bundles of field lines are shown. Middle panel: The lower half of the box showcases the temperature distribution with sparse, yellow coloured, hot-spots (as high as $3\,\mathrm{MK}$) localized around narrow current sheets, the blue-to-white strips in the top half domain. Right panel: The mid-plane slice shows the magnitude of the velocity component perpendicular to the magnetic field. Two reconnecting field lines intersect where the velocity is high ($\sim 100\,\mathrm{km}\,\mathrm{s}^{-1}$ in the red spots). Arrows show the strength and orientation of the outflow in the proximity of the magnetic field lines, similar to Fig. \ref{['Fig:paper_2_scheme']}. Movie I shows a $\sim 500\,\mathrm{s}$ long temporal evolution of the three panels, including field line braiding (left), progressive current sheet build-up and dissipation into heat (center), and outflows acceleration during component-reconnection (right).
• Figure 3: Cumulative distribution of the plasma current density magnitude (upper panels) and velocity component perpendicular to $\vec{B}$ (lower panels). Left plot: fraction of the volume enclosed by plasma with current density (velocity) up to $J^{tr}$ ($V_{\perp B}^{tr}$). The best-fit functions above and below $J^{tr} \sim 250\,\mathrm{StC}\,\mathrm{s}^{-1}\,\mathrm{cm}^{-2}$ ($V_{\perp B}^{tr} \sim 45\,\mathrm{km}\,\mathrm{s}^{-1}$) are indicated (red dashed lines). Right panels: Maps of the current density (velocity $\perp B$) magnitude at the mid-plane. The regions with $J < J_{\perp}^{tr}$ ($V < V_{\perp}^{tr}$) are masked out.
• Figure 4: Example of automatic detection reconnection outflows in 3D MHD simulations. Top row: Horizontal cut of the velocity magnitude perpendicularly to the magnetic field across the midplane (corresponding to the loop apex) and at time $t \simeq 2400\,\mathrm{s}$ (left panel); cut of the current density magnitude (middle panel); and, cut of the temperature (right panel). Lower row: Horizontal cut of high-velocity bumps (left panel), cut of high current dissipating regions (middle panel); and, cut of the reconnection outflow clustering as a result of the automatic detection method (right panel). In green (blue) we show the regions where condition $\mathbb{A}$ ($\mathbb{B}$) in Eq. \ref{['eq:clustering_1']} (\ref{['eq:clustering_2']}) is fulfilled. The two regions may overlap (magenta). Movie II shows the evolution of the six panels, including the impulsive reconnection events yielding to fast outflows (upper left), strong current sheets (upper left) and heating (upper right); and their detection by ROAD (lower panels).
• Figure 5: A 3D rendering of the clustering algorithm results $t \simeq 2400\,\mathrm{s}$. Each cluster satisfies Eq. \ref{['eq:clustering_5']} and is shown with a different colour.