Are there broad absorption-line blazars?

Mishra, Sapna; Gopal-Krishna, Gopal-Krishna; Chand, Hum; Chand, Krishan; Ojha, Vineet

doi:10.1093/mnrasl/slz122

Cited by 4 publications

(3 citation statements)

References 34 publications

(53 reference statements)

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“…Borguet & Hutsemékers (2010) simulated the two-component polar+equatorial wind model of quasar outflows and showed that it is necessary to include both the equatorial and the polar absorption regions to explain the C BAL profiles in some sources. However, the search of Mishra et al (2019) to find BAL blazars using intranight optical variability did not result in any detection. Interestingly, we find that the BAL fraction increases for the highest log(R 𝐼 ) (lowest orientation angles) bins even though the number of sources in these bins is low.…”

Section: Dependence Of Bal Fraction On Quasar Orientationmentioning

confidence: 90%

Fraction of broad absorption line quasars in different radio morphologies

Nair,

Vivek

2022

Preprint

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In this study, we investigated the orientation model of Broad Absorption Line (BAL) quasars using a sample of sources that are common in Sloan Digital Sky Survey (SDSS) Data Release (DR)-16 quasar catalog and Very Large Array (VLA)-Faint Images of the Radio Sky at Twenty Centimeters (FIRST) survey. Using the radio cut-out images from the FIRST survey, we first designed a deep learning model using convolutional neural networks (CNN) to classify the quasar radio morphologies into the core-only, young jet, single lobe, or triples. These radio morphologies are further sub-classified into core-dominated and lobe-dominated sources. The CNN models can classify the sources with a high precision of >98% for all the morphological sub-classes. The average BAL fraction in the resolved core, core-dominated, and lobe-dominated quasars are consistent with the BAL fraction inferred from radio and infra-red surveys. We also present the distribution of BAL quasars as a function of quasar orientation by using the radio core-dominance as an orientation indicator. A similar analysis is performed for HiBALs, LoBALs, and FeLoBALs. All the radio morphological sub-classes and BAL sub-classes show an increase in BAL fraction at high orientation angles of the jets with respect to the line of sight. Our analysis suggests that BAL quasars are more likely to be found in viewing angles close to the equatorial plane of the quasar. However, a pure orientation model is inadequate, and a combination of orientation and evolution is probably the best way to explain the complete BAL phenomena.

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Section: Dependence Of Bal Fraction On Quasar Orientationmentioning

confidence: 90%

Fraction of broad absorption line quasars in different radio morphologies

Nair,

Vivek

2022

Preprint

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“…The presence of INOV in the DLCs was checked by applying the test (de Diego 2010), following the basic procedure described in Mishra et al (2019). Among the 3 comparison stars initially chosen for a given session, we identified the steadier two by inspecting the star-star DLCs and the test was applied to only the 3 DLCs involving those two comparison stars and the target blazar.…”

Section: Discussionmentioning

confidence: 99%

Intranight variability of UV emission from powerful blazars

Chand,

Gopal-Krishna,

Omar

et al. 2021

Preprint

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We report the first study to characterise intranight variability of the blazar class from the perspective of (rest-frame) UV emission. For this, we carried out intranight optical monitoring of 14 flat-spectrum radio quasars (FSRQs) located at high redshifts (1.5 < < 3.7), in 42 sessions of median duration ∼ 5.4 hr. These sources were grouped into two samples distinguished by published fractional optical polarisation: (i) nine low-polarisation sources with < 3% and (ii) five high-polarisation sources. Unexpectedly, a high duty cycle (DC ∼ 30%) is found for intranight variability (with amplitude > 3%) of the low-polarisation sources. This DC is a few times higher than that reported for low-polarisation FSRQs located at moderate redshifts ( ∼ 0.7) and hence typically monitored in the rest-frame blue-optical. Further, we found no evidence for an increased intranight variability of UV emission with polarisation, in contrast to the strong correlation found for intranight variability of optical emission. We briefly discuss this in the context of an existing scenario which posits that the nonthermal UV emission of blazars arises from a relativistic particle population different from that radiating up to near-infrared/optical frequencies.

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“…Consequently, QSOs are used to study astrophysical problems in various fields. For instance, the spectrum of QSOs is a powerful tracer of the formation and evolution of black holes, the spins of black holes, and the co-evolution of black holes and host galaxies (Kormendy & Richstone 1995;Silk & Rees 1998;Kaspi et al 2000;Di Matteo et al 2005;Springel et al 2005;Kormendy & Ho 2013;Chen 2021;Valentini et al 2021); taking advantage of microlensing, astronomers study the feature of accretion disks with the light curves of QSOs (Agol & Krolik 1999;Morgan et al 2010;Dexter & Agol 2011;Blackburne et al 2011); the absorption lines of quasars are unique tracers of the interstellar media along the line of sight (Scaringi et al 2009;Hall et al 2013;Chen et al 2020;Mishra et al 2021;Zabl et al 2021). Besides, high-redshift quasars are valuable for understanding the reionization of the Universe and the formation of galaxies (McLure & Jarvis 2002;Wang et al 2019;Lupi et al 2021).…”

Section: Introductionmentioning

confidence: 99%

The Quasar Candidates Catalogs of DESI Legacy Imaging Survey Data Release 9

Zizhao¹,

Li²

2022

Preprint

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Quasars can be used to measure baryon acoustic oscillations at high redshift, which are considered as direct tracers of the most distant large-scale structures in the Universe. It is fundamental to select quasars from observations before implementing the above research. This work focuses on creating a catalog of quasar candidates based on photometric data to provide primary priors for further object classification with spectroscopic data in the future, such as The Dark Energy Spectroscopic Instrument (DESI) Survey. We adopt a machine learning algorithm (Random Forest, RF) for quasar identification. The training set includes 651, 073 positives and 1, 227, 172 negatives, in which the photometric information are from DESI Legacy Imaging Surveys (DESI-LIS) & Wide-field Infrared Survey Explore (WISE), and the labels are from a database of spectroscopically confirmed quasars based on Sloan Digital Sky Survey (SDSS) and the Set of Identifications & Measurements and Bibliography for Astronomical Data (SIMBAD). The trained RF model is applied to point-like sources in DESI-LIS Data Release 9. To quantify the classifier's performance, we also inject a testing set into the to-be-applied data. Eventually, we obtained 1, 953, 932 Grade-A quasar candidates and 22, 486, 884 Grade-B quasar candidates out of 425, 540, 269 sources (∼ 5.7%). The catalog covers ∼ 99% of quasars in the to-be-applied data by evaluating the completeness of the classification on the testing set. The statistical properties of the candidates agree with that given by the method of colorcut selection. Our catalog can intensely decrease the workload for confirming quasars with the upcoming DESI data by eliminating enormous non-quasars but remaining high completeness. All data in this paper is publicly available online.

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Are there broad absorption-line blazars?

Cited by 4 publications

References 34 publications

Fraction of broad absorption line quasars in different radio morphologies

Fraction of broad absorption line quasars in different radio morphologies

Intranight variability of UV emission from powerful blazars

The Quasar Candidates Catalogs of DESI Legacy Imaging Survey Data Release 9

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