SIMBAD references

2017MNRAS.467.3970G - Mon. Not. R. Astron. Soc., 467, 3970-3992 (2017/June-1)

Strong lensing signatures of luminous structure and substructure in early-type galaxies.


Abstract (from CDS):

The arrival times, positions and fluxes of multiple images in strong lens systems can be used to infer the presence of dark subhaloes in the deflector, and thus test predictions of cold dark matter models. However, gravitational lensing does not distinguish between perturbations to a smooth gravitational potential arising from baryonic and non-baryonic mass. In this work, we quantify the extent to which the stellar mass distribution of a deflector can reproduce flux ratio and astrometric anomalies typically associated with the presence of a dark matter subhalo. Using Hubble Space Telescope images of nearby galaxies, we simulate strong lens systems with real distributions of stellar mass as they would be observed at redshift zd = 0.5. We add a dark matter halo and external shear to account for the smooth dark matter field, omitting dark substructure, and use a Monte Carlo procedure to characterize the distributions of image positions, time delays and flux ratios for a compact background source of diameter 5 pc. By convolving high-resolution images of real galaxies with a Gaussian point spread function, we simulate the most detailed smooth potential one could construct given high-quality data, and find scatter in flux ratios of ≃10 per cent, which we interpret as a typical deviation from a smooth potential caused by large- and small-scale structure in the lensing galaxy. We demonstrate that the flux ratio anomalies arising from galaxy-scale baryonic structure can be minimized by selecting the most massive and round deflectors and by simultaneously modelling flux ratio and astrometric data.

Abstract Copyright: © 2017 The Authors Published by Oxford University Press on behalf of the Royal Astronomical Society

Journal keyword(s): gravitational lensing: strong - galaxies: structure - galaxies: structure

Simbad objects: 34

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