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- Villarroel, Brian, et al.
(författare)
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The VASCO project : 100 red transients and their follow up
- 2020
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Ingår i: Proceedings of the International Astronautical Congress, IAC. - : International Astronautical Federation, IAF.
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Konferensbidrag (refereegranskat)abstract
- The Vanishing & Appearing Sources during a Century of Observations (VASCO) project investigates astronomical surveys spanning a 70 years time interval, searching for unusual and exotic transients. We present herein the VASCO Citizen Science Project, that uses three different approaches to the identification of unusual transients in a given set of candidates: hypothesis-driven, exploratory-driven and machine learning-driven (which is of particular benefit for SETI searches). To address the big data challenge, VASCO combines methods from the Virtual Observatory, a user-aided machine learning and visual inspection through citizen science. In this article, we demonstrate the citizen science project, the new and improved candidate selection process and give a progress report. We also present the VASCO citizen science network led by amateur astronomy associations mainly located in Algeria, Cameroon and Nigeria. At the moment of writing, the citizen science project has carefully examined 12,000 candidate image pairs in the data, and has so far identified 713 objects classified as “vanished”. The most interesting candidates will be followed up with optical and infrared imaging, together with the observations by the most potent radio telescopes.
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2. |
- Villarroel, Beatriz, et al.
(författare)
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Launching the VASCO Citizen Science Project
- 2022
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Ingår i: Universe. - : MDPI AG. - 2218-1997. ; 8:11, s. 561-
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Tidskriftsartikel (refereegranskat)abstract
- The Vanishing & Appearing Sources during a Century of Observations (VASCO) project investigates astronomical surveys spanning a time interval of 70 years, searching for unusual and exotic transients. We present herein the VASCO Citizen Science Project, which can identify unusual candidates driven by three different approaches: hypothesis, exploratory, and machine learning, which is particularly useful for SETI searches. To address the big data challenge, VASCO combines three methods: the Virtual Observatory, user-aided machine learning, and visual inspection through citizen science. Here we demonstrate the citizen science project and its improved candidate selection process, and we give a progress report. We also present the VASCO citizen science network led by amateur astronomy associations mainly located in Algeria, Cameroon, and Nigeria. At the moment of writing, the citizen science project has carefully examined 15,593 candidate image pairs in the data (ca. 10% of the candidates), and has so far identified 798 objects classified as "vanished". The most interesting candidates will be followed up with optical and infrared imaging, together with the observations by the most potent radio telescopes.
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