Spatially non-parametric recovery of intrinsic kinematic maps in pre- to post-merger galaxies

Abstract

We introduce an adaptable kinematic modelling tool called ROHSA-SNAPD, "Spatially Non-parametric Approach to PSF Deconvolution using ROHSA". ROHSA-SNAPD utilises kinematic regularisation to forward model the intrinsic emission-line flux and kinematics (velocity and linewidth) of 3D data cubes. Kinematic regularisation removes the need to assume an underlying rotation model (eg. exponential disc, tilted-ring) to deconvolve kinematic data. We evaluate the code on mock observations of simulated galaxies: one idealised disc model and three more complex galaxies from a cosmological simulation with varying levels of kinematic disturbance, from pre-merger to post-merger state. The mock observations are designed to approximate published results at $z\sim 1-2$ from 8-metre class near-infrared spectroscopic facilities, using realistic observational parameters including spatial and spectral resolution, noise and point spread function. We demonstrate that ROHSA-SNAPD can effectively recover the intrinsic kinematics of complex systems whilst accounting for observational effects. ROHSA-SNAPD is publicly released on Github.