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