ESA Research Fellow working on data mining with the use of citizen science and machine learning.
Hubble Asteroid Hunter: exploring the ESA Hubble archives with citizen science
The Hubble Space Telescope (HST) archives can hide many unexpected treasures, such as trails of asteroids, showing a characteristic curvature due to the parallax induced by the orbital motion of the spacecraft during the exposures.
We present a new citizen science project exploring the ESA HST (eHST) archive for serendipitously observed asteroids. Hubble Asteroid Hunter (www.asteroidhunter.org) was set up as a collaboration between scientists and engineers at the ESAC Science Data Centre (ESDC) and Zooniverse and launched on the International Asteroid Day in June 2019. Since then, more than 10,000 volunteers provided 2 million classifications of 150,000 HST images and uncovered 1500 asteroid trails in them, many of the asteroids yet to be identified. Finding the asteroids in HST images allows us to refine the ephemerides of their orbits, as well as to study their orbital distribution. In addition to marking the positions of asteroids, volunteers also tagged satellites in orbits higher than Hubble’s and discovered new strong gravitational lenses and collisional ring galaxies. We argue that a combination of citizen science and artificial intelligence methods is an efficient way of exploring archival data and highlight some of the interesting results found by this project with the invaluable help of the Zooniverse volunteers.
An example of an asteroid passing in front of the Crab Nebula, imaged by HST - http://www.esa.int/ESA_Multimedia/Images/2019/10/Foreground_asteroid_passing_the_Crab_Nebula