Variable Stars Common Observation
Mission in Particular Areas of the Sky
The project was initiated in 2011 by Ivan Sergey, an experienced amateur astronomer with variable stars research as the primary focus. The VS-COMPAS acronym stands for Variable Stars Common Observation Mission in Particular Areas of the Sky. This is an exact match with the project's agenda. The main intention of the VS-COMPAS project is to expand the VSX catalog with new variable stars.
Before that time the project was started, Ivan had been using (and continues) his extremely vast knowledge to explore the night sky for new variables by using sets of telescopic images and blinking them manually. Such an approach is as exciting as exhausting at the same time. Though there were more than 20 stars discovered during several last years.
To improve the discovery process it was decided to use a huge NSVS photometric survey covering nearly 14 million of stars from the entire northern hemisphere. At this point a team of four amateur astronomers was created to accumulate efforts in achieving the goal.
Generally, the goal is to cover the sky area visible from mid-nothern latitudes (declination value of -30 and upper, to the north pole), actually following the same declination range as the NSVS survey does. In fact, the discovery process is currently concentrated around the following constellations, mostly in the Milky Way area: Perseus, Andromeda, Aries, Taurus, Auriga, Cygnus, Aquila, Scutum, Lacerta, Cepheus, Cassiopeia, Camelopardalis, etc.
As the next step, a piece of scripting software was created by Ivan Adamin to help to pull out the relevant sets of NSVS data automatically. This allowed to eliminate an enormous amount of manual work digging into the raw NSVS photometric data, reducing it by 50-70 times at least (not to mention the amount of saved time that would be spent on it). The result output contains highly relevant sets of NSVS photometric data to be carefully reviewed by a human eye.
Another notable ability of the software was an automatic check for possible duplicates or existing entries in VSX/GCVS catalog itself. This filtered out nearly 100% of previously discovered variables during the selection phase, allowing us to concentrate on undiscovered ones/candidates. The trick here is that most catalogs have different RA and DEC values for the same object to match.
Based on a need of still large amount of data to be reviewed, Alexey Tkachenko created a web tool allowing all team members to review particular objects and left distinctive statuses. This application is extremely useful when you have a distributed team looking at a potentially the same data. Also it helps to split efforts between team members allowing to process the data simultaneously.
To help us to find an appropriate period value and a phase curve there was a WinEFK software used. Next turn was to obtain all the possible public data about the object. This data usually includes aliases from other star catalogs/surveys; also we need to generate a graphical representation of a light and phase curves and submit this to VSX Administration for a discovery acceptance. You should be careful at this point when the time comes for variability type determining. Also there is an opportunity of combining the photometric data from other surveys to increase a period value accuracy.
To make the last step even more precise, Andrey Prokopovich improved the original WinEFK software to be able to process series of photometric arrays (from the filtering software output). Additionally, he made an ability to distinctively mark photometric data from different surveys.
As a part of the project, depending on the number of discovered eclipsing variables we are going to publish a small survey exposing calculated models for dicovered eclipsing systems. Another point of paying attention to is to continue monitoring of variable stars using the real sky data with our hardware.
The VS-COMPAS team appreciates Sebastian Otero (VSX Team) for his extremely valuable comments and help in resolving the most intricate cases we face during the discovery and variables identification process. Many VS-COMPAS' discoveries have been resolved with help of Sebastian's vast knowledge and his priceless experience in the field.
Variables by Type
Variables by Magnitude
Variables by Period
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