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Register a new userGalaxy And Mass Assembly: A Comparison between Galaxy-Galaxy Lens Searches in KiDS/GAMA
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Shawn Knabel
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Strong gravitational lenses are a rare and instructive type of astronomical object. Identification has long relied on serendipity, but different strategies -- such as mixed spectroscopy of multiple galaxies along the line of sight, machine learning algorithms, and citizen science -- have been employed to identify these objects as new imaging surveys become available. We report on the comparison between spectroscopic, machine learning, and citizen science identification of galaxy-galaxy lens candidates from independently constructed lens catalogs in the common survey area of the equatorial fields of the GAMA survey. In these, we have the opportunity to compare high-completeness spectroscopic identifications against high-fidelity imaging from the Kilo Degree Survey (KiDS) used for both machine learning and citizen science lens searches. We find that the three methods -- spectroscopy, machine learning, and citizen science -- identify 47, 47, and 13 candidates respectively in the 180 square degrees surveyed. These identifications barely overlap, with only two identified by both citizen science and machine learning. We have traced this discrepancy to inherent differences in the selection functions of each of the three methods, either within their parent samples (i.e. citizen science focuses on low-redshift) or inherent to the method (i.e. machine learning is limited by its training sample and prefers well-separated features, while spectroscopy requires sufficient flux from lensed features to lie within the fiber). These differences manifest as separate samples in estimated Einstein radius, lens stellar mass, and lens redshift. The combined sample implies a lens candidate sky-density $sim0.59$ deg$^{-2}$ and can inform the construction of a training set spanning a wider mass-redshift space.
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The Galaxy And Mass Assembly Survey (GAMA) covers five fields with highly complete spectroscopic coverage ($>95$ per cent) to intermediate depths ($r<19.8$ or $i < 19.0$ mag), and collectively spans 250 square degrees of Equatorial or Southern sky. Four of the GAMA fields (G09, G12, G15 and G23) reside in the ESO VST KiDS and ESO VISTA VIKING survey footprints, which combined with our GALEX, WISE and Herschel data provide deep uniform imaging in the $FUV,NUV,ugriZYJHK_s,W1,W2,W3,W4,P100,P160,S250,S350,S500$ bands. Following the release of KiDS DR4, we describe the process by which we ingest the KiDS data into GAMA (replacing the SDSS data previously used for G09, G12 and G15), and redefine our core optical and near-IR catalogues to provide a complete and homogeneous dataset. The source extraction and analysis is based on the new ProFound image analysis package, providing matched-segment photometry across all bands. The data are classified into stars, galaxies, artefacts, and ambiguous objects, and objects are linked to the GAMA spectroscopic target catalogue. Additionally, a new technique is employed utilising ProFound to extract photometry in the unresolved MIR-FIR regime. The catalogues including the full FUV-FIR photometry are described and will be fully available as part of GAMA DR4. They are intended for both standalone science, selection for targeted follow-up with 4MOST, as well as an accompaniment to the upcoming and ongoing radio arrays now studying the GAMA $23^h$ field.
We present the catalogue of blended galaxy spectra from the Galaxy And Mass Assembly (GAMA) survey. These are cases where light from two galaxies are significantly detected in a single GAMA fibre. Galaxy pairs identified from their blended spectrum fall into two principal classes: they are either strong lenses, a passive galaxy lensing an emission-line galaxy; or occulting galaxies, serendipitous overlaps of two galaxies, of any type. Blended spectra can thus be used to reliably identify strong lenses for follow-up observations (high resolution imaging) and occulting pairs, especially those that are a late-type partly obscuring an early-type galaxy which are of interest for the study of dust content of spiral and irregular galaxies. The GAMA survey setup and its autoz automated redshift determination were used to identify candidate blended galaxy spectra from the cross-correlation peaks. We identify 280 blended spectra with a minimum velocity separation of 600 km/s, of which 104 are lens pair candidates, 71 emission-line-passive pairs, 78 are pairs of emission-line galaxies and and 27 are pairs of galaxies with passive spectra. We have visually inspected the candidates in the Sloan Digital Sky Survey (SDSS) and Kilo Degree Survey (KiDS) images. Many blended objects are ellipticals with blue fuzz (Ef in our classification). These latter Ef classifications are candidates for possible strong lenses, massive ellipticals with an emission-line galaxy in one or more lensed images. The GAMA lens and occulting galaxy candidate samples are similar in size to those identified in the entire SDSS. This blended spectrum sample stands as a testament of the power of this highly complete, second-largest spectroscopic survey in existence and offers the possibility to expand e.g., strong gravitational lens surveys.
We measure the projected 2-point correlation function of galaxies in the 180 deg$^2$ equatorial regions of the GAMA II survey, for four different redshift slices between z = 0.0 and z=0.5. To do this we further develop the Cole (2011) method of producing suitable random catalogues for the calculation of correlation functions. We find that more r-band luminous, more massive and redder galaxies are more clustered. We also find that red galaxies have stronger clustering on scales less than ~3 $h^{-1}$ Mpc. We compare to two differe
We study the star formation rate (SFR), stellar mass ($M_{star}$) and the gas metallicity (Z) for 4,636 galaxy pairs using the Galaxy And Mass Assembly (GAMA) survey. Our galaxy pairs lie in a redshift range of 0 $<$ $z$ $<$ 0.35, mass range of 7.5 $<$ log( M$_{star}$/ M$_odot$) $<$ 11.5 and $Delta V$ $<$ 1000 km s$^{-1}$. We explore variations in SFR and Z from three point of views: multiplicity, pair separation and dynamics. We define multiplicity as the number of galaxies paired with a single galaxy, and analyzed for the first time variations in SFR and Z for both, single pairs and pairs with higher multiplicity. For the latter, we find SFR enhancements from 0.025-0.15 dex, that would shift the M-SFR relation of single pairs by 27$%$ to higher SFRs. The effect of Z on the other hand, is of only 4$%$. We analyze the most and least massive galaxy of major/minor pairs as a function of the pair separation. We define major pairs those with mass ratios of 0.5 $<$ $M_1$/$M_2$ $<$ 2, while pairs with more discrepant mass ratios are classified as minor pairs. We find SFR enhancements of up to 2 and 4 times with respect to their control sample, for major and minor pairs. For the case of Z, we find decrements of up to 0.08 dex for the closest pairs. When we focus on dynamics, Z enhancements are found for minor pairs with high velocity dispersion $(sigma_p > 250 ; mathrm{km,s ^{-1}})$ and high multiplicity.
We explore the clustering of galaxy groups in the Galaxy and Mass Assembly (GAMA) survey to investigate the dependence of group bias and profile on separation scale and group mass. Due to the inherent uncertainty in estimating the group selection function, and hence the group auto-correlation function, we instead measure the projected galaxy--group cross-correlation function. We find that the group profile has a strong dependence on scale and group mass on scales $r_bot lesssim 1 h^{-1} mathrm{Mpc}$. We also find evidence that the most massive groups live in extended, overdense, structures. In the first application of marked clustering statistics to groups, we find that group-mass marked clustering peaks on scales comparable to the typical group radius of $r_bot approx 0.5 h^{-1} mathrm{Mpc}$. While massive galaxies are associated with massive groups, the marked statistics show no indication of galaxy mass segregation within groups. We show similar results from the IllustrisTNG simulations and the L-Galaxies model, although L-Galaxies shows an enhanced bias and galaxy mass dependence on small scales.
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