





已完成!看來這個專案已經沒有資料了!
Welcome to Rubin Comet Catchers! Update 3 September 2026: Thanks for your super-FAST comet classifications of Rubin data! Wow! And great news: we unearthed MORE special datasets from Rubin’s Early Data Preview 2 data! By popular demand, we are releasing a limited edition workflow for identifying near-Earth objects (NEOs) in Rubin data! These trailed sources — lovingly called sausages — are important to understand for planetary defense, and they can have comet tails too! And don’t worry, comet fans — we also have new images of Centaurs and other populations coming up or already online! All of these are actual Rubin images that the science team figured out a clever way to get at more science! Just how much and what is in there is up to you to discover… we’re super-excited!
Thanks, everyone, for all your hard work! You can always check out this YouTube video featuring Colin on a show he hosts about the upcoming Rubin Observatory and the Legacy Survey of Space and Time! It features Citizen Science, and Clare Higgs of Rubin Education and Public Outreach presents, too! Thanks again, everyone! We cannot do this without you!
In this section you will find a list of frequently asked questions (FAQ). This page will be updated as we get more questions and as the project evolves.
In solar system astronomy and planetary science, activity is a broad term that describes material -- like dust or gas -- leaving a body. This can include solar system bodies, like comets and active asteroids, as well as interstellar objects, such as comet 2I/Borisov.
Volatiles typically refer to substances that are liquid or gas at room temperature on the surface of Earth. In space, these substances usually sublimate -- meaning they change from solid to gas, skipping the liquid phase -- similar to dry ice here on Earth.
The team has developed a comprehensive pipeline to extract the thumbnail images for this project from Rubin Observatory data. To date, we have relied almost exclusively on the Rubin Science Platform, a website designed for people to work with Rubin data on a cloud server rather than downloading everything, as the data is too large! The general concept is described in the Chandler et al. 2024 paper about the Active Asteroids citizen science project, but we will be publishing a new paper about the Rubin Comet Catchers approach as it is radically different due to the scale.
See also "How do you get the pictures?" above. Right now, the training images (examples of known active or known inactive) objects come from Dark Energy Camera (DECam) data, and the new images are from Rubin Observatory's commissioning camera, ComCam. Once LSSTCam data become publicly available, we'll start to include that as well.
You may hear these terms used interchangeably, but strictly speaking main belt comets (MBCs) are a subset of active asteroids. MBCs orbit only within the main asteroid belt that is found between the orbits of Mars and Jupiter.
This question is basically asking how we can tell if the activity in question is really coming from the object, and not an image artifact or some background object such as a galaxy. To evaluate potential activity we first consider how many images of the activity we have. If we only have one image of the activity, we may extract a "comparison field" that shows exactly the same field of view but at a different time. If the "activity" is still there but the asteroid is not, then the "activity" is actually something else, such as a background galaxy. Hopefully we have multiple images of the object being active. No matter what images we have, in the case of a new active object discovery we would carry out a follow-up observing campaign to study the object and confirm activity.
We will carry out a follow-up observing campaign of newfound active objects in order to confirm activity and to study the objects in more detail. Classifications may also be used to train machine learning systems and inform future ground- and space-based observatories about various aspects of finding and observing active objects.
This is a complex question, but the main places the project involves are the DiRAC Institute at the University of Washington, NSF-DOE Vera C. Rubin Observatory, Zooniverse, Northern Arizona University, the Apache Point Observatory, and Lowell Observatory.
Stay tuned for a better answer as the project scales up with the upcoming LSSTCam data! As of project launch, we have only needed about one terabyte of storage, and a few hundred hours of a relatively simple compute system (a few CPUs) from the Rubin Science Platform.