Improving the full spectrum fitting method: accurate convolution with Gauss-Hermite functions

I start by providing an updated summary of the penalized pixel-fitting (PPXF) method that is used to extract the stellar and gas kinematics, as well as the stellar population of galaxies, via full spectrum fitting. I then focus on the problem of extracting the kinematics when the velocity dispersion sigma is smaller than the velocity sampling Delta V that is generally, by design, close to the instrumental dispersion sigma(inst). The standard approach consists of convolving templates with a discretized kernel, while fitting for its parameters. This is obviously very inaccurate when s less than or similar to Delta V/2, due to undersampling. Oversampling can prevent this, but it has drawbacks. Here I present a more accurate and efficient alternative. It avoids the evaluation of the undersampled kernel and instead directly computes its well-sampled analytic Fourier transform, for use with the convolution theorem. A simple analytic transform exists when the kernel is described by the popular Gauss-Hermite parametrization (which includes the Gaussian as special case) for the line-of-sight velocity distribution. I describe how this idea was implemented in a significant upgrade to the publicly available PPXF software. The key advantage of the new approach is that it provides accurate velocities regardless of sigma. This is important e.g. for spectroscopic surveys targeting galaxies with sigma << sigma(inst), for galaxy redshift determinations or for measuring line-of-sight velocities of individual stars. The proposed method could also be used to fix Gaussian convolution algorithms used in today's popular software packages.