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Register a new userAstro-WISE for KiDS survey production and quality control
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Added by
Gijs Verdoes Kleijn
Publication date
2011
fields
Physics
and research's language is
English
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The Kilo Degree Survey (KiDS) is a 1500 square degree optical imaging survey with the recently commissioned OmegaCAM wide-field imager on the VLT Survey Telescope (VST). A suite of data products will be delivered to ESO and the community by the KiDS survey team. Spread over Europe, the KiDS team uses Astro-WISE to collaborate efficiently and pool hardware resources. In Astro-WISE the team shares, calibrates and archives all survey data. The data-centric architectural design realizes a dynamic live archive in which new KiDS survey products of improved quality can be shared with the team and eventually the full astronomical community in a flexible and controllable manner
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In this paper we describe the way the Astro-WISE information system (or simply Astro-WISE) supports the data from a wide range of in- struments and combines multiple surveys and their catalogues. Astro-WISE allows ingesting of data from any optical instrument, survey or catalogue, pro- cessing of this data to create new catalogues and bringing in data from different surveys into a single catalogue, keeping all dependencies back to the original data. Full data lineage is kept on each step of compiling a new catalogue with an ability to add a new data source recursively. With these features, Astro- WISE allows not only combining and retrieving data from multiple surveys, but performing scientific data reduction and data mining down to the rawest data in the data processing chain within a single environment.
After its first implementation in 2003 the Astro-WISE technology has been rolled out in several European countries and is used for the production of the KiDS survey data. In the multi-disciplinary Target initiative this technology, nicknamed WISE technology, has been further applied to a large number of projects. Here, we highlight the data handling of other astronomical applications, such as VLT-MUSE and LOFAR, together with some non-astronomical applications such as the medical projects Lifelines and GLIMPS, the MONK handwritten text recognition system, and business applications, by amongst others, the Target Holding. We describe some of the most important lessons learned and describe the application of the data-centric WISE type of approach to the Science Ground Segment of the Euclid satellite.
Large area arrays composed by dispersed stations are of major importance in experiments where Extended Air Shower (EAS) sampling is necessary. In those dispersed stations is mandatory to have detectors that requires very low maintenance and shows good resilience to environmental conditions. In 2012 our group started to work in RPCs that could become acceptable candidates to operate within these conditions. Since that time, more than 30 complete detectors were produced, tested and installed in different places, both indoor and outdoor. The data and analysis to be presented is manly related to the tests made in the Auger site, where two RPCs are under test in real conditions for more than two years. The results confirm the capability to operate such kind of RPCs for long time periods under harsh conditions at a stable efficiency. In the last years Lip and USP - S~ao Carlos start collaboration that aim to install an Eng. Array at BATATA (Auger) site to better study and improve the resilience and performance of the RPCs in outdoor experiments. The organization of such collaboration and the work done so far will be presented.
The OmegaCAM wide-field optical imager is the sole instrument on the VLT Survey Telescope at ESOs Paranal Observatory. The instrument, as well as the telescope, have been designed for surveys with very good, natural seeing-limited image quality over a 1 square degree field. OmegaCAM was commissioned in 2011 and has been observing three ESO Public Surveys in parallel since October 15, 2011. We use the Astro-WISE information system to monitor the calibration of the observatory and to produce the Kilo Degree Survey (KiDS). Here we describe the photometric monitoring procedures in Astro-WISE and give a first impression of OmegaCAMs photometric behavior as a function of time. The long-term monitoring of the observatory goes hand in hand with the KiDS survey production in Astro-WISE. KiDS is observed under partially non-photometric conditions. Based on the first year of OmegaCAM operations it is expected that a $sim 1%-2%$ photometric homogeneity will be achieved for KiDS.
Automatic source detection and classification tools based on machine learning (ML) algorithms are growing in popularity due to their efficiency when dealing with large amounts of data simultaneously and their ability to work in multidimensional parameter spaces. In this work, we present a new, automated method of outlier selection based on support vector machine (SVM) algorithm called one-class SVM (OCSVM), which uses the training data as one class to construct a model of normality in order to recognize novel points. We test the performance of OCSVM algorithm on textit{Wide-field Infrared Survey Explorer (WISE)} data trained on the Sloan Digital Sky Survey (SDSS) sources. Among others, we find $sim 40,000$ sources with abnormal patterns which can be associated with obscured and unobscured active galactic nuclei (AGN) source candidates. We present the preliminary estimation of the clustering properties of these objects and find that the unobscured AGN candidates are preferentially found in less massive dark matter haloes ($M_{DMH}sim10^{12.4}$) than the obscured candidates ($M_{DMH}sim 10^{13.2}$). This result contradicts the unification theory of AGN sources and indicates that the obscured and unobscured phases of AGN activity take place in different evolutionary paths defined by different environments.
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