Multi-Channel Auto-Calibration for the Atmospheric Imaging Assembly using Machine Learning

Solar activity plays a quintessential role in influencing the interplanetary medium and space-weather around the Earth. Remote sensing instruments onboard heliophysics space missions provide a pool of information about the Suns activity via the measurement of its magnetic field and the emission of light from the multi-layered, multi-thermal, and dynamic solar atmosphere. Extreme UV (EUV) wavelength observations from space help in understanding the subtleties of the outer layers of the Sun, namely the chromosphere and the corona. Unfortunately, such instruments, like the Atmospheric Imaging Assembly (AIA) onboard NASAs Solar Dynamics Observatory (SDO), suffer from time-dependent degradation, reducing their sensitivity. Current state-of-the-art calibration techniques rely on periodic sounding rockets, which can be infrequent and rather unfeasible for deep-space missions. We present an alternative calibration approach based on convolutional neural networks (CNNs). We use SDO-AIA data for our analysis. Our results show that CNN-based models could comprehensively reproduce the sounding rocket experiments outcomes within a reasonable degree of accuracy, indicating that it performs equally well compared with the current techniques. Furthermore, a comparison with a standard astronomers technique baseline model reveals that the CNN approach significantly outperforms this baseline. Our approach establishes the framework for a novel technique to calibrate EUV instruments and advance our understanding of the cross-channel relation between different EUV channels.

Differential Emission Measure Plasma Diagnostics of a Long-Lived Coronal Hole

We use Solar Dynamics Observatory (SDO)/Atmospheric Imaging Assembly (AIA) data to reconstruct the plasma properties from differential emission measure (DEM) analysis for a previously studied long-lived, low-latitude coronal hole (CH) over its lifetime of ten solar rotations. We initially obtain a non-isothermal DEM distribution with a dominant component centered around 0.9 MK and a secondary smaller component at 1.5 - 2.0 MK. We find that deconvolving the data with the instrument point spread function (PSF) to account for long-range scattered light reduces the secondary hot component. Using the 2012 Venus transit and a 2013 lunar eclipse to test the efficiency of this deconvolution, significant amounts of residual stray light are found for the occulted areas. Accounting for this stray light in the error budget of the different AIA filters further reduces the secondary hot emission, yielding CH DEM distributions that are close to isothermal with the main contribution centered around 0.9 MK. Based on these DEMs, we analyze the evolution of the emission measure (EM), density, and averaged temperature during the CHs lifetime. We find that once the CH is clearly observed in EUV images, the bulk of the CH plasma reveals a quite constant state, i.e. temperature and density reveal no major changes, whereas the total CH area and the photospheric magnetic fine structure inside the CH show a distinct evolutionary pattern. These findings suggest that CH plasma properties are mostly set at the CH formation or/and that all CHs have similar plasma properties.

Spectroscopy and Differential Emission Measure diagnostics of a coronal dimming associated with a fast halo CME

We study the coronal dimming caused by the fast halo CME (deprojected speed v =1250 km s $^{-1})$ associated with the C3.7 two-ribbon flare on 2012 September 27, using Hinode/EIS spectroscopy and SDO/AIA Differential Emission Measure (DEM) analysis. The event reveals bipolar core dimmings encompassed by hook-shaped flare ribbons located at the ends of the flare-related polarity inversion line, and marking the footpoints of the erupting filament. In coronal emission lines of $log T , [{rm K}] = 5.8-6.3$, distinct double component spectra indicative of the superposition of a stationary and a fast up-flowing plasma component with velocities up to 130 km s$^{-1}$ are observed at regions, which were mapped by the scanning EIS slit close in time of their impulsive dimming onset. The outflowing plasma component is found to be of the same order and even dominant over the stationary one, with electron densities in the upflowing component of $2times 10^{9}$cm$^{-3}$ at $log T , [{rm K}] = 6.2$. The density evolution in core dimming regions derived from SDO/AIA DEM analysis reveals impulsive reductions by $40 - 50%$ within $lesssim$10 min, and remains at these reduced levels for hours. The mass loss rate derived from the EIS spectroscopy in the dimming regions is of the same order than the mass increase rate observed in the associated white light CME ($1 times 10^{12} {rm ; g ; s}^{-1}$), indicative that the CME mass increase in the coronagraphic field-of-view results from plasma flows from below and not from material piled-up ahead of the outward moving and expanding CME front.

On the Accuracy of the Differential Emission Measure Diagnostics of Solar Plasmas. Application to AIA/SDO. Part II: Multithermal plasmas

The Differential Emission Measure (DEM) analysis is one of the most used diagnostic tools for solar and stellar coronae. Being an inverse problem, it has limitations due to the presence of random and systematic errors. We present in theses series of papers an analysis of the robustness of the inversion in the case of AIA/SDO observations. We completely characterize the DEM inversion and its statistical properties, providing all the solutions consistent with the data along with their associated probabilities, and a test of the suitability of the assumed DEM model. While Paper I focused on isothermal conditions, we now consider multi-thermal plasmas and investigate both isothermal and multithermal solutions. We demonstrate how the ambiguity between noises and multi-thermality fundamentally limits the temperature resolution of the inversion. We show that if the observed plasma is multi-thermal, isothermal solutions tend to cluster on a constant temperature whatever the number of passbands or spectral lines. The multi-thermal solutions are also found to be biased toward near isothermal solutions around 1 MK. This is true even if the residuals support the chosen DEM model, possibly leading to erroneous conclusions on the observed plasma. We propose tools to identify and quantify the possible degeneracy of solutions, thus helping the interpretation of DEM inversion.

On the Accuracy of the Differential Emission Measure Diagnostics of Solar Plasmas. Application to AIA/SDO. Part I: Isothermal plasmas

DEM analysis is a major diagnostic tool for stellar atmospheres. But both its derivation and its interpretation are notably difficult because of random and systematic errors, and the inverse nature of the problem. We use simulations with simple thermal distributions to investigate the inversion properties of SDO/AIA observations of the solar corona. This allows a systematic exploration of the parameter space and using a statistical approach, the respective probabilities of all the DEMs compatible with the uncertainties can be computed. Following this methodology, several important properties of the DEM inversion, including new limitations, can be derived and presented in a very synthetic fashion. In this first paper, we describe the formalism and we focus on isothermal plasmas, as building blocks to understand the more complex DEMs studied in the second paper. The behavior of the inversion of AIA data being thus quantified, and we provide new tools to properly interpret the DEM. We quantify the improvement of the isothermal inversion with 6 AIA bands compared to previous EUV imagers. The maximum temperature resolution of AIA is found to be 0.03 log Te, and we derive a rigorous test to quantify the compatibility of observations with the isothermal hypothesis. However we demonstrate limitations in the ability of AIA alone to distinguish different physical conditions.