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We present a machine learning based information retrieval system for astronomical observatories that tries to address user defined queries related to an instrument. In the modern instrumentation scenario where heterogeneous systems and talents are simultaneously at work, the ability to supply with the right information helps speeding up the detector maintenance operations. Enhancing the detector uptime leads to increased coincidence observation and improves the likelihood for the detection of astrophysical signals. Besides, such efforts will efficiently disseminate technical knowledge to a wider audience and will help the ongoing efforts to build upcoming detectors like the LIGO-India etc even at the design phase to foresee possible challenges. The proposed method analyses existing documented efforts at the site to intelligently group together related information to a query and to present it on-line to the user. The user in response can further go into interesting links and find already developed solutions or probable ways to address the present situation optimally. A web application that incorporates the above idea has been implemented and tested for LIGO Livingston, LIGO Hanford and Virgo observatories.
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We derive the ranking of the astronomical observatories with the highest impact in astronomy based on the citation analysis of papers published in 2006. We also present a description of the methodology we use to derive this ranking. The current ranking is lead by the Sloan Digital Sky Survey, followed by Swift and the Hubble Space Telescope.
We present here a provenance management system adapted to astronomical projects needs. We collected use cases from various astronomy projects and defined a data model in the ecosystem developed by the IVOA (International Virtual Observatory Alliance). From those use cases, we observed that some projects already have data collections generated and archived, from which the provenance has to be extracted (provenance on top), and some projects are building complex pipelines that automatically capture provenance information during the data processing (capture inside). Different tools and prototypes have been developed and tested to capture, store, access and visualize the provenance information, which participate to the shaping of a full provenance management system able to handle detailed provenance information.
(Abr.) Laser guide stars employed at astronomical observatories provide artificial wavefront reference sources to help correct (in part) the impact of atmospheric turbulence on astrophysical observations. Following the recent commissioning of the 4 Laser Guide Star Facility (4LGSF) on UT4 at the VLT, we characterize the spectral signature of the uplink beams from the 22W lasers to assess the impact of laser scattering from the 4LGSF on science observations. We use the MUSE optical integral field spectrograph to acquire spectra at a resolution of R~3000 of the uplink laser beams over the wavelength range of 4750AA to 9350AA. We report the first detection of laser-induced Raman scattering by N2, O2, CO2, H2O and (tentatively) CH4 molecules in the atmosphere above the astronomical observatory of Cerro Paranal. In particular, our observations reveal the characteristic spectral signature of laser photons -- but 480AA to 2210AA redder than the original laser wavelength of 5889.959AA -- landing on the 8.2m primary mirror of UT4 after being Raman-scattered on their way up to the sodium layer. Laser-induced Raman scattering is not unique to the observatory of Cerro Paranal, but common to any astronomical telescope employing a laser-guide-star (LGS) system. It is thus essential for any optical spectrograph coupled to a LGS system to handle thoroughly the possibility of a Raman spectral contamination via a proper baffling of the instrument and suitable calibrations procedures. These considerations are particularly applicable for the HARMONI optical spectrograph on the upcoming Extremely Large Telescope. At sites hosting multiple telescopes, laser collision prediction tools also ought to account for the presence of Raman emission from the uplink laser beam(s) to avoid the unintentional contamination of observations acquired with telescopes in the vicinity of a LGS system.
We have developed a method that maps large astronomical images onto a two-dimensional map and clusters them. A combination of various state-of-the-art machine learning (ML) algorithms is used to develop a fully unsupervised image quality assessment and clustering system. Our pipeline consists of a data pre-processing step where individual image objects are identified in a large astronomical image and converted to smaller pixel images. This data is then fed to a deep convolutional autoencoder jointly trained with a self-organizing map (SOM). This part can be used as a recommendation system. The resulting output is eventually mapped onto a two-dimensional grid using a second, deep, SOM. We use data taken from ground-based telescopes and, as a case study, compare the systems ability and performance with the results obtained by supervised methods presented by Teimoorinia et al. (2020). The availability of target labels in this data allowed a comprehensive performance comparison between our unsupervised and supervised methods. In addition to image-quality assessments performed in this project, our method can have various other applications. For example, it can help experts label images in a considerably shorter time with minimum human intervention. It can also be used as a content-based recommendation system capable of filtering images based on the desired content.
The Commission on Science and Information Technology (CTCI) of the Brazilian Astronomical Society (SAB) is tasked with assisting the Society on issues of astronomical data management, from its handling and the management of data centres and networks, to technical aspects of the archiving, storage and dissemination of data. In this paper we present a summary of the results of a survey recently conducted by the Commission to diagnose the status of several data-related issues within the Brazilian astronomical community, as well as some proposals derived therefrom.
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