Hybridization technique (“feathering”)

In this family, most of the processing is done on the interferometric data alone. Indeed, the interferometric data is deconvolved and corrected for the primary beam contribution to obtain

  $\displaystyle I_\ensuremath{\mathrm{sky}}^\ensuremath{\mathrm{id}} = B_\ensuremath{\mathrm{clean}} \star I_\ensuremath{\mathrm{source}} + N',
$ (14)
where $B_{\ensuremath{\mathrm{clean}}}$ is a Gaussian of FWHM equal to the interferometer resolution and $N'$ is some thermal noise corrected for the primary beam contribution. Two main facts are hidden in this formulation: 1) the field-of-view of the observation is obviously limited to the observed portion of the sky and 2) more importantly, the lack of short-spacings has not yet been overcome and a better formulation would be
  $\displaystyle I_\ensuremath{\mathrm{sky}}^\ensuremath{\mathrm{id}} = \mbox{High...
...nsuremath{\mathrm{clean}} \star I_\ensuremath{\mathrm{source}} \right\}} + N'.
$ (15)
The simplicity of equation 14 is thus slightly misleading but we will keep it for the sake of simplicity. The hybridization method consists in combining two images ( $I_{\ensuremath{\mathrm{meas}}}^{\ensuremath{\mathrm{sd}}}$ and $I_{\ensuremath{\mathrm{clean}}}^{\ensuremath{\mathrm{id}}}$) in the uv plane.

  1. Both images are first spatially regridded on the same fine grid.
  2. The FFT of those two images are computed, and linearly combined by selecting the low spatial frequencies from FFT( $I_{\ensuremath{\mathrm{meas}}}^{\ensuremath{\mathrm{sd}}}$) and the high spatial frequencies from FFT( $I_{\ensuremath{\mathrm{sky}}}^{\ensuremath{\mathrm{id}}}$).
    $\displaystyle \mathrm{FFT}(uv) = f(uv) \mathrm{FFT}(I_{\ensuremath{\mathrm{meas...
...(1-f(uv)) \mathrm{FFT}(I_{\ensuremath{\mathrm{sky}}}^{\ensuremath{\mathrm{id}}}$
    The transition $f(uv)$between low and high spatial frequency is selected to use the best regions of the uv plane in both images.
  3. The result is FFTed back to the image plane to produce a final,unique image, which takes into account both single-dish and interferometric information.
The method has the following free parameters: the transition radius and the detailed shape of that transition. To avoid discontinuity, the transition shape is chosen to be reasonably smooth. When the low resolution image is provided by a single-dish, the best signal-to-noise combination is obtained using a function $f(uv)$ that is Fourier transform of the single-dish beam. However, that is only optimal if the noise in this image is small enough and no other instrumental effect (such as pointing errors or baseline ripples) affect the data. So, $f(uv)$ can also be chosen arbitrarily. The spatial frequency of transition is selected close to the smallest spatial frequency reliably measured by the interferometer (e.g. about 18 m for NOEMA), and/or the largest spatial frequency measured by the low resolution image (e.g. about 20 m for data taken with the IRAM 30-m telescope). For combining ACA and ALMA data, this would be 15 m, and of ACA and 12-m single dish, about 9 m.