This has been puzzling me. Given a set of redshift distributions nᵢ(z), i = 1, 2, ..., it's easy to work out the variance σᵢ² for each bin. How to fill in the rest of the "covariance matrix" so that it has intuitive properties? E.g. perfectly overlapping bins having σᵢⱼ = σᵢ² = σⱼ².

Fantastic little book for World Book Day from DK and Lego

I have just now released version 2023.7 of our cosmological simulation code GLASS. A pretty cool addition are window functions which correspond to linear and cubic spline interpolation, respectively, giving much better approximations of radial functions.

https://glass.readthedocs.io

For a simple lower bound on the accuracy of angular power spectrum codes (non-Limber etc.), you can compare the sum of all tomographic C_ells of your survey and the non-tomographic C_ell.