WEDA: A Weak Emission-Line Detection Algorithm Based on the Weighted Ranking

The $\text{H}\alpha $ emission line in rest wavelength frame of optical spectra is valuable characteristics for nebulae detection. Searching and recognizing the spectra with $\text{H}\alpha $ emission line from massive data are necessary for the further study, while the most of methods existed currently do not adapt to such spectral data, especially for the spectra with weak $\text{H}\alpha $ emission line. To address this issue, a new algorithm (named WEDA) for detection of spectra with $\text{H}\alpha $ emission line is provided in this paper. Firstly, the difference factor $\mu $ between the line characteristics of the specific data is defined as its weight in recognizing of the whole lines table. Secondly, a tuning function $\mathit {f(\tau, \delta)}$ based on the momentum formula is defined to update the weights during the process. In this step, the spectra with $\text{H}\alpha $ emission line are analysed and classified as 3 different situations. The amount of spectra with $\text{H}\alpha $ emission line is different in 3 different situations, so the speed of weight of update is different in 3 different situations. The weight of update helps us detect the data containing weak $\text{H}\alpha $ emission line in the 3 situations. Based on this, a new integrated algorithm especially for the detection of the spectra with $\text{H}\alpha $ is provided. In the end, by using several spectral datasets from the DR5 of LAMOST survey, experiments results indicate that the WEDA shows higher accuracy basically unaffected by the dataset size and the signal to noise ratio(SNR) than the other similar algorithms.