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The intrinsic fraction of broad-absorption line quasars

The intrinsic fraction of broad-absorption line quasars
The intrinsic fraction of broad-absorption line quasars
We carefully reconsider the problem of classifying broad-absorption line quasars (BALQSOs) and derive a new, unbiased estimate of the intrinsic BALQSO fraction from the Sloan Digital Sky Survey (SDSS) DR3 quasi-stellar object (QSO) catalogue. We first show that the distribution of objects selected by the so-called 'absorption index' (AI) is clearly bimodal in log AI, with only one mode corresponding to definite BALQSOs. The surprisingly high BALQSO fractions that have recently been inferred from AI-based samples are therefore likely to be overestimated. We then present two new approaches to the classification problem that are designed to be more robust than the AI, but also more complete than the traditional 'balnicity index' (BI). Both approaches yield observed BALQSO fractions around 13.5 per cent, while a conservative third approach suggests an upper limit of 18.3 per cent. Finally, we discuss the selection biases that affect our observed BALQSO fraction. After correcting for these biases, we arrive at our final estimate of the intrinsic BALQSO fraction. This is fBALQSO= 0.17 ± 0.01 (stat) ± 0.03 (sys) with an upper limit of fBALQSO? 0.23 . We conclude by pointing out that the bimodality of the log AI distribution may be evidence that the BAL-forming region has clearly delineated physical boundaries.
methods: statistical, catalogues, surveys, quasars: absorption lines
1365-2966
1426-1435
Knigge, Christian
ac320eec-631a-426e-b2db-717c8bf7857e
Scaringi, Simone
88701970-a1b9-41fe-bf55-886716ee3374
Goad, Michael R.
98d06542-81a7-4d7b-a0a5-c79079b9c662
Cottis, Christopher E.
25aa05dc-de5d-4deb-9486-c04d94e871d0
Knigge, Christian
ac320eec-631a-426e-b2db-717c8bf7857e
Scaringi, Simone
88701970-a1b9-41fe-bf55-886716ee3374
Goad, Michael R.
98d06542-81a7-4d7b-a0a5-c79079b9c662
Cottis, Christopher E.
25aa05dc-de5d-4deb-9486-c04d94e871d0

Knigge, Christian, Scaringi, Simone, Goad, Michael R. and Cottis, Christopher E. (2008) The intrinsic fraction of broad-absorption line quasars. Monthly Notices of the Royal Astronomical Society, 386 (3), 1426-1435. (doi:10.1111/j.1365-2966.2008.13081.x).

Record type: Article

Abstract

We carefully reconsider the problem of classifying broad-absorption line quasars (BALQSOs) and derive a new, unbiased estimate of the intrinsic BALQSO fraction from the Sloan Digital Sky Survey (SDSS) DR3 quasi-stellar object (QSO) catalogue. We first show that the distribution of objects selected by the so-called 'absorption index' (AI) is clearly bimodal in log AI, with only one mode corresponding to definite BALQSOs. The surprisingly high BALQSO fractions that have recently been inferred from AI-based samples are therefore likely to be overestimated. We then present two new approaches to the classification problem that are designed to be more robust than the AI, but also more complete than the traditional 'balnicity index' (BI). Both approaches yield observed BALQSO fractions around 13.5 per cent, while a conservative third approach suggests an upper limit of 18.3 per cent. Finally, we discuss the selection biases that affect our observed BALQSO fraction. After correcting for these biases, we arrive at our final estimate of the intrinsic BALQSO fraction. This is fBALQSO= 0.17 ± 0.01 (stat) ± 0.03 (sys) with an upper limit of fBALQSO? 0.23 . We conclude by pointing out that the bimodality of the log AI distribution may be evidence that the BAL-forming region has clearly delineated physical boundaries.

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More information

Published date: 21 May 2008
Keywords: methods: statistical, catalogues, surveys, quasars: absorption lines
Organisations: Astronomy and Space Science

Identifiers

Local EPrints ID: 144205
URI: http://eprints.soton.ac.uk/id/eprint/144205
ISSN: 1365-2966
PURE UUID: a12fe87c-df5e-4034-a153-dea52998fcd4

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Date deposited: 16 Apr 2010 15:21
Last modified: 14 Mar 2024 00:45

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Contributors

Author: Simone Scaringi
Author: Michael R. Goad
Author: Christopher E. Cottis

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