Broad Absorption Line Quasar catalogues with Supervised Neural Networks

被引：0

作者：

Scaringi, Simone

Cottis, Christopher E.

Knigge, Christian

Goad, Michael R.

机构：

来源：

CLASSIFICATION AND DISCOVERY IN LARGE ASTRONOMICAL SURVEYS | 2008年 / 1082卷

关键词：

surveys; catalogues; neural networks; quasars; broad absorption line;

D O I：

暂无

中图分类号：

P1 [天文学];

学科分类号：

0704 ;

摘要：

We have applied a Learning Vector Quantization (LVQ) algorithm to SDSS DR5 quasar spectra in order to create a large catalogue of broad absorption line quasars (BALQSOs). We first discuss the problerns with BALQSO catalogues constructed using the conventional balnicity and/or absorption indices (BI and AI), and then describe the supervised LVQ network we have trained to recognise BALQSOs. The resulting BALQSO catalogue should be substantially more robust and complete than BI- or AI-based ones.

引用

页码：191 / 195

页数：5

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