arXiv · 2007.00716
Monte-Carlo Imaging for Optical Interferometry
Abstract
We present a flexible code created for imaging from the bispectrum and visibility-squared. By using a simulated annealing method, we limit the probability of converging to local chi-squared minima as can occur when traditional imaging methods are used on data sets with limited phase information. We present the results of our code used on a simulated data set utilizing a number of regularization schemes including maximum entropy. Using the statistical properties from Monte-Carlo Markov chains of images, we show how this code can place statistical limits on image features such as unseen binary companions.
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Michael J. Ireland, John D. Monnier, Nathalie Thureau. 2020-07-01. Monte-Carlo Imaging for Optical Interferometry. https://doi.org/10.1117/12.670940
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