ORCID Profile
0000-0003-0986-9143
Current Organisation
The University of Edinburgh
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Publisher: EDP Sciences
Date: 02-2019
DOI: 10.1051/0004-6361/201833564
Abstract: The LOFAR Two-metre Sky Survey (LoTSS) is an ongoing sensitive, high-resolution 120–168 MHz survey of the northern sky with erse and ambitious science goals. Many of the scientific objectives of LoTSS rely upon, or are enhanced by, the association or separation of the sometimes incorrectly catalogued radio components into distinct radio sources and the identification and characterisation of the optical counterparts to these sources. We present the source associations and optical and/or IR identifications for sources in the first data release, which are made using a combination of statistical techniques and visual association and identification. We document in detail the colour- and magnitude-dependent likelihood ratio method used for statistical identification as well as the Zooniverse project, called LOFAR Galaxy Zoo, used for visual classification. We describe the process used to select which of these two different methods is most appropriate for each LoTSS source. The final LoTSS-DR1-IDs value-added catalogue presented contains 318 520 radio sources, of which 231 716 (73%) have optical and/or IR identifications in Pan-STARRS and WISE.
Publisher: EDP Sciences
Date: 02-2019
DOI: 10.1051/0004-6361/201833562
Abstract: The LOFAR Two-metre Sky Survey (LoTSS) is a sensitive, high-resolution 120–168 MHz survey of the Northern sky. The LoTSS First Data Release (DR1) presents 424 square degrees of radio continuum observations over the HETDEX Spring Field (10 h 45 m 00 s right ascension 15 h 30 m 00 s and 45°00′00″ declination 57°00′00″) with a median sensitivity of 71 μ Jy beam −1 and a resolution of 6″. In this paper we present photometric redshifts (photo- z ) for 94.4% of optical sources over this region that are detected in the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS) 3 π steradian survey. Combining the Pan-STARRS optical data with mid-infrared photometry from the Wide-field Infrared Survey Explorer, we estimate photo- z s using a novel hybrid photometric redshift methodology optimised to produce the best possible performance for the erse s le of radio continuum selected sources. For the radio-continuum detected population, we find an overall scatter in the photo- z of 3.9% and an outlier fraction (| z phot − z spec |/(1 + z spec ) 0.15) of 7.9%. We also find that, at a given redshift, there is no strong trend in photo- z quality as a function of radio luminosity. However there are strong trends as a function of redshift for a given radio luminosity, a result of selection effects in the spectroscopic s le and/or intrinsic evolution within the radio source population. Additionally, for the s le of sources in the LoTSS First Data Release with optical counterparts, we present rest-frame optical and mid-infrared magnitudes based on template fits to the consensus photometric (or spectroscopic when available) redshift.
Publisher: Oxford University Press (OUP)
Date: 30-05-2023
Abstract: The Square Kilometre Array Observatory (SKAO) will explore the radio sky to new depths in order to conduct transformational science. SKAO data products made available to astronomers will be correspondingly large and complex, requiring the application of advanced analysis techniques to extract key science findings. To this end, SKAO is conducting a series of Science Data Challenges, each designed to familiarize the scientific community with SKAO data and to drive the development of new analysis techniques. We present the results from Science Data Challenge 2 (SDC2), which invited participants to find and characterize 233 245 neutral hydrogen (H i) sources in a simulated data product representing a 2000 h SKA-Mid spectral line observation from redshifts 0.25–0.5. Through the generous support of eight international supercomputing facilities, participants were able to undertake the Challenge using dedicated computational resources. Alongside the main challenge, ‘reproducibility awards’ were made in recognition of those pipelines which demonstrated Open Science best practice. The Challenge saw over 100 participants develop a range of new and existing techniques, with results that highlight the strengths of multidisciplinary and collaborative effort. The winning strategy – which combined predictions from two independent machine learning techniques to yield a 20 per cent improvement in overall performance – underscores one of the main Challenge outcomes: that of method complementarity. It is likely that the combination of methods in a so-called ensemble approach will be key to exploiting very large astronomical data sets.
Publisher: Oxford University Press (OUP)
Date: 30-08-2022
Abstract: New-generation radio telescopes like LOFAR are conducting extensive sky surveys, detecting millions of sources. To maximize the scientific value of these surveys, radio source components must be properly associated into physical sources before being cross-matched with their optical/infrared counterparts. In this paper, we use machine learning to identify those radio sources for which either source association is required or statistical cross-matching to optical/infrared catalogues is unreliable. We train a binary classifier using manual annotations from the LOFAR Two-metre Sky Survey (LoTSS). We find that, compared to a classification model based on just the radio source parameters, the addition of features of the nearest-neighbour radio sources, the potential optical host galaxy, and the radio source composition in terms of Gaussian components, all improve model performance. Our best model, a gradient boosting classifier, achieves an accuracy of 95 per cent on a balanced data set and 96 per cent on the whole (unbalanced) s le after optimizing the classification threshold. Unsurprisingly, the classifier performs best on small, unresolved radio sources, reaching almost 99 per cent accuracy for sources smaller than 15 arcsec, but still achieves 70 per cent accuracy on resolved sources. It flags 68 per cent more sources than required as needing visual inspection, but this is still fewer than the manually developed decision tree used in LoTSS, while also having a lower rate of wrongly accepted sources for statistical analysis. The results have an immediate practical application for cross-matching the next LoTSS data releases and can be generalized to other radio surveys.
Publisher: EDP Sciences
Date: 02-2019
DOI: 10.1051/0004-6361/201833559
Abstract: The LOFAR Two-metre Sky Survey (LoTSS) is an ongoing sensitive, high-resolution 120–168 MHz survey of the entire northern sky for which observations are now 20% complete. We present our first full-quality public data release. For this data release 424 square degrees, or 2% of the eventual coverage, in the region of the HETDEX Spring Field (right ascension 10h45m00s to 15h30m00s and declination 45°00′00″ to 57°00′00″) were mapped using a fully automated direction-dependent calibration and imaging pipeline that we developed. A total of 325 694 sources are detected with a signal of at least five times the noise, and the source density is a factor of ∼10 higher than the most sensitive existing very wide-area radio-continuum surveys. The median sensitivity is S 144 MHz = 71 μ Jy beam −1 and the point-source completeness is 90% at an integrated flux density of 0.45 mJy. The resolution of the images is 6″ and the positional accuracy is within 0.2″. This data release consists of a catalogue containing location, flux, and shape estimates together with 58 mosaic images that cover the catalogued area. In this paper we provide an overview of the data release with a focus on the processing of the LOFAR data and the characteristics of the resulting images. In two accompanying papers we provide the radio source associations and deblending and, where possible, the optical identifications of the radio sources together with the photometric redshifts and properties of the host galaxies. These data release papers are published together with a further ∼20 articles that highlight the scientific potential of LoTSS.
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Lara Alegre.