SIMBAD references

2016ApJS..224...18P - Astrophys. J., Suppl. Ser., 224, 18-18 (2016/June-0)

A selection of giant radio sources from NVSS.


Abstract (from CDS):

Result. of the application of pattern-recognition techniques to the problem of identifying giant radio sources (GRSs) from the data in the NVSS catalog are presented, and issues affecting the process are explored. Decision-tree pattern-recognition software was applied to training-set source pairs developed from known NVSS large-angular-size radio galaxies. The full training set consisted of 51,195 source pairs, 48 of which were known GRSs for which each lobe was primarily represented by a single catalog component. The source pairs had a maximum separation of 20^′ and a minimum component area of 1.87 square arcmin at the 1.4 mJy level. The importance of comparing the resulting probability distributions of the training and application sets for cases of unknown class ratio is demonstrated. The probability of correctly ranking a randomly selected (GRS, non-GRS) pair from the best of the tested classifiers was determined to be 97.8±1.5%. The best classifiers were applied to the over 870,000 candidate pairs from the entire catalog. Images of higher-ranked sources were visually screened, and a table of over 1600 candidates, including morphological annotation, is presented. These systems include doubles and triples, wide-angle tail and narrow-angle tail, S- or Z-shaped systems, and core-jets and resolved cores. While some resolved-lobe systems are recovered with this technique, generally it is expected that such systems would require a different approach.

Abstract Copyright: © 2016. The American Astronomical Society. All rights reserved.

Journal keyword(s): astronomical databases: miscellaneous - catalogs - galaxies: general

VizieR on-line data: <Available at CDS (J/ApJS/224/18): table6.dat>

Nomenclature: Table 6: NVGRC JHHMMSS.s+DDMMSS N=1492.

CDS comments: Sources J122045.0+055204, J172331.0-352542, J182708.3-124020 and J185618.6+013120 are not in SIMBAD.

Simbad objects: 11

goto Full paper

goto View the reference in ADS

To bookmark this query, right click on this link: simbad:2016ApJS..224...18P and select 'bookmark this link' or equivalent in the popup menu


© Université de Strasbourg/CNRS

    • Contact