Stellar masses calibrated with micro-lensed quasars

Schechter, Paul L.; Blackburne, Jeffrey A.; Pooley, David; Wambsganß, J.

doi:10.1017/s1743921315003464

Cited by 3 publications

(3 citation statements)

References 10 publications

(13 reference statements)

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“…The magnification of SNe from stars is studied in (53), where it is found that ∼ 70 % of multiple lensed SNe will experience additional magnification from the lens galaxy star population of > 0.5 mag. The case of lensed quasars is studied in, e.g (54).…”

Section: Modelling Of the Gravitational Lensmentioning

confidence: 99%

iPTF16geu: A multiply imaged, gravitationally lensed type Ia supernova

Goobar

Amanullah

Kulkarni

et al. 2017

Science

230

232

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We report the discovery of a multiply-imaged gravitationally lensed Type Ia supernova, iPTF16geu (SN 2016geu), at redshift $z=0.409$. This phenomenon could be identified because the light from the stellar explosion was magnified more than fifty times by the curvature of space around matter in an intervening galaxy. We used high spatial resolution observations to resolve four images of the lensed supernova, approximately 0.3" from the center of the foreground galaxy. The observations probe a physical scale of $\sim$1 kiloparsec, smaller than what is typical in other studies of extragalactic gravitational lensing. The large magnification and symmetric image configuration implies close alignment between the line-of-sight to the supernova and the lens. The relative magnifications of the four images provide evidence for sub-structures in the lensing galaxy.Comment: Matches published versio

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Section: Modelling Of the Gravitational Lensmentioning

confidence: 99%

iPTF16geu: A multiply imaged, gravitationally lensed type Ia supernova

Goobar

Amanullah

Kulkarni

et al. 2017

Science

230

232

View full text Add to dashboard Cite

show abstract

“…Strong gravitational lenses have been used extensively to study the structure and late (z < 1) evolution of massive galaxies, both through the detailed study of a small number of systems (see e.g. Sonnenfeld et al 2012;Barnabè et al 2013;Smith et al 2015;Collett et al 2018;Schuldt et al 2019) and with the statistical combination of tens of objects (Auger et al 2010;Bolton et al 2012;Schechter et al 2014;Oguri et al 2014;Sonnenfeld et al 2015;Oldham & Auger 2018). However, strong lenses are rare systems, and dedicated follow-up observations are usually required to confirm their nature and to obtain all of the necessary information for a successful analysis.…”

Section: Introductionmentioning

confidence: 99%

Statistical strong lensing

Sonnenfeld

2022

A&A

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Context. Existing samples of strong lenses have been assembled by giving priority to sample size, but this is often at the cost of a complex selection function. However, with the advent of the next generation of wide-field photometric surveys, it might become possible to identify subsets of the lens population with well-defined selection criteria, trading sample size for completeness. Aims. There are two main advantages of working with a complete sample of lenses. First, such completeness makes possible to recover the properties of the general population of galaxies, of which strong lenses are a biased subset. Second, the relative number of lenses and non-detections can be used to further constrain models of galaxy structure. The present work illustrates how to carry out a statistical strong lensing analysis that takes advantage of these features. Methods. I introduce a general formalism for the statistical analysis of a sample of strong lenses with known selection function, and then test it on simulated data. The simulation consists of a population of 105 galaxies with an axisymmetric power-law density profile, a population of background point sources, and a subset of ∼103 strong lenses, which form a complete sample above an observational cut. Results. The method allows the user to recover the distribution of the galaxy population in Einstein radius and mass density slope in an unbiased way. The number of non-lenses helps to constrain the model when magnification data are not available. Conclusions. Complete samples of lenses are a powerful asset with which to turn precise strong lensing measurements into accurate statements on the properties of the general galaxy population.

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“…Under that assumption, the problem reduces to the determination of a handful of parameters describing the average of the distribution and possible scaling relations between the mass parameters of each lens and some galaxy properties (see, e.g. Rusin & Kochanek 2005;Grillo 2012;Oguri et al 2014;Schechter et al 2014). A more general method for inferring the statistical properties of an ensemble of lenses is hierarchical modelling, in which lenses are still assumed to be drawn from a common distribution to be inferred from the data, but where the parameters describing individual objects are allowed to vary independently of each other (see Sonnenfeld et al 2015Sonnenfeld et al , 2019aBirrer et al 2020;Shajib et al 2021).…”

Section: Introductionmentioning

confidence: 99%

Statistical strong lensing

Sonnenfeld

Cautun

2021

A&A

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Context. The number of known strong gravitational lenses is expected to grow substantially in the next few years. The combination of large samples of lenses has the potential to provide strong constraints on the inner structure of galaxies. Aims. We investigate the extent to which we can calibrate stellar mass measurements and constrain the average dark matter density profile of galaxies by combining strong lensing data from thousands of lenses. Methods. We generated mock samples of axisymmetric lenses. We assume that, for each lens, we have measurements of two image positions of a strongly lensed background source, as well as magnification information from full surface brightness modelling, and a stellar-population-synthesis-based estimate of the lens stellar mass. We then fitted models describing the distribution of the stellar population synthesis mismatch parameter αsps (the ratio between the true stellar mass and the stellar-population-synthesis-based estimate) and the dark matter density profile of the population of lenses to an ensemble of 1000 mock lenses. Results. We obtain the average αsps, projected dark matter mass, and dark matter density slope with greater precision and accuracy compared with current constraints. A flexible model and knowledge of the lens detection efficiency as a function of image configuration are required in order to avoid a biased inference. Conclusions. Statistical strong lensing inferences from upcoming surveys provide a way to calibrate stellar mass measurements and to constrain the inner dark matter density profile of massive galaxies.

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Stellar masses calibrated with micro-lensed quasars

Cited by 3 publications

References 10 publications

iPTF16geu: A multiply imaged, gravitationally lensed type Ia supernova

iPTF16geu: A multiply imaged, gravitationally lensed type Ia supernova

Statistical strong lensing

Statistical strong lensing

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