2021
DOI: 10.3389/fspas.2020.505043
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Fine Classification of QSOs and Seyferts for Activity Types Based on SDSS Spectroscopy

Abstract: Using the SDSS spectroscopy, we have carried out fine optical spectral classification for activity types for 710 AGN candidates. These objects come from a larger sample of some 2,500 candidate AGN using pre-selection by various samples; bright objects of the Catalog of Quasars and Active Galactic Nuclei, AGN candidates among X-ray sources, optically variable radio sources, IRAS extragalactic objects, etc. A number of papers have been published with the results of this spectral classification. More than 800 QSO… Show more

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Cited by 9 publications
(7 citation statements)
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“…In addition in Table 2, we also describe the types and subtypes used in many known catalogs, such as VCV-13. Some of the spectra are taken from our similar SDSS based classification papers, as here our goal is to explain the most typical features for each type and subtype (Mickaelian et al (2021) and references therein).…”
Section: The Classification Schemementioning
confidence: 99%
See 1 more Smart Citation
“…In addition in Table 2, we also describe the types and subtypes used in many known catalogs, such as VCV-13. Some of the spectra are taken from our similar SDSS based classification papers, as here our goal is to explain the most typical features for each type and subtype (Mickaelian et al (2021) and references therein).…”
Section: The Classification Schemementioning
confidence: 99%
“…In this paper we give this classification scheme and describe all possible classes and subclasses based on their emission-line features, both main emission lines (H, NII, OIII, OI, SII) and other minor details. Our scheme is based on our research carried out during the last 10-15 years (HyperLEDA (2007), Mickaelian (2015), Mickaelian et al (2007Mickaelian et al ( , 2011Mickaelian et al ( , 2018Mickaelian et al ( , 2021, Gavrilović et al (2007), Abrahamyan (2020), Abrahamyan et al (2018aAbrahamyan et al ( ,b, 2019aAbrahamyan et al ( ,b, 2020, Paronyan et al (2019Paronyan et al ( , 2020, Mikayelyan et al (2019), and many others.) and has a strong observational basis.…”
Section: Introductionmentioning
confidence: 99%
“…Here we give in Figures 1 and 2 some examples of fine classification spectra. Some of the spectra are taken from our similar SDSS based classification papers, as here our goal is to explain the most typical features for each type and subtype (Mickaelian et al (2021) and references therein).…”
Section: The Classification Schemementioning
confidence: 99%
“…In this paper we give this classification scheme and describe all possible classes and subclasses based on their emission-line features, both main emission lines (H, NII, OIII, OI, SII) and other minor details. Our scheme is based on our research carried out during the last 10-15 years (HyperLEDA (2007), Mickaelian (2015), Mickaelian et al (2007Mickaelian et al ( , 2011Mickaelian et al ( , 2018Mickaelian et al ( , 2021, Gavrilovic et al (2007), Abrahamyan (2020) 2019a,b, 2020)), Paronyan et al (2019Paronyan et al ( , 2020, Mikayelyan et al (2019), and many others.) and has a strong observational basis.…”
Section: Introductionmentioning
confidence: 99%
“…A primary feature of the type 1 AGNs is the presence of both broad and narrow emission lines in their spectra, whereas type 2 AGNs show only narrow lines (see, e.g., Weedman 1977;Antonucci 1993;Padovani et al 2017). From the literature, we are aware that the intermediate AGN types (e.g., 1.5 or 1.8; Osterbrock 1981) are primarily based on the gradual weakening of the broad component of the Hα and Hβ emission lines in the spectra (see also Runco et al 2016;Mickaelian et al 2021). Such static classifications based on the study of different AGNs and, more recently, continuous follow-up of single sources, have become blended.…”
Section: Introductionmentioning
confidence: 99%