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Radio Galaxy Zoo: host galaxies and radio morph...

Kyle Willett
October 20, 2015

Radio Galaxy Zoo: host galaxies and radio morphologies for large surveys from visual inspection

Contributed talk given at the conference "The Many Facets of Radio Extragalactic Surveys: Towards New Scientific Challenges". Bologna, Italy, 20-23 Oct 2015.

Kyle Willett

October 20, 2015
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  1. Automated routines Lcll = Z dm p(m)Lc(m)Lr0 (m) Z dm0p(m0|m)Lr1

    (m0)Lr2 (2m m0) Bayesian hypothesis testing B1,2 = L1 L2 m00 = 2m m0 Model Evaluate Likelihood Fan et al. (2015)
  2. Automated routines Lcll = Z dm p(m)Lc(m)Lr0 (m) Z dm0p(m0|m)Lr1

    (m0)Lr2 (2m m0) Bayesian hypothesis testing B1,2 = L1 L2 m00 = 2m m0 Model Evaluate Likelihood Fan et al. (2015) success!
  3. m00 = 2m m0 + k(m m0) k Lcll =

    Z dm p(m)Lc(m)Lr0 (m) Z dm0p(m0|m Lcll = Z dm p(m)Lc(m)Lr0 (m) Z dm0p(m0|m)Lr1 (m0)Lr2 (2m m0 + k(m m0) ⇥ k Fan et al. (2015) failure Automated routines
  4. • Goal: identify multi-component radio sources and cross-match to host

    galaxy • Data: • Radio: FIRST and ATLAS • Infrared: WISE and SWIRE • Since launch in Dec 2013: • > 8,000 individual participants • 1.3 million classifications • 76,000 completed images (45% of total) Radio Galaxy Zoo
  5. • Goal: identify multi-component radio sources and cross-match to host

    galaxy • Data: • Radio: FIRST and ATLAS • Infrared: WISE and SWIRE • Since launch in Dec 2013: • > 8,000 individual participants • 1.3 million classifications • 76,000 completed images (45% of total) Radio Galaxy Zoo
  6. Science - WISE colors of radio hosts (b) cool T-dwarfs

    (W2 - W3) (W1 - W2) 3.0 2.0 1.0 0.0 (a) (W2 - W3) (W1 - W2) 3.0 2.0 1.0 0.0 2.5 1.5 0.5 -0.5 -1.0 WISE all-sky sources Banfield et al. (2015) RGZ sources PRGs (Gurkan+14)
  7. Science - WISE colors of radio hosts (b) cool T-dwarfs

    (W2 - W3) (W1 - W2) 3.0 2.0 1.0 0.0 (a) (W2 - W3) (W1 - W2) 3.0 2.0 1.0 0.0 2.5 1.5 0.5 -0.5 -1.0 WISE all-sky sources Banfield et al. (2015) RGZ sources PRGs (Gurkan+14)
  8. Citizen science is a good thing for radio astronomy 1.

    The data sets are already too large for science teams to individually inspect, and they’re about to get much larger. 2. There is useful science to be extracted from tasks that non-professionals can perform. 3. More inspection of the data enables serendipitous discoveries. 4. Citizen science has massive additional benefits in engagement, outreach, and education.
  9. What is the future of citizen science in radio astronomy?

    rare and unusual detailed analysis of radio sources new surveys time domain/ multi-frequency training sets for machine learning ?