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The potential of likelihood-free inference of cosmological parameters with weak lensing data

Published online by Cambridge University Press:  01 July 2015

Michael Vespe*
Affiliation:
Department of Statistics, Carnegie Mellon University, Baker Hall 132, Pittsburgh, PA 15232 email: mvespe@andrew.cmu.edu
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Abstract

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In the statistical framework of likelihood-free inference, the posterior distribution of model parameters is explored via simulation rather than direct evaluation of the likelihood function, permitting inference in situations where this function is analytically intractable. We consider the problem of estimating cosmological parameters using measurements of the weak gravitational lensing of galaxies; specifically, we propose the use a likelihood-free approach to investigate the posterior distribution of some parameters in the ΛCDM model upon observing a large number of sheared galaxies. The choice of summary statistic used when comparing observed data and simulated data in the likelihood-free inference framework is critical, so we work toward a principled method of choosing the summary statistic, aiming for dimension reduction while seeking a statistic that is as close as possible to being sufficient for the parameters of interest.

Type
Contributed Papers
Copyright
Copyright © International Astronomical Union 2015 

References

Beaumont, M. A., Cornuet, J., Marin, J., & Robert, C. 2009, Biometrika, 96, 983CrossRefGoogle Scholar
Blum, M. G. B., Nunes, M. A., Prangle, D., & Sisson, S. A. 2012, arXiv:1202.3819Google Scholar
Cameron, E. & Pettitt, A. N. 2012, MNRAS, 425, 44CrossRefGoogle Scholar
Fearnhead, P. & Prangle, D. 2012, J. Roy. Stat. Soc. B Met., 74, 419Google Scholar
Heymans, C., Grocutt, E., Heavens, A., Kilbinger, M., et al. 2013, MNRAS, 432, 2433Google Scholar
Kiessling, A., Heavens, A. F., & Taylor, A. N. 2011, MNRAS, 414, 2235CrossRefGoogle Scholar
Lin, H., Dodelson, S., Seo, H., Soares-Santos, M., Annis, J., et al. 2012, ApJ, 761, 15Google Scholar
Pritchard, J. K., Seielstad, M. T., et al. 2012, Mol. Biol. Evol., 16, 1791Google Scholar
Weyant, A., Schafer, C., & Wood-Vasey, W. M. 2013, ApJ, 764, 116Google Scholar