Zooniverse

Abstract:

We discuss a potential MeerKAT campaign to shed more light into the nature of the optically identified Blue Early Type galaxies (BETGs), a subset of the so-called "green valley" population, quenching star formation on time scales of less than 0.25 Gyr and the likely progenitor population of post-starburst galaxies. Employing a WSRT pilot survey of four galaxies, we have shown that BETGs have radio properties that fit to a mechanical removal of star forming material, potentially by AGN activity, as in particular we found H I to be removed farther and farther from the centre of the galaxies with older and older age of the stellar population. We argue that MeerKAT is the optimal instrument to conduct a pointed survey of BETGs to become more conclusive about this specific transition state, which is so rare that it will not be detected at a high enough rate in planned sufficiently sensitive large-sky surveys, for which we expect a total detection number of the order of 12 objects.

Abstract:

We present deep Chandra X-ray observations of the core of IC 2497, the galaxy associated with Hanny's Voorwerp and hosting a fading AGN. We find extended soft X-ray emission from hot gas around the low intrinsic luminosity (unobscured) AGN ($L_{\rm bol} \sim 10^{42}-10^{44}$ erg s$^{-1}$). The temperature structure in the hot gas suggests the presence of a bubble or cavity around the fading AGN ($\mbox{E$_{\rm bub}$} \sim 10^{54} - 10^{55}$ erg). A possible scenario is that this bubble is inflated by the fading AGN, which after changing accretion state is now in a kinetic mode. Other possibilities are that the bubble has been inflated by the past luminous quasar ($L_{\rm bol} \sim 10^{46}$ erg s$^{-1}$), or that the temperature gradient is an indication of a shock front from a superwind driven by the AGN. We discuss the possible scenarios and the implications for the AGN-host galaxy interaction, as well as an analogy between AGN and X-ray binaries lifecycles. We conclude that the AGN could inject mechanical energy into the host galaxy at the end of its lifecycle, and thus provide a source for mechanical feedback, in a similar way as observed for X-ray binaries.

Abstract:

We report the discovery of 29 promising (and 59 total) new lens candidates from the CFHT Legacy Survey (CFHTLS) based on about 11 million classifications performed by citizen scientists as part of the first Space Warps lens search. The goal of the blind lens search was to identify lens candidates missed by robots (the RingFinder on galaxy scales and ArcFinder on group/cluster scales) which had been previously used to mine the CFHTLS for lenses. We compare some properties of the samples detected by these algorithms to the Space Warps sample and find them to be broadly similar. The image separation distribution calculated from the Space Warps sample shows that previous constraints on the average density profile of lens galaxies are robust. SpaceWarps recovers about 65% of known lenses, while the new candidates show a richer variety compared to those found by the two robots. This detection rate could be increased to 80% by only using classifications performed by expert volunteers (albeit at the cost of a lower purity), indicating that the training and performance calibration of the citizen scientists is very important for the success of Space Warps. In this work we present the SIMCT pipeline, used for generating in situ a sample of realistic simulated lensed images. This training sample, along with the false positives identified during the search, has a legacy value for testing future lens finding algorithms. We make the pipeline and the training set publicly available.

Abstract:

We describe SpaceWarps, a novel gravitational lens discovery service that yields samples of high purity and completeness through crowd-sourced visual inspection. Carefully produced colour composite images are displayed to volunteers via a webbased classification interface, which records their estimates of the positions of candidate lensed features. Images of simulated lenses, as well as real images which lack lenses, are inserted into the image stream at random intervals; this training set is used to give the volunteers instantaneous feedback on their performance, as well as to calibrate a model of the system that provides dynamical updates to the probability that a classified image contains a lens. Low probability systems are retired from the site periodically, concentrating the sample towards a set of lens candidates. Having divided 160 square degrees of Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) imaging into some 430,000 overlapping 82 by 82 arcsecond tiles and displaying them on the site, we were joined by around 37,000 volunteers who contributed 11 million image classifications over the course of 8 months. This Stage 1 search reduced the sample to 3381 images containing candidates; these were then refined in Stage 2 to yield a sample that we expect to be over 90% complete and 30% pure, based on our analysis of the volunteers performance on training images. We comment on the scalability of the SpaceWarps system to the wide field survey era, based on our projection that searches of 105 images could be performed by a crowd of 105 volunteers in 6 days.