Model Comparison for the Density Structure Across Solar Coronal Waveguides

Arregui, I.; Soler, Roberto; Ramos, A. Asensio

doi:10.1088/0004-637x/811/2/104

Cited by 26 publications

(21 citation statements)

References 52 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Terradas et al 2008;Pascoe et al 2011) and other profiles can be considered, such as a sinusoidal (e.g. Goossens et al 2002;Roberts 2008) or parabolic (Arregui et al 2015) transition layer profile. We also consider a Gaussian density profile (Model G; e.g.…”

Section: Methodsmentioning

confidence: 99%

Coronal loop density profile estimated by forward modelling of EUV intensity

Pascoe

Goddard

Anfinogentov

et al. 2017

A&A

View full text Add to dashboard Cite

Aims. The transverse density structuring of coronal loops was recently calculated for the first time using the general damping profile for kink oscillations. This seismological method assumes a density profile with a linear transition region. We consider to what extent this density profile accounts for the observed intensity profile of the loop, and how the transverse intensity profile may be used to complement the seismological technique. Methods. We use isothermal and optically transparent approximations for which the intensity of extreme ultraviolet (EUV) emission is proportional to the square of the plasma density integrated along the line of sight. We consider four different models for the transverse density profile; the generalised Epstein profile, the step function, the linear transition region profile, and a Gaussian profile. The effect of the point spread function is included and Bayesian analysis is used for comparison of the models. Results. The two profiles with finite transitions are found to be preferable to the step function profile, which supports the interpretation of kink mode damping as being due to mode coupling. The estimate of the transition layer width using forward modelling is consistent with the seismological estimate. Conclusions. For wide loops, that is those observed with sufficiently high spatial resolution, this method can provide an independent estimate of density profile parameters for comparison with seismological estimates. In the ill-posed case of only one of the Gaussian or exponential damping regimes being observed, it may provide additional information to allow a seismological inversion to be performed. Alternatively, it may be used to obtain structuring information for loops that do not oscillate.

show abstract

Section: Methodsmentioning

confidence: 99%

Coronal loop density profile estimated by forward modelling of EUV intensity

Pascoe

Goddard

Anfinogentov

et al. 2017

A&A

View full text Add to dashboard Cite

show abstract

“…In Pascoe et al (2017b) the result of this seismology was compared to density profiles estimated from the EUV intensity for one coronal loop. Arregui et al (2015) considered the dependence of seismological information on the inhomogeneous layer density profile, without the use of the non-exponential section of the damping envelope, meaning inversion curves were obtained and compared for the different density profiles.…”

Section: Introductionmentioning

confidence: 99%

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

Goddard

Pascoe

Anfinogentov

et al. 2017

A&A

View full text Add to dashboard Cite

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.

show abstract

“…Considering different alternatives for the density profile leads to differences in the forward predictions and also in the inverse so-Article number, page 6 of 16 lutions. The latter may be important in strong damping regimes, as shown by Arregui et al (2015).…”

Section: Information On Wave Dampingmentioning

confidence: 94%

Inference of magnetic field strength and density from damped transverse coronal waves

Arregui

Montes-Solís

Ramos

2019

A&A

Self Cite

View full text Add to dashboard Cite

A classic application of coronal seismology uses transverse oscillations of waveguides to obtain estimates of the magnetic field strength. The procedure requires information on the density of the structures. Often, it ignores the damping of the oscillations. We computed marginal posteriors for parameters such as the waveguide density; the density contrast; the transverse inhomogeneity lengthscale; and the magnetic field strength, under the assumption that the oscillations can be modelled as standing magnetohydrodynamic (MHD) kink modes damped by resonant absorption. Our results show that the magnetic field strength can be properly inferred, even if the densities inside and outside the structure are largely unknown. Incorporating observational estimates of plasma density further constrains the obtained posteriors. The amount of information one is willing to include (a priori) for the density and the density contrast influences their corresponding posteriors, but very little the inferred magnetic field strength. The decision to include or leave out the information on the damping and the damping time-scales have a minimal impact on the obtained magnetic field strength. In contrast to the classic method which provides with numerical estimates with error bars or possible ranges of variation for the magnetic field strength, Bayesian methods offer the full distribution of plausibility over the considered range of possible values. The methods are applied to available datasets of observed transverse loop oscillations, can be extended to prominence fine structures or chromospheric spicules and implemented to propagating waves in addition to standing oscillations.

show abstract

Model Comparison for the Density Structure Across Solar Coronal Waveguides

Cited by 26 publications

References 52 publications

Coronal loop density profile estimated by forward modelling of EUV intensity

Coronal loop density profile estimated by forward modelling of EUV intensity

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

Inference of magnetic field strength and density from damped transverse coronal waves

Contact Info

Product

Resources

About