Astrophysical data analysis with information field theory
Abstract
Non-parametric imaging and data analysis in astrophysics and cosmology can be addressed by information field theory (IFT), a means of Bayesian, data based inference on spatially distributed signal fields. IFT is a statistical field theory, which permits the construction of optimal signal recovery algorithms. It exploits spatial correlations of the signal fields even for nonlinear and non-Gaussian signal inference problems. The alleviation of a perception threshold for recovering signals of unknown correlation structure by using IFT will be discussed in particular as well as a novel improvement on instrumental self-calibration schemes. IFT can be applied to many areas. Here, applications in in cosmology (cosmic microwave background, large-scale structure) and astrophysics (galactic magnetism, radio interferometry) are presented.
Cite
@article{arxiv.1405.7701,
title = {Astrophysical data analysis with information field theory},
author = {Torsten Enßlin},
journal= {arXiv preprint arXiv:1405.7701},
year = {2015}
}
Comments
4 pages, 2 figures, accepted chapter to the conference proceedings for MaxEnt 2013, to be published by AIP