PSF Deconvolution of the IFU Data and Restoration of Galaxy Stellar Kinematics

Abstract

We present a performance test of the Point Spread Function deconvolution algorithm applied to astronomical Integral Field Unit (IFU) Spectroscopy data for restoration of galaxy kinematics. We deconvolve the IFU data by applying the Lucy-Richardson algorithm to the 2D image slice at each wavelength. We demonstrate that the algorithm can effectively recover the true stellar kinematics of the galaxy, by using mock IFU data with diverse combination of surface brightness profile, S/N, line-of-sight geometry and Line-Of-Sight Velocity Distribution (LOSVD). In addition, we show that the proxy of the spin parameter ${\lambda }_{R_e}$ can be accurately measured from the deconvolved IFU data. We apply the deconvolution algorithm to the actual SDSS-IV MaNGA IFU survey data. The 2D LOSVD, geometry and ${\lambda }_{R_e}$ measured from the deconvolved MaNGA IFU data exhibit noticeable difference compared to the ones measured from the original IFU data. The method can be applied to any other regular-grid IFU data to extract the PSF-deconvolved spatial information.

40 pages, 38 figures, 2nd revision submitted to ApJS. Deconvolution code in Python3 is available at https://github.com/astrohchung/deconv. An example code to deconvolve a MaNGA IFU data and compare the 2D kinematics measured from the original and the deconvolved MaNGA data is provided (Partially reconstruct Figure 9)

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• Stellar CoRGI in MaNGA: Stellar Counterrotating Galaxies Identified in the MaNGA Survey
• Diverse Rotation Curves of Galaxies in a Simulated Universe: the Observed Dependence on Stellar Mass and Morphology Reproduced
• The catalogue of virtual early-type galaxies from IllustrisTNG: validation and real observation consistency