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Improved characterization of intranight optical variability of prominent AGN classes

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dc.contributor.author Goyal, A.
dc.contributor.author Gopal-Krishna
dc.contributor.author Witta, P. J.
dc.contributor.author Stalin, C. S.
dc.contributor.author Sagar, R.
dc.date.accessioned 2015-06-30T06:49:09Z
dc.date.available 2015-06-30T06:49:09Z
dc.date.issued 2013
dc.identifier.uri http://hdl.handle.net/123456789/1118
dc.description.abstract The incidence of intranight optical variability (INOV) is known to differ significantly among different classes of powerful active galactic nuclei (AGN). A number of statistical methods have been employed in the literature for testing the presence of INOV in the light curves, sometimes leading to discordant results. In this paper, we compare the INOV characteristics of six prominent classes of AGN, as evaluated using three commonly used statistical tests, namely the χ² -test, the modified C-test and the F-test, which has recently begun to gain popularity. The AGN classes considered are: radio-quiet quasars, radio-intermediate quasars, lobe-dominated quasars, low optical polarization core-dominated quasars, high optical polar- ization core-dominated quasars and TeV blazars. Our analysis is based on a large body of AGN monitoring data, involving 262 sessions of intranight monitoring of a total 77 AGN, using 1–2 m class optical telescopes located in India. In order to compare the usefulness of the statistical tests, we have also subjected them to a ‘sanity check’ by comparing the number of false positives yielded by each test with the corresponding statistical prediction. The present analysis is intended to serve as a benchmark for future INOV studies of AGN of different classes. en_US
dc.language.iso en_US en_US
dc.publisher Oxford University Press en_US
dc.relation.ispartofseries mn435-1300
dc.subject Methods:data analysis – methods: statistical – techniques: photometric – galaxies: active. en_US
dc.title Improved characterization of intranight optical variability of prominent AGN classes en_US
dc.type Article en_US


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