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In its 32 years of observations, the NASA/ ESA Hubble Space Telescope has built up an archive containing hundreds of thousands of targeted observations of galaxies, the cluster of galaxies, gravitational lenses and nebulae.
At times, closer objects such as asteroids pass the telescope’s field of view while other targets are being observed, leaving the images’ trails.
Image Credits: Pixabay
On International Asteroid Day in 2019, astronomers launched the Hubble Asteroid Hunter, a citizen science project on the Zooniverse platform (the world’s largest citizen science platform), aiming to visually identify asteroids in archival images from the European Space Agency Hubble Space Telescope (eHST) archive and examine their properties.
The initiative was developed by the European Science and Technology Centre (ESTEC) and the European Space Astronomy Centre’s Science Data Centre (ESDC), collaborating with Google and Zooniverse.
Firstly, the astronomers detected more than 37,000 composite images that were taken between April 2002 and March 2021 with Hubble’s Advanced Camera for Surveys (ACS) and Wide Field Camera 3 (WFC3) instruments.
Hubble can observe an object such as a nebula or galaxy, for an average of 30 minutes. After the observation, the asteroids appeared as streaks or curved lines in the images.
More than 11,400 members of the public then classified and analyzed these images. They identified over 1,000 asteroid trails and the collected data was used to set up an automated algorithm based on artificial intelligence. The final dataset was made by citizen science and AI which contained 1701 trails in 1316 Hubble images.
The project participants also identified several other astronomical objects such as nebulae, galaxies and gravitational lenses.
Approximately one-third of the asteroid trails were recognized and put into the known asteroids category in the International Astronomical Union’s (IAU) Minor Planet Centre, the largest database of solar system objects. The remaining 1,031 trails were previously unknown asteroids. These asteroids were indistinct and likely to be smaller asteroids than those discovered in ground-based surveys.
The majority of these asteroids are expected to be found in the main asteroid belt between Mars and Jupiter, where asteroids of such small size are poorly studied.
As asteroids are small remains left after the formation of the Solar System, their trails could give astronomers some hints about the conditions of the solar system when the planets were forming.
“Citizen science and machine learning are very useful techniques for the systematic search for Solar System objects in existing astronomy science data archives,” said researchers.
“Our work describes a method for finding new asteroids in astronomical archives that span decades. It could be effectively applied to other datasets, increasing the overall sample of well-characterised small bodies in the Solar System and refining their ephemerides.”
The next step of the project is to explore 1,031 streaks of previously unidentified asteroids. Scientists would like to identify their orbits and study their properties, such as their rotation periods and sizes. Many years ago, Hubble identified most of these asteroid streaks, however, researchers can’t use them now to identify their orbits.
With the help of Hubble, scientists can use the parallax effect (a difference in the apparent position of an object when viewed along two different lines of sight) to determine the distances to the asteroids and the shapes of their orbits. This can be done by knowing the position of Hubble at the time of observing and measuring the curvature of the streaks.
The detailed study and its results have been published in the journal Astronomy & Astrophysics.
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