SSC for g-g lensing and galaxy clustering using DarkEmulator #1079
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Add the function Tk3D_SSC_Terasawa22 for computing super-sample covariance. Also add some module to import.
Update tk3d.py
Update tk3d.py
Lint errors correction
Update tk3d.py
Lint-check for SSC-Terasawa
update tk3d.py
Fix free Einasto alpha dimension (#989)
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I implemented the functions to calculate galaxy-matter and galaxy-auto power spectrum responses to the super-survey modes, which are responsible for super sample covariance. The halo statistics (halo-matter/halo-auto power spectrum, mass function) are calculated by DarkEmulator. We approximate the halo-matter/halo-auto power spectrum growth response to super-survey modes by its growth response to the Hubble parameter, which is calculated using DarkEmulator.
Changes are mostly in darkemulator.py, which I created.
In darkemulator.py, the main functions are
darkemu_Pgm_Tk3D_SSC: returns a class:
~pyccl.tk3d.Tk3Dobject containing the super-sample covariance trispectrum between galaxy-matter power spectra.darkemu_Pgm_resp: calculates galaxy-matter power spectrum responses to the super-survey modes.
darkemu_Pgg_resp_zresp/darkemu_Pgg_resp_Asresp: calculates galaxy-auto power spectrum responses to the super-survey modes.