Aprajita Verma

Abstract:

We present source counts at 6.7 and 15 μm from our maps of the Hubble Deep Field (HDF) region, reaching 38.6 μJy at 6.7 μm and 255 μJy at 15 μm. These are the first ever extragalactic number counts to be presented at 6.7 μm, and are three decades fainter than IRAS at 12 μm. Both source counts and a P(D) analysis suggest that we have reached the Infrared Space Obsen'atory (ISO) confusion limit at 15 μm: this will have important implications for future space missions. These data provide an excellent reference point for other ongoing ISO surveys. A no-evolution model at 15 μm is ruled out at > 3σ, while two models which fit the steep IRAS 60-μm counts are acceptable. This provides important confirmation of the strong evolution seen in IRAS surveys. One of these models can then be ruled out from the 6.7-μm data. © 1997 RAS.

Abstract:

Strong lenses are extremely useful probes of the distribution of matter on galaxy and cluster scales at cosmological distances, but are rare and difficult to find. The number of currently known lenses is on the order of 1,000. We wish to use crowdsourcing to carry out a lens search targeting massive galaxies selected from over 442 square degrees of photometric data from the Hyper Suprime-Cam (HSC) survey. We selected a sample of $\sim300,000$ galaxies with photometric redshifts in the range $0.2 < z_{phot} < 1.2$ and photometrically inferred stellar masses $\log{M_*} > 11.2$. We crowdsourced lens finding on this sample of galaxies on the Zooniverse platform, as part of the Space Warps project. The sample was complemented by a large set of simulated lenses and visually selected non-lenses, for training purposes. Nearly 6,000 citizen volunteers participated in the experiment. In parallel, we used YattaLens, an automated lens finding algorithm, to look for lenses in the same sample of galaxies. Based on a statistical analysis of classification data from the volunteers, we selected a sample of the most promising $\sim1,500$ candidates which we then visually inspected: half of them turned out to be possible (grade C) lenses or better. Including lenses found by YattaLens or serendipitously noticed in the discussion section of the Space Warps website, we were able to find 14 definite lenses, 129 probable lenses and 581 possible lenses. YattaLens found half the number of lenses discovered via crowdsourcing. Crowdsourcing is able to produce samples of lens candidates with high completeness and purity, compared to currently available automated algorithms. A hybrid approach, in which the visual inspection of samples of lens candidates pre-selected by discovery algorithms and/or coupled to machine learning is crowdsourced, will be a viable option for lens finding in the 2020s.