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

A5e5f24da39ad8290bbf1ca6822cd21e?s=47 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.

A5e5f24da39ad8290bbf1ca6822cd21e?s=128

Kyle Willett

October 20, 2015
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  1. Radio Galaxy Zoo Kyle Willett University of Minnesota @kwwillett

  2. Identification of the host galaxy for radio sources is critical

    Banfield et al. (2015) (e)
  3. 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)
  4. 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!
  5. 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
  6. Expert visual classification ~7,000 sources Proctor (2011) Dozens of potential

    categories
  7. • 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
  8. • 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
  9. None
  10. None
  11. Data products Banfield et al. (2015)

  12. RGZ catalog Willett et al. (in prep)

  13. 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)
  14. 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)
  15. Science - identification of hybrid radio galaxies Kapińska et al.

    (submitted)
  16. Jet bending angles ~ v ICM

  17. Intercluster medium Dehghan+14 Indicators of ICM pressure, dynamical state, merger

    history, etc. ⇢ICMv2 gal h = w 2 2 R
  18. Comparing the observations to simulations Mendygral & Jones (in prep)

    131.3 Myr Mendygral+12 100 kpc 196.8 Myr
  19. Sharply-bent radio galaxies from RGZ Rudnick et al. (in prep)

  20. Bending angles of radio jets near galaxy clusters Rudnick, Willett,

    Garon et al. (in prep)
  21. 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.
  22. 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 ?
  23. Grazie. willett@physics.umn.edu Work supported by NSF AST 12-11295 radio.galaxyzoo.org