1. Eyeballs and automation in pursuit of moons (and limiting magnitudes) Max Mutchler Research & Instrument Scientist Space Telescope Science Institute Nix & Hydra 5th Anniversary Workshop May 11-12, 2010

2. Overview Currently have HST moon search data for Pluto, Ceres, Vesta, Pallas, and Lutetia. Would like to further define methods to enable efficient moon searches and limiting magnitude studies for archival data sets, and to help justify future HST and JWST observations Ideas for turbo-charged “Steffl et al. on steroids” moon searches, and limiting magnitudes: –Monte Carlo method: thousands of software iterations –Zoo method: thousands of human eyeballs What are the optimal roles and usage for eyeballs and software for setting limiting magnitudes? The time is ripe: what other planetary data analysis tasks could benefit from the “Zoo” approach?

3. Eyeballs: pros and cons Eye-brain can quickly parse a messy image Very reliable for short periods of time, but can become fatigued Small-number statistics: can only get a few colleagues to do it Best as spot check and tuning for a more automated approach?

4. Automation: pros and cons Hardware/software can work tirelessly with consistency Can consistently miss candidates in complex images Monte Carlo: relentless iteration can sample entire field with better statistics Visual inspections still needed for spot checks, tuning, verification Certain tasks may never fully lend themselves to automation: is this one?

5. Nix & Hydra discovery observations ACS Wide Field Channel (WFC) covers entire orbital stability zone Pluto-Charon near chip gap 4 long exposures on May 15 and again on May 18, 2005 Nix & Hydra playing peek-a- boo throughout the observing sequence Many pixels to inspect, even for this relatively small data set Limiting magnitude data is inherently noisy and messy: complicated images

6. Quite a few different artifacts to contend with… 15 May 2005 sum 4 frames

7. 15 May 2005 median 4 frame Even cleaned-up images are not necessarily ideal

8. “clean” implanted software detections truth Implanting and automatically detecting simulated moons Can Monte Carlo iterations (better statistics) overcome software detection limitations?

9. Deep (saturated and bleeding) image implanted with simulated moons

10. Software detections marked with red boxes Truth marked with blue boxes

11. Can iterate endlessly to test every pixel in the field with simulated moons of varying magnitudes, and build up a hi-resolution limiting magnitude map...

12. Can iterate endlessly to test every pixel in the field with simulated moons of varying magnitudes, and build up a hi-resolution limiting magnitude map...

13. Can iterate endlessly to test every pixel in the field with simulated moons of varying magnitudes, and build up a hi-resolution limiting magnitude map...

14. Then again, imagine if we could have thousands of people making millions of independent visual searches?

18. Welcome to the Zooniverse, where you can help astronomers explore the Universe We need your help to classify… a task at which your brain is better than even the most advanced computer… you may even be the first person in history to see… More than 250,000 people have taken part … within 24 hours of launch, the site was receiving 70,000 classifications an hour, and more than 50 million classifications were received by the project during its first year. Having multiple classifications of the same object is important… we were able to prove that the classifications are as good as those completed by professional astronomers. Thanks to the overwhelming response we realized we could ask much more. In the 14 months the site was up, Galaxy Zoo 2 users helped us make over 60,000,000 classifications.

19. Next “Zoo” ? Find-a-moon online activity; not a gimmick Helps set limiting magnitudes Small but enticing chance of discovery, e.g. “Hanny’s Voorwerp”…the next Nix or Hydra… a post-Pluto KBO for New Horizons to visit? Best of both worlds: versatility of human eyeballs, with good statistics via brute force (many people instead of many CPU cycles) The tools and “standing army of thousands” already exists. They are hungry for a wider range of projects to do, thanks to the “Zooniverse”

21. NEXT ZOO ? full frame sum clean