Space Warps – I. Crowdsourcing the discovery of gravitational lenses
2016
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.
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