Orbit@Home in Production Mode with Real Data
We are pleased to announce that orbit@home is now in production mode. WUs are generated now at a rate of about 300,000 every week, each one requiring about one hour to complete on average personal computers. We plan to maintain this production rate for at least one month, and then reassess how to continue the research.
At this moment the research of orbit@home uses real observational data from dedicated near-Earth objects (NEOs) surveys. These surveys have dedicated telescopes that observe every night (weather and moon allowing), and detect asteroids and comets in the solar system. Most detected objects are already known and cataloged, but occasionally a new object is discovered. Historical observational data is available covering over a decade, and orbit@home is using it to generate an high-resolution population of NEOs, that is, mapping not only the known ones, but also the probability distribution of the ones that are still unknown. When we complete this work, we will have a very clear idea not only of how many asteroids and comets with a given brightness (related to their size) are still unknown, but also how they are distributed in space, and this is a very precious information for NEOs surveys that try to discover them every night. In principle, it will be possible to "hunt down" the large NEOs (larger than about 1 km) that are still missing in the catalog of known asteroids, and then progressively continue the search to smaller ones.
The complexity in tracking NEOs and describing their distribution probability has several sources: first of all, it's not simple to characterize how efficiently a telescope is observing every night, and how different factors play together in determining this; secondly, all asteroids move on different orbits, and when observed from the Earth, they all have different apparent rates of motion and directions, so their probability distributions keep stretching and moving on the sky plane. So doing this on a decade worth of observations, and for the whole NEOs population, is a very demanding computational problem, and tackling it could not have been possible without the help of tens of thousands of volunteers.