CMBLike

A provisional new CMB likelihood module for CosmoMC. Download cosmomc/source code (to be integrated with next cosmomc release; unzip replacing old files in cosmomc/source). New likelihood code is in Planck_like.f90.

New likelihood module reads in XXX.dataset file as usual. The dataset file specifies files giving the C_l estimators, noise C_l, covariance matrix, and fiducial model used to calculate the covariance matrix. Dataset file parameters:

like_approx: 1: The new approximation, 2: Gaussian approximation with fixed covariance, 3. Exact full sky (Wishart)
cl_lmin, cl_lmax: The range of l to use for calculating likelihoods
fields_use: The fields to use for calculating the likelihoods. Can be any combination of T, E, B.
cl_hat_file: The text file of C_l estimators, first column ell, other columns specified by cl_hat_order. If cl_hat_includes_noise=T the C_l include noise, otherwise they don't (are cross-estimators or have the noise bias subtracted). All units are muK^2, and numbers given are l(l+1)C_l/2pi.
cl_fiducial_file: Fiducial power spectrum that was used for calculating/simulating the covariance matrix (in the same format)
cl_noise_file: N_l noise power spectra
covmat_fiducial: Currently a single precision binary file containing the C_l estimator covariance matrix evaluated for the fiducial model. The range of ell is specified in covmat_lmin, covmat_lmax, and ordering of the C_l in covmat_cl. The matrix has side (covmat_lmax-covmat_lmin+1)*(number of elements in covmat_cl), with the indices running from C¹_{covmat_lmin..covmat_lmax},C²_{covmat_lmin..covmat_lmax},..... It must be invertible when cut from cl_lmin to cl_lmax.
The binary matrix can be read/written using AMLUtils routines MatrixSym_Read_Binary and MatrixSym_Write_Binary_Single, e.g. write matrix mat using
```
do i=1,n
    write (file_unit) real(mat(i:n,i), kind(1.0))
end do
```
Should probably integrate fits option. Any standards for storing general symmetric fits matrices?

The module currently inverts the required part of the covariance matrix and caches it for future re-use. So first time it runs it can be slow to start. You can download a sample dataset file and files.

Simulation code

The likelihood approximations have been tested extensively in Hammimeche&Lewis. You can download the code used for simple hybrid Pseudo-C_l simulation of single maps with Planck-like noise (you'd have to install the mask and noise fits files separately). Assumes Healpix is installed, and is based on LensPix MPI interface to Healpix. Since probably no-one will download it, there is no documentation. Some routines may be of general use though, e.g. for calculating arrays of Pseudo-Cl coupling matrices quickly over a cluster.

Note compiling with heap-arrays option is essential for intel compilers (or generally make stack size huge).

AL Dec 07.