Welcome to FisherLens. This code provides a wrapper for the CLASS_delens code to facilitate Fisher forecasting of cosmological parameter constraints from CMB spectra.
For full documentation on CLASS_delens, see: https://github.com/selimhotinli/class_delens
Authors: Selim C. Hotinli, Joel Meyers, Cynthia Trendafilova, Daniel Green, Alexander van Engelen
Download and compile the CLASS_delens submodule.
Running the file fisherGenerateDataClass_example.py will produce a set of forecasts for LambdaCDM + N_eff + m_nu, for 20 different experimental configurations.
Within fisherGenerateDataClass_example.py, the following options may be adjusted by the user:
useMPI: Calculating the full covariance matrices including lensing-induced non-Gaussian covariances demands a lot of memory, O(100 GB), and it is thus recommended to perform these calculations on a high-performance computing cluster. The example forecast file is parallelized using MPI, and this feature can be turned on/off with this flag.
expNames: The total number of experiments being included in the forecast.
lmax: The highest \ell-modes to include in the Fisher matrix sum.
lmaxTT: The highest \ell-modes to include for TT, specifically, in the Fisher matrix sum.
lmin: The lowest \ell-modes to include in the Fisher matrix sum.
noiseLevels: The white noise levels, in uK-arcmin, of the experiments being included in the forecast.
beamSizeArcmin: The beam size, in arcmin, of the experiments being included in the forecast.
classExecDir: The directory where you have downloaded and compiled CLASS_delens.
classDataDir: The directory where you would like the intermediate calculation files and the final result files to be stored. Note that the intermediate files can be very large and are best written to e.g. a scratch space.
fileBase: The base file name to be used for all output files.
polCombs: The polarizations to be included in the Fisher matrix sum. BB may also be added.
cosmoFid: A dictionary containing the free parameters of interest and their fiducial values. Only the parameters in cosmoFid will be varied.
stepSizes: A dictionary containing step sizes for parameters to be used for the numerical derivatives.
reconstructionMask: A dictionary that can be used to mask certain \ells from being included in the lensing reconstruction. The example shows how to cut off T at \ell of 3000.
extra_params: A dictionary where you can specify additional CLASS parameters, included model parameters whose values you would like to specify but keep fixed. Additional CLASS_delens options can also be passed within extra_params. See the CLASS_delens repository for full documentation.
ellsToUse: A dictionary specifying which \ells, for each polarization, to include in the Fisher sum.
ellsToUseNG: Same as above, but used when non-Gaussian covariances are included in the calculation. The full covariance matrix will be calculated up to 'lmaxCov', and then the specified lmin, lmax ranges will be used in the Fisher sum.
doNonGaussian: Whether or not to include calculation of lensing-induced non-Gaussian covariances.
includeUnlensedSpectraDerivatives: If doNonGaussian is enabled, this option controls whether or not to include the contributions of derivatives of lensed/delensed CMB spectra with respect to unlensed spectra.
Additional python files and Jupyter notebooks can be found under paperPlots. These will replicate the CMB results and figures from:
Please place the utility file plotTools.py in the same directory as your Jupyter notebooks. This file provides helper functions for loading and manipulating forecast results.
This code is free to use. If you use it, please cite https://arxiv.org/abs/2111.15036 in your publications.
If you use the DALI functionality released alongside our second paper, please also cite https://arxiv.org/abs/2211.06534.