# W-kernel support size ## Introduction To reserve sufficient space for the convolution by the w-kernel it is important to know the support in advance. This document describes the derivation of an approximate formula for the w-kernel support size When the W-term is Nyquist sampled in the image domain, the support in the uv-domain fits exactly inside the grid. Strictly speaking the W-term can not be Nyquist sampled, because its support is infinite. However, the W-term can be considered Nyquist sampled when the phase change from pixel to pixel is smaller then $`\pi`$. This criterion cuts the tails of the convolution function at approximately the 1% level. ## Derivation Let the phase of the W-term be given as function of image coordinate $`l`$, ```math \varphi(l) = 2\pi w(1-n(l)) = 2\pi w(1-\sqrt{1 - l^2}), ``` where $`w`$ is the w-coordinate in wavelengths. The phase change from pixel to pixel is given by ```math \Delta\varphi = \frac{\mathrm{d}\varphi(l)}{\mathrm{d}l}\Delta l, ``` where $`\Delta l = s/N `$ and $`s`$ is the image size in radians and $`N`$ is the image size in number of pixels. The derivative is given by ```math \frac{\mathrm{d}\varphi(l)}{\mathrm{d}l} = -2\pi w \frac{-l}{\sqrt{1 - l^2}}. ``` This can be simplified by using the approximation ```math \sqrt{1 - l^2} \approx 1 ``` for small $`l`$. And thus ```math \frac{\mathrm{d}\varphi(l)}{\mathrm{d}l} \approx 2\pi w l. ``` The W-term changes fastest at the edge of the image where $`l = s/2`$. At the edge ```math \Delta \varphi = \pi w s^2/N ``` Equating $`\Delta \varphi`$ to $`\pi`$ leads to the final result $`N = w s^2`$. ## Introducing the shift When imaging a facet in a tangent plane not for the center of the facet, the W-term will depend on the shift parameter as well. Let the shift be given by $`\delta l`$. At the edge of the facet $`l' = s/2 + \delta l`$. ```math \Delta\varphi = 2\pi w l' \Delta l = 2\pi w (s/2 + \delta l) s/N ``` Equation this to $`\pi`$ leads to ```math N = w (s + 2\delta l)s ```