# Deep-Learning-Based Identification of Broad-Absorption Line Quasars
## 2 Data  
### Dataset  
The Sloan Digital Sky Survey (SDSS), a major astronomical survey project that uses the Sloan Foundation 2.5 m telescope at the Apache Point Observatory (APO) and the DuPont 2.5 m telescope at the Las Campanas Observatory (LCO), has multi-band images and spectroscopic data that have been provided for more than three million objects. The SDSS has gone through the following five phases since the start of its official survey in 2000: SDSS-I (2000-2005), SDSS-II (2005-2008), SDSS-III (2008-2014), SDSS-IV (2014-2020), and SDSS -V (2020-2025). Each phase covered different observational and scientific objectives [23].  
The SDSS-IV DR16 is the core dataset of this study. DR16 was derived from the fourth data release of SDSS-IV in 2020, which included quasars with spectral wavelengths in the range of 3600-10,400 A and a spectral resolution of \(\sim\)2000. The DR16 Quasar Catalog (DR16Q) ([PERSON] et al., 2020) recorded 750,414 quasars with 920,110 observations. DR16Q is the final SDSS-IV/eBOSS catalog and the largest sample of spectroscopically certified quasars available to date [22; 23]. [PERSON] et al. (2012) described the classification and redshift measurement methods applied to the SDSS data [24]. The SDSS DR16, documented by [PERSON] et al. (2020), provides extensive spectroscopic data that were critical for analyzing and classifying quasars in this study [23].  
The rest-frame wavelength range of 1260-2400 A was selected in this paper following thorough analysis and consideration. This range was chosen due to the significance of key spectral lines, such as C IV and Si IV, and their positions within the spectrum. This selection ensured adequate coverage of the C IV absorption region, which was crucial for studying the BAL quasars as it reflects the absorption signature of high-velocity ions. Additionally, this range minimized the impact of unrelated spectral regions, enabling a more precise analysis of the absorption features. Figure 1 shows some spectral images of the BAL and non-BAL samples, which were the one-dimensional spectrum.  
In constructing the dataset, the BAL_PROB parameter from SDSS DR16Q was used to differentiate between the BAL quasars and the non-BAL quasars. The classification of the BAL quasars and the non-BAL quasars was based on the BAL_PROB parameter provided in the DR16Q quasar catalog. BAL_PROB is a probability value calculated by fitting the C IV absorption features in the spectrum. When the BAL_PROB parameter is a 1, it indicates that the quasar exhibits significant broad-absorption line features, meaning it is a BAL quasar, and when the BAL_PROB parameter is a 0, it indicates that the quasar does not exhibit broad-absorption line features, meaning it is a non-BAL quasar. This calculation method combines physical model fitting and statistical analysis to ensure the accuracy of a classification [21]. To ensure the model remained balanced and unbiased, a random selection of the non-BAL quasars, equal in number to the BAL quasars, was chosen to form the final training and test datasets. The exact sample sizes are presented in Table 1.