Fiber spectrum extraction for LAMOST based on 2-D exponential polynomial model

Abstract

A spectrum extraction method based on a two-dimensional (2-D) exponential polynomial model is proposed in this paper. It is presented for extracting the flux of the fiber spectrum from a two-dimensional image observed by Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST). Due to the effects of the environments and the instruments, centers of the fiber spectra deviate from the ideal, and the energy is expanded to the neighbors in the form of a point-spread function (PSF) in two dimensions. Thus we use a 2-D model to fit the PSF. In spatial orientation and wavelength orientation, the flat-field images and the calibration lamp images are respectively used to evaluate the parameters of the 2-D exponential polynomial model. With the 2-D exponential polynomial model, the spectrum flux is extracted based on the least square theory. The experiments are processed through simulated profiles to demonstrate the effectiveness of the proposed algorithm. Especially, its superiority of restraining noise and fitting asymmetric fiber profiles is proved.