SPT CMB-cluster lensing

Estimator reference: SPTpol CMB-cluster lensing using polarisation-only data. arXiv: 1907.08906

Example:

• Look into this notebook for a simple example.

Steps for pipeline execution:

• Step 1: Creating cluster lensed or random unlensed CMB simulations.
  • python step1_create_sims.py -paramfile params.ini (for cluster lensed sims)
  • python step1_create_sims.py -paramfile params.ini -clusters_or_randoms randoms (for random unlensed sims used for background subtraction)
• Step 2: Create models.
  • python step2_gen_models.py -dataset_fname [path_to_cluster_lensed_cmb_sim_file_from_step1]
• Step 3: Estimate covariance matrix using JK approach / obtain likelihoods. This module also helps you to do tSZ subtraction automatically if cluster correalted tSZ signal is added to the lensed CMB simulations.
  • python step3_get_likelihoods.py -dataset_fname [path_to_cluster_lensed_cmb_sim_file_from_step1]