Online material

Appendix A: AIA response functions

Figure A.1 shows the AIA response functions calculated with the present atomic data (full lines) as compared to those obtained from CHIANTI v.6 (dashed lines).

Since iron is the dominant element in all of the six EUV bands considered here, the iron abundance is the main unknown paramater. The “coronal” abundances adopted within the standard AIA responses are a compilation of older measurements, and have an iron abundance a factor 3.98 higher than the photospheric value of Asplund et al. (2009). Any emission measure obtained from AIA observations would therefore scale by this factor. It is however interesting to see if different elemental abundances have an effect on the shape of the AIA responses. Figure A.2 displays the AIA response functions calculated with “coronal” abundances (solid lines) and with the ‘photospheric’ abundances, scaled by a 3.98 factor (dashed lines). It is clear that the main peaks in the responses are the same, due to the fact that the peak emission contributing to the AIA bands comes from iron. However, significant differences in the secondary peaks, in particular for the 193 and 211 Å bands, are present. These differences would be enhanced when cool emission is observed.

	Fig. A.1 Top: the SDO AIA response functions calculated with the CHIANTI v.6 ion abundances, the “photospheric” (Asplund et al. 2009) abundances at constant pressure (1015 cm-3 K), with the present atomic data (full lines) and CHIANTI v.6 (dashed lines).
Open with DEXTER

	Fig. A.2 The SDO AIA response functions calculated with the CHIANTI v.6 ion abundances, constant pressure (1015 cm-3 K), “coronal” abundances (solid lines) and with “photospheric” abundances, scaled by a 3.98 factor (dashed lines).
Open with DEXTER

; Here is a simple example on how to calculate
the
; AIA temperature response function for the
193 A channel, using the SSW AIA and
CHIANTI programs.

; First, we need to define an array of
;temperatures:

temp=10.d^(indgen(81)*0.05+4.0)

; The we calculate an isothermal spectrum using
; the CHIANTI routine isothermal.
; The example below is with constant density
; (edensity=1.e9), including all the lines
(/all),
; the continuum (/cont), over a range of
5--500 A,
; with a 0.1 A bin, and your choice of elemental
; (abund_name=) and ion (ioneq_name=) abundance.

isothermal, 5, 500, 0.1, temp, lambda,spectrum,\begin{formule}$ 
  list_wvl,list_ident,$\end{formule}
  edensity=1.e9 ,/photons,/cont, \begin{formule}$ 
  abund_name=’asplund_etal_09.abund’,$\end{formule}
  ioneq_name=!xuvtop+’/ioneq/chianti.ioneq’
,/all


; This is the conversion factor for an AIA pixel
; (number of steradians per AIA pixel size):

sterad_aia_pix=8.4d-12

; Get the AIA effective areas from Solarsoft:

aia_resp = aia_get_response(/dn)

; regrid the AIA effective areas onto the
; wavelength grid with e.g. interpol:

eff_193=interpol(aia_resp.a193.ea, \begin{formule}$ 
aia_resp.a193.wave,lambda) ; 

fold the isothermal spectra with the 
; effective areas: 
sp_conv= spectrum & sp_conv[*,*]=0. 
for i=0,n_elements(temp)-1 do $\end{formule}
 sp_conv[*, i]=sterad_aia_pix*spectrum[*,i]*eff_193

; total over the wavelengths:

resp_193=total(sp_conv,1)

; plot

plot_oo,temp,resp_193

Appendix B: The EIS spatial resolution

In principle, AIA images could be used to estimate the effective EIS spatial resolution. As clearly shown in this paper, all AIA images are multi-thermal, hence a direct comparison with the EIS monchromatic images is not possible. The only direct comparison that can be made is when considering the 193 Å band. Indeed EIS does observe all the lines contributing to the AIA 193 Å band.

For each EIS slit position, we first convolved each AIA 193 Å image. We then averaged those AIA images taken during each EIS exposure, rebinned them onto the “EIS pixel” size, and obtained a slice of the corresponding averaged AIA image. We then built a time-averaged “rebinned” image for direct comparison with the EIS monochromatic images. Figure B.1 shows three AIA 193 Å images. The first (top right) is obtained without convolution, while the other two (bottom row) are obtained by convolving the AIA images with a Gaussian PSF of 2, and 4″ full-width-half-maximum (FWHM). We also took the EIS calibrated spectra, and for each point multiplied them with the AIA 193 Å effective area, and summed over wavelength, to obtain effective AIA DN/s per EIS pixel. The resulting image is shown in Fig. B.1 (top left). This image is very close, in morphology and count rates, to the AIA one convolved with a PSF between 2 and 4″, if one considers the presence of the jitter.

What is remarkable is the agreement between the count rates predicted from the EIS spectra and those actually measured by AIA. This is shown in Fig. B.2, where a cut across the images is shown. It is interesting to note that the exact value of the EIS PSF is not relevant for the discussion in this paper, indeed the count rates obtained with a PSF of 2 or 4″ are very similar in most locations. A more detailed analysis of the EIS PSF is deferred to a future paper, once the AIA PSF is well-known.

	Fig. B.1 Top left: an image in the AIA 193 Å band, as predicted from the Hinode EIS spectra. The other images are obtained from the AIA 193 Å data, rebinned onto the EIS spatio-temporal scale. The top right is without convolution, while the other two are convolved with a PSF of FWHM of 2 and 4″.
Open with DEXTER

	Fig. B.2 AIA 193 Å count rates along the E-W direction, at solar Y = 313 (see Fig. B.1).
Open with DEXTER

Appendix C: AIA simulated data for the loop leg region L

Simulated AIA count rates have been obtained for the loop leg region L following the same procedure outlined for the loop base region “B”. The results, shown in Figs. C.1, C.2, are similar, although the plasma is somewhat warmer.

	Fig. C.1 AIA simulated spectra from the DEM modeling for the loop leg region L.
Open with DEXTER

	Fig. C.2 AIA simulated spectra in the 335 Å band from the DEM modeling for the loop leg region L.
Open with DEXTER

© ESO, 2011