Research On Automatic Identification Of LAMOST Spectra With Continuum Problem Based On High Performance Computing

As the ongoing of LAMOST Survey,the efficiency and accuracy of Pipeline is getting higher and higher,and the spectral quality is also improved.According to the standard of each pixel signal-to-noise(S/N)bigger than ten,the qualified spectra accounts for about 70%of the observed spectra,while there are a lot of low-quality spectra in released data,and a larger proportion in the low-quality spectra was taken by spectra with continuum problems.Continuum problem is a phenomenon that the continuum of spectra get off their actual continuum even break off due to interstellar extinction and flux calibration,and it will have negative impact on the subsequent process such as spectral line extraction and so on,so that the study to continuum problem spectra is imminent.Tens of thousands of spectra will be obtained in each observation night,and a higher request was being placed on identifying continuum problem spectra quickly and availably.A method of automatic detection and recognition of the continuum problem in the stellar spectra is proposed based on the background above,the main work is divided into the following three parts:(1)Fit continuum.The continuum spectra of the test spectrum and the template spectrum with corresponding type are extracted and then we do the process of flux interpolation and normalization in order to analyze data by means of the non-dimensional contrast.(2)Continuum template matching.In order to make continuum template matching for the test spectrum,the flux differences of the test stellar spectra and template spectra at every point of wavelength in the continuum spectra will be calculated to analyze the features of its distribution.The features we count are average(called ?)value and standard deviation(called ?).The percentage of points distributed in range ?±?*? will be detected to confirm that if there is continuum problem.(3)Confirm the subclass of the test stellar spectra.The subclasses of most continuum problem spectra are not defined.The prerequisite of continuum template matching is to determine the subclass of the test spectrum.In this paper,we assign the stellar type of the template spectrum with the minimum distance to the test spectrum by calculating the Euclidean distance between the two lick indices of the template spectrum and the test spectrum.(4)Automatic identification of LAMOST continuum problem spectra based on high performance computing.We studied parallel computing method based on HPC using python,which by calling MPI to divide many FITS files into a number of processes.The result of each processes will be collected by root when the last processes was completed.To sum up,the parallel computation method of the automatic recognition of the continuum problem spectrum is realized on the high performance computing platform.It achieves more rapid and efficient recognition effect compared to the single computer.