This is a set of python tools dedicated to CMB lensing and CMB delensing, by Julien Carron.

Main features are:

• Maximum a posterior estimation of CMB lensing deflection maps from temperature and/or polarization maps.
  (See https://arxiv.org/abs/1704.08230 by J.Carron and A. Lewis)
• Wiener filtering of masked CMB data and allowing for inhomogenous noise, including lensing deflections, using a multigrid preconditioner.
  (Described in the same reference)
• Fast and accurate simulation libraries for lensed CMB skies, and standard quadratic estimator lensing reconstruction tools.
  (See https://arxiv.org/abs/1611.01446 by J. Peloton et al.)
• CMB internal delensing tools, including internal delensing biases calculation for temperature and/or polarization maps.
  (See https://arxiv.org/abs/1701.01712 by J. Carron, A. Lewis and A. Challinor)

Several parts were directly adapted from or inspired by qcinv (https://github.com/dhanson/qcinv) and quicklens (https://github.com/dhanson/quicklens) by Duncan Hanson, many thanks to him.

Many parts use the flat-sky approximation, with likely extension to curved-sky in a near future.
To use the GPU implementation of some of the routines, you will need pyCUDA. (https://mathema.tician.de/software/pycuda)

An ipython notebook 'demo_basics.ipynb' covers the simple aspects of building simulation librairies.

(New Sept. 2018) The notebook 'demo_lensit.ipynb' shows an example of iterative lensing map reconstruction for a configuration roughly in line with CMB Stage IV specifications.

(New May 2019) The notebook 'demo_curvlens.ipynb' shows how to generate a lensed CMB temperature map.

Other example and tests scripts might follow, or you may just write to me.