A statistical study of the inferred transverse density profile of coronal loop threads observed with SDO/AIA

Abstract

Aims. We carry out a statistical study of the inferred coronal loop cross-sectional density profiles using extreme ultraviolet (EUV) imaging data from the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO). Methods. We analysed 233 coronal loops observed during 2015/2016. We consider three models for the density profile; the step function (model S ), the linear transition region profile (model L), and a Gaussian profile (model G). Bayesian inference is used to compare the three corresponding forward modelled intensity profiles for each loop. These are constructed by integrating the square of the density from a cylindrical loop cross section along the line of sight, assuming an isothermal cross section, and applying the instrumental point spread function. Results. Calculating the Bayes factors for comparisons between the models, it was found that in 47 % of cases there is very strong evidence for model L over model S and in 45 % of cases very strong evidence for model G over S . Using multiple permutations of the Bayes factor the favoured density profile for each loop was determined for multiple evidence thresholds. There were a similar number of cases where model L or G are favoured, showing evidence for inhomogeneous layers and constantly varying density cross sections, subject to our assumptions and simplifications. Conclusions. For sufficiently well resolved loop threads with no visible substructure it has been shown that using Bayesian inference and the observed intensity profile we can distinguish between the proposed density profiles at a given AIA wavelength and spatial resolution. We have found very strong evidence for inhomogeneous layers, with model L being the most general, and a tendency towards thicker or even continuous layers.

Spatiotemporal Analysis of Coronal Loops Using Seismology of Damped Kink Oscillations and Forward Modeling of EUV Intensity Profiles

“…The results are also consistent with the approach based on a 2D array used in Pascoe et al (2017b) and Goddard et al (2017), but the increased efficiency allows us to readily investigate the variation of the transverse density profile with time (Section 6.1).…”

“…Pascoe et al (2017b) used a similar method (applied to data from SDO/AIA) to estimate the inhomogeneous layer width of a coronal loop and found a value consistent with that calculated seismologically for the same loop in Pascoe et al (2017a). Goddard et al (2017) studied the density profiles of 233 coronal loops and found that the majority exhibit evidence for having an inhomogeneous layer of finite width. The potential for seismological techniques to provide structuring information is also relevant for studies of multi-threaded coronal structures considered by many authors (e.g., Lenz et al 1999;Aschwanden et al 2000;Pascoe et al 2007;Brooks et al 2012;Antolin et al 2015;Aschwanden & Peter 2017).…”

“…Our use of this profile is based on the availability of the full analytical solution for the damping envelope , and so it is currently the only profile that can be used for both our temporal and spatial analysis. However, when considering the spatial information revealed by the intensity profile separate from the seismological method (e.g., Goddard et al 2017;Pascoe et al 2017b), we may choose any other profile to test. Below, we describe six other density profiles we also test against the observational data.…”

Coronal Loop Seismology Using Standing Kink Oscillations With a Lookup Table

“…Another method for estimating ǫ is by forward modeling the appearance of the density profile for direct comparison with the transverse EUV intensity profile of the loop (Goddard et al, 2017;Pascoe et al, 2017b). It is possible to apply both of these methods simultaneously to observational data.…”

Dispersive Evolution of Nonlinear Fast Magnetoacoustic Wave Trains

“…Observations of standing kink oscillations have recently been used to calculate the density (and Alfvén speed) profiles for coronal loops using their damping profiles by resonant absorption (Pascoe et al 2013a(Pascoe et al , 2016(Pascoe et al , 2017a(Pascoe et al , 2017c. The perpendicular inhomogeneity size has also been independently estimated by forward modeling the EUV intensity (Goddard et al 2017;Pascoe et al 2017b), although so far this has relied on the isothermal approximation (e.g., Aschwanden et al 2007), whereas hot (multi-thermal) flaring loops may require more sophisticated forward modeling (e.g., De Moortel & Bradshaw 2008;Van Doorsselaere et al 2016a). Simultaneous observations of standing kink oscillations would therefore allow the density profile to be seismologically inferred, allowing a much narrower parametric study to determine the properties of the driver (e.g., A, x D ) required to reproduce the observed wave trains and/or radio bursts.…”