The Sloan Lens ACS Survey. XIII. Discovery of 40 New Galaxy-scale Strong Lenses^∗

Abstract

We present the full sample of 118 galaxy-scale strong-lens candidates in the Sloan Lens ACS (SLACS) Survey for the Masses (S4TM) Survey, which are spectroscopically selected from the final data release of the Sloan Digital Sky Survey. Follow-up Hubble Space Telescope (HST) imaging observations confirm that 40 candidates are definite strong lenses with multiple lensed images. The foreground-lens galaxies are found to be early-type galaxies (ETGs) at redshifts 0.06-0.44, and background sources are emission-line galaxies at redshifts 0.22-1.29. As an extension of the SLACS Survey, the S4TM Survey is the first attempt to preferentially search for strong-lens systems with relatively lower lens masses than those in the pre-existing strong-lens samples. By fitting HST data with a singular isothermal ellipsoid model, we find that the total projected mass within the Einstein radius of the S4TM strong-lens sample ranges from 3×1010 M e to 2×10 11 M e . In Shu et al., we have derived the total stellar mass of the S4TM lenses to be 5×1010 M e to 1×10 12 M e . Both the total enclosed mass and stellar mass of the S4TM lenses are on average almost a factor of 2 smaller than those of the SLACS lenses, which also represent the typical mass scales of the current strong-lens samples. The extended mass coverage provided by the S4TM sample can enable a direct test, with the aid of strong lensing, for transitions in scaling relations, kinematic properties, mass structure, and dark-matter content trends of ETGs at intermediate-mass scales as noted in previous studies.

The use of convolutional neural networks for modelling large optically-selected strong galaxy-lens samples

“…Likewise, velocity dispersions were selected from a normal distribution with mean 250 and standard deviation of 44 km s −1 based on results from SLACS papers (e.g. Shu et al 2017). These were then used to determine lens Einstein radii which along with effective radii were In total there are six convolutional layers, each with batch normalisation, four max-pooling layers and two fully connected layers.…”

Probing cosmic acceleration by strong gravitational lensing systems

“…These 10 systems are excluded in order to get rid of some unknown systematic errors imported by any model fitting effect. 27 SLACS data are chosen from 40 grade-A lenses listed in Shu et al (2017). In their work, a parameter χ 2 /do f is achieved, which represents the goodness of fitting for SIE model.…”

LinKS: discovering galaxy-scale strong lenses in the Kilo-Degree Survey using convolutional neural networks

“…The largest homogeneously-selected sample of confirmed strong lenses is the Sloan Lens ACS Survey (SLACS; Bolton et al 2006Bolton et al , 2008, which yielded more than a hundred spectroscopically confirmed strong lenses with complete redshift information and high-resolution imaging follow-up (with e.g., the Hubble Space Telescope and Keck Observatory Adaptive Optics). In total, all lens surveys combined have produced up to a thousand highly-likely 2 gravitational lens candidates (e.g., Browne et al 2003;Faure et al 2008;Treu et al 2011;Inada et al 2012;Brownstein et al 2012;More et al 2012;Stark et al 2013;Sonnenfeld et al 2013a;Gavazzi et al 2014;More et al 2016;Shu et al 2016Shu et al , 2017.…”