Imperial College London
Alternate

ProfessorDanielMortlock

Faculty of Natural Sciences, Department of Physics

Professor of Astrophysics and Statistics
 
 
 
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Contact

 

+44 (0)20 7594 7878d.mortlock Website

 
 
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Location

 

1018ABlackett LaboratorySouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Argyle:2018:mnras/sty1691,
author = {Argyle, JJ and Mendez-Abreu, J and Wild, V and Mortlock, DJ},
doi = {mnras/sty1691},
journal = {Monthly Notices of the Royal Astronomical Society},
pages = {3076--3093},
title = {Bayesian bulge-disc decomposition of galaxy images},
url = {http://dx.doi.org/10.1093/mnras/sty1691},
volume = {479},
year = {2018}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - We introduce phi, a fully Bayesian Markov chain Monte Carlo algorithm designed for the structural decomposition of galaxy images. phi uses a triple layer approach to effectively and efficiently explore the complex parameter space. Combining this with the use of priors to prevent non-physical models, phi offers a number of significant advantages for estimating surface brightness profile parameters over traditional optimization algorithms. We apply phi to a sample of synthetic galaxies with Sloan Digital Sky Survey (SDSS)-like image properties to investigate the effect of galaxy properties on our ability to recover unbiased and well-constrained structural parameters. In two-component bulge+disc galaxies, we find that the bulge structural parameters are recovered less well than those of the disc, particularly when the bulge contributes a lower fraction to the luminosity, or is barely resolved with respect to the pixel scale or point spread function (PSF). There are few systematic biases, apart from for bulge+disc galaxies with large bulge Sérsic parameter, n. On application to SDSS images, we find good agreement with other codes, when run on the same images with the same masks, weights, and PSF. Again, we find that bulge parameters are the most difficult to constrain robustly. Finally, we explore the use of a Bayesian information criterion method for deciding whether a galaxy has one or two components.
AU  - Argyle,JJ
AU  - Mendez-Abreu,J
AU  - Wild,V
AU  - Mortlock,DJ
DO  - mnras/sty1691
EP  - 3093
PY  - 2018///
SN  - 0035-8711
SP  - 3076
TI  - Bayesian bulge-disc decomposition of galaxy images
T2  - Monthly Notices of the Royal Astronomical Society
UR  - http://dx.doi.org/10.1093/mnras/sty1691
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000441382300013&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - http://hdl.handle.net/10044/1/67121
VL  - 479
ER  -
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