CosmoCov_ClCov - harmonic-space shear covariance

Fork of CosmoLike/CosmoCov with interface for shear harmonic space covariance.

CosmoLike/CosmoCov is written by Xiao Fang, Elisabeth Krause & Tim Eifler. Please see their list of papers to cite here.

Compilation

$ make shear_clcov

The GSL and FFTW3 libraries are required.

Usage

The code is designed to produce one block-row of the full shear covariance matrix in a single command, where a single block corresponds to a pair of power spectra.

One block-row corresponds to holding one power spectrum of the pair fixed. This is the spectrum indexed by spec1_idx (see Power spectrum indexing section below). The code will automatically iterate over all spec2_idx <= spec1_idx.

For a given spec1_idx, the code can be run as follows:

$ ./get_shear_clcov {path_to_config.ini} {spec1_idx}

where {path_to_config.ini} is the path to the configuration file (see Configuration section below).

Power spectrum indexing

Since each power spectrum corresponds to a pair of shear fields, the set of power spectra may be laid out in the upper (or lower) triangle of a matrix.

The convention used here is to order the power spectra by diagonal of this matrix, then by row. Note that this corresponds to new=True ordering in healpy. An example is shown below for 5 shear fields, labelled bin1 to bin5.

Zero-based indexing is used.

      bin1 bin2 bin3 bin4 bin5
bin1     0    5    9   12   14
bin2     -    1    6   10   13
bin3     -    -    2    7   11
bin4     -    -    -    3    8
bin5     -    -    -    -    4

Configuration

See an example configuration file: example_input/example.ini.

The config file contains all the settings other than {spec1_idx}. Most are the same as the original CosmoCov settings. A complete list of settings is below.

Inherited from CosmoCov:

• Omega_m, Omega_v, omb, sigma_8, n_spec, w0 wa, h0: cosmological parameters (Omega_v == Omega_lambda);

• area: survey area in square degrees;

• c_footprint_file : (optional) mask power spectrum used for super-sample covariance (is automatically normalised);

• clustering_REDSHIFT_FILE, shear_REDSHIFT_FILE, lens_tomobins, source_tomobins, lens_n_gal, source_n_gal: details of lens and source galaxy samples (file paths, the numbers of tomographic bins, the number densities in each bin); the redshift file has (number of tomo bin + 1) columns, in which the 1st column is the z_min of each z bin;

• sigma_e: total intrinsic shape dispersion;

• lens_tomogbias: linear galaxy bias parameter of each lens galaxy bin;

• lens_tomo_bmag: magnification bias parameter of each lens galaxy bin (with b_mag described in Section 5.1.3 of Fang et al. (arXiv:1911.11947));

• IA: 0 or 1, the switch of running the intrinsic alignment NLA model;

• A_ia, eta_ia: parameters of the NLA model (see Eq. 4.9 of Fang et al. (arXiv:1911.11947), but with A_ia represented by a_IA in the equation).

ClCov-specific settings:

• lmin, lmax: continuous ell range required;

• ell: alternatively, specify discrete ells separated by commas, e.g. 2,5,10,100;

• do_g: include Gaussian contribution (which includes shape noise);

• do_ss: include super-sample covariance;

• do_cng: include connected non-Gaussian covariance (slow and generally sub-dominant);

• output_dir: directory to output results to (must already exist).

Output

For each (spec1, spec2) pair a text file is produced, with filename cov_{contributions}_spec1_{spec1_idx}_spec2_{spec2_idx}.txt, where {contributions} is the relevant combination of g, ss and cng separated by underscores, depending on the settings of do_g, do_ss and do_cng.

The file contains the covariance matrix of the two power spectra with indices spec1_idx and spec2_idx. It is symmetric if spec2_idx == spec1_idx.