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Dark census: Statistically detecting the satellite populations of distant galaxies

Cyr-Racine, Francis-Yan and Moustakas, Leonidas A. and Keeton, Charles R. and Sigurdson, Kris and Gilman, Daniel A. (2016) Dark census: Statistically detecting the satellite populations of distant galaxies. Physical Review D, 94 (4). Art. No. 043505. ISSN 2470-0010. http://resolver.caltech.edu/CaltechAUTHORS:20160808-115817446

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Abstract

In the standard structure formation scenario based on the cold dark matter paradigm, galactic halos are predicted to contain a large population of dark matter subhalos. While the most massive members of the subhalo population can appear as luminous satellites and be detected in optical surveys, establishing the existence of the low mass and mostly dark subhalos has proven to be a daunting task. Galaxy-scale strong gravitational lenses have been successfully used to study mass substructures lying close to lensed images of bright background sources. However, in typical galaxy-scale lenses, the strong lensing region only covers a small projected area of the lens’s dark matter halo, implying that the vast majority of subhalos cannot be directly detected in lensing observations. In this paper, we point out that this large population of dark satellites can collectively affect gravitational lensing observables, hence possibly allowing their statistical detection. Focusing on the region of the galactic halo outside the strong lensing area, we compute from first principles the statistical properties of perturbations to the gravitational time delay and position of lensed images in the presence of a mass substructure population. We find that in the standard cosmological scenario, the statistics of these lensing observables are well approximated by Gaussian distributions. The formalism developed as part of this calculation is very general and can be applied to any halo geometry and choice of subhalo mass function. Our results significantly reduce the computational cost of including a large substructure population in lens models and enable the use of Bayesian inference techniques to detect and characterize the distributed satellite population of distant lens galaxies.


Item Type:Article
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1103/PhysRevD.94.043505DOIArticle
http://journals.aps.org/prd/abstract/10.1103/PhysRevD.94.043505PublisherArticle
http://arxiv.org/abs/1506.01724arXivDiscussion Paper
ORCID:
AuthorORCID
Sigurdson, Kris0000-0002-6729-0765
Additional Information:© 2016 American Physical Society. (Received 18 June 2015; published 5 August 2016) We thank Geoffrey Bryden, James Bullock, Curt Cutler, Olivier Doré, David Hogg, Jeffrey Jewel, James Taylor, and Michele Vallisneri for useful conversations. The work of F.-Y. C.-R. was performed in part at the California Institute of Technology for the Keck Institute for Space Studies, which is funded by the W. M. Keck Foundation. F.-Y. C.-R. thanks the Aspen Center for Physics, where some of this work was performed. The Aspen Center for Physics is supported by the National Science Foundation under Grant No. 1066293. Part of the research described in this paper was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (NASA). L. A. M. gratefully acknowledges support by the NASA ATFP program through Award No. 399131.02.02.02.98. C. R. K. acknowledges support from the National Science Foundation under Grant No. AST-0747311. The research of K. S. is supported in part by a Natural Science and Engineering Research Council (NSERC) of Canada Discovery Grant. D. A. G. acknowledges the support of the NASA Undergraduate Internship and Student Internship programs.
Group:Keck Institute for Space Studies
Funders:
Funding AgencyGrant Number
Keck Institute for Space Studies (KISS)UNSPECIFIED
W. M. Keck FoundationUNSPECIFIED
NSFPHY-1066293
NASA/JPL/CaltechUNSPECIFIED
NASA399131.02.02.02.98
NSFAST-0747311
Natural Sciences and Engineering Research Council of Canada (NSERC)UNSPECIFIED
NASA Undergraduate Student Research ProgramUNSPECIFIED
Record Number:CaltechAUTHORS:20160808-115817446
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20160808-115817446
Official Citation:Dark census: Statistically detecting the satellite populations of distant galaxies Francis-Yan Cyr-Racine, Leonidas A. Moustakas, Charles R. Keeton, Kris Sigurdson, and Daniel A. Gilman Phys. Rev. D 94, 043505
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:69505
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:09 Aug 2016 14:36
Last Modified:04 May 2017 19:38

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