Monte-carlo imaging for optical interferometry

Michael J. Ireland; John D. Monnier; Nathalie Thureau

doi:10.1117/12.670940

Monte-carlo imaging for optical interferometry

Michael J. Ireland^*, John D. Monnier, Nathalie Thureau

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

51 Citations (Scopus)

Abstract

We present a flexible code created for imaging from the bispectrum and V². 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.

Original language	English
Title of host publication	Advances in Stellar Interferometry
Editors	John D. Monnier, Markus Schöller, William C. Danchi
Place of Publication	Bellingham, WA
Publisher	SPIE
Pages	1-8
Number of pages	8
ISBN (Print)	0819463337, 9780819463333
DOIs	https://doi.org/10.1117/12.670940
Publication status	Published - Jun 2006
Externally published	Yes
Event	Advances in Stellar Interferometry - Orlando, FL, United States Duration: 25 May 2006 → 30 May 2006

Publication series

Name	Proc. of SPIE
Publisher	SPIE
Volume	6268

Other

Other	Advances in Stellar Interferometry
Country	United States
City	Orlando, FL
Period	25/05/06 → 30/05/06

Keywords

Aperture synthesis imaging
Astronomical software
Bayesian statistics
Optical interferometry

Access to Document

10.1117/12.670940

Link to publication in Scopus

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Cite this

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title = "Monte-carlo imaging for optical interferometry",

abstract = "We present a flexible code created for imaging from the bispectrum and V2. 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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Monte-carlo imaging for optical interferometry. / Ireland, Michael J.; Monnier, John D.; Thureau, Nathalie.

Advances in Stellar Interferometry. ed. / John D. Monnier; Markus Schöller; William C. Danchi. Bellingham, WA : SPIE, 2006. p. 1-8 62681T (Proc. of SPIE; Vol. 6268).

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

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