Space Warps: I. Crowd-sourcing the discovery of gravitational lenses
| Autor: | David Miller, Chris Snyder, Rafael Küng, Edward Paget, Anupreeta More, Christine Macmillan, Arfon M. Smith, Philip J. Marshall, Claude Cornen, Edwin Simpson, M. Baumer, Thomas E. Collett, Aprajita Verma, Prasenjit Saha, Amit Kapadia, Chris Lintott, Elisabeth Baeten, Julianne K. Wilcox, R. Simpson, Michael Parrish, Christopher P. Davis, Surhud More |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
Cosmology and Nongalactic Astrophysics (astro-ph.CO)
astro-ph.GA statistical [methods] FOS: Physical sciences Crowdsourcing 01 natural sciences law.invention Telescope Set (abstract data type) Optics law 0103 physical sciences Computer vision Projection (set theory) 010303 astronomy & astrophysics Instrumentation and Methods for Astrophysics (astro-ph.IM) Physics 010308 nuclear & particles physics business.industry Astronomy and Astrophysics Real image Astrophysics - Astrophysics of Galaxies Sample (graphics) Lens (optics) Gravitational lens Space and Planetary Science strong [gravitational lensing] Astrophysics of Galaxies (astro-ph.GA) astro-ph.CO Artificial intelligence Astrophysics - Instrumentation and Methods for Astrophysics business Astrophysics - Cosmology and Nongalactic Astrophysics astro-ph.IM |
| Zdroj: | Marshall, P J, Verma, A, More, A, Davis, C P, More, S, Kapadia, A, Parrish, M, Snyder, C, Wilcox, J, Baeten, E, Macmillan, C, Cornen, C, Baumer, M, Simpson, E, Lintott, C J, Miller, D, Paget, E, Simpson, R J, Smith, A M, Küng, R, Saha, P, Collett, T E & Tecza, M 2015, ' Space Warps I. Crowd-sourcing the discovery of gravitational lenses ', Monthly Notices of the Royal Astronomical Society, vol. 455, no. 2, pp. 1171-1190 . https://doi.org/10.1093/mnras/stv2009 |
| ISSN: | 1365-2966 0035-8711 |
| DOI: | 10.1093/mnras/stv2009 |
| Popis: | 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. Comment: 21 pages, 13 figures, MNRAS accepted, minor to moderate changes in this version |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|