We present the stray-light point-spread functions (PSFs) and their inverses we characterized for the Atmospheric Imaging Assembly (AIA) EUV telescopes on board the Solar Dynamics Observatory (SDO) spacecraft. The inverse kernels are approximate inverses under convolution. Convolving the original Level 1 images with them produces images with improved stray-light characteristics. We demonstrate the usefulness of these PSFs by applying them to two specific cases: photometry and differential emission measure (DEM) analysis. The PSFs consist of a narrow Gaussian core, a diffraction component, and a diffuse component represented by the sum of a Gaussian-truncated Lorentzian and a shoulder Gaussian. We determined the diffraction term using the measured geometry of the diffraction pattern identified in flare images and the theoretically computed intensities of the principal maxima of the first few diffraction orders. To determine the diffuse component, we fitted its parameterized model using iterative forward-modeling of the lunar interior in the SDO/AIA images from the 2011 March 4 lunar transit. We find that deconvolution significantly improves the contrast in dark features such as miniature coronal holes, though the effect was marginal in bright features. On a percentage-scattering basis, the PSFs for SDO/AIA are better by a factor of two than that of the EUV telescope on board the Transition Region And Coronal Explorer mission. A preliminary analysis suggests that deconvolution alone does not affect DEM analysis of small coronal loop segments with suitable background subtraction. We include the derived PSFs and their inverses as supplementary digital materials.

The coronal heating mechanism for active region core loops is difficult to determine because these loops are often not resolved and cannot be studied individually. Rather, we concentrate on the "inter-moss" areas between loop footpoints. We use observations from the Hinode EUV Imaging Spectrometer and the X-Ray Telescope to calculate the emission measure distributions of eight inter-moss areas in five different active regions. The combined data sets provide both high-and low-temperature constraints and ensure complete coverage in the temperature range appropriate for active regions. For AR 11113, the emission can be modeled with heating events that occur on timescales less than the cooling time. The loops in the core regions appear to be close to equilibrium and are consistent with steady heating. The other regions studied, however, appear to be dominated by nanoflare heating. Our results are consistent with the idea that active region age is an important parameter in determining whether steady or nanoflare heating is primarily responsible for the core emission, that is, older regions are more likely to be dominated by steady heating, while younger regions show more evidence of nanoflares.

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