Public repository of the Cosmic Linear Anisotropy Solving System (master for the most recent version of the standard code; GW_CLASS to include Cosmic Gravitational Wave Background anisotropies; classnet branch for acceleration with neutral networks; ExoCLASS branch for exotic energy injection; class_matter branch for FFTlog)
How can I create a Gaussian random field (GRF) from the Cl's I am given by CLASS for a patch of sky at high resolution?
The problem is that I can't create a GRF with a high enough resolution when I am bound to use Healpix:
https://github.com/healpy/healpy/issues/564
However, I only need to create a square of 20 deg^2 GRF at a resolution of 0.0024 deg^2. I can think of two options:
Use something similar to the graphical interface RealSpaceInterface, which is in the latest release, since it is able to create a 2D GRF as can be seen in the following presentation slide 16:
https://lesgourg.github.io/class-tour/Narbonne.pdf
Instead of generating angular power spectrum (Cl's), create Fourier power spectrum (Pk's) of the temperature fluctuation. Hence, make use of the flat-sky approximation.
I do not know which option would faster to implement, or how to implement it. I would be very grateful for your advice.
How can I create a Gaussian random field (GRF) from the Cl's I am given by CLASS for a patch of sky at high resolution? The problem is that I can't create a GRF with a high enough resolution when I am bound to use Healpix: https://github.com/healpy/healpy/issues/564 However, I only need to create a square of 20 deg^2 GRF at a resolution of 0.0024 deg^2. I can think of two options:
Use something similar to the graphical interface RealSpaceInterface, which is in the latest release, since it is able to create a 2D GRF as can be seen in the following presentation slide 16: https://lesgourg.github.io/class-tour/Narbonne.pdf
Instead of generating angular power spectrum (Cl's), create Fourier power spectrum (Pk's) of the temperature fluctuation. Hence, make use of the flat-sky approximation.
I do not know which option would faster to implement, or how to implement it. I would be very grateful for your advice.