Space Warps I. Crowd-sourcing the discovery of gravitational lenses

Philip J. Marshall, Aprajita Verma, Anupreeta More, Christopher P. Davis, Surhud More, Amit Kapadia, Michael Parrish, Chris Snyder, Julianne Wilcox, Elisabeth Baeten, Christine Macmillan, Claude Cornen, Michael Baumer, Edwin Simpson, Chris J. Lintott, David Miller, Edward Paget, Robert J. Simpson, Arfon M. Smith, Rafael KüngPrasenjit Saha, Thomas E. Collett, Matthias Tecza

Research output: Contribution to journalArticlepeer-review

126 Downloads (Pure)

Abstract

We describe Space Warps, 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 web- based 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 10$^5$ images could be performed by a crowd of 10$^5$ volunteers in 6 days.
Original languageEnglish
Pages (from-to)1171-1190
Number of pages20
JournalMonthly Notices of the Royal Astronomical Society
Volume455
Issue number2
DOIs
Publication statusPublished - 10 Nov 2015

Keywords

  • astro-ph.IM
  • astro-ph.CO
  • astro-ph.GA
  • gravitational lensing: strong
  • methods: statistical

Fingerprint

Dive into the research topics of 'Space Warps I. Crowd-sourcing the discovery of gravitational lenses'. Together they form a unique fingerprint.

Cite this