Gaussian Process Model for the Local Stellar Velocity Field from Gaia Data Release 2

TL;DR

This paper models the local stellar velocity field using Gaia DR2 data with a Gaussian process approach, revealing complex substructures and disequilibrium in the Milky Way's disk.

Contribution

It introduces a non-parametric Gaussian process model for the stellar velocity field using Gaia data, providing detailed 3D maps and new insights into disk dynamics.

Findings

Estimated Oort constants in agreement with previous studies

Identified complex substructures in the local velocity field

First 3D map of the divergence of stellar velocities

Abstract

We model the local stellar velocity field using position and velocity measurements for 4M stars from the second data release of Gaia. We determine the components of the mean or bulk velocity in ~27k spatially-defined bins. Our assumption is that these quantities constitute a Gaussian process where the correlation between the bulk velocity at different locations is described by a simple covariance function or kernel. We use a sparse Gaussian process algorithm based on inducing points to construct a non-parametric, smooth, and differentiable model for the underlying velocity field. We estimate the Oort constants A, B, C, and K and find values in excellent agreement with previous results. Maps of the velocity field within 2 kpc of the Sun reveal complicated substructures, which provide clear evidence that the local disk is in a state of disequilibrium. We present the first 3D map of the divergence of the stellar velocity field and identify regions of the disk that may be undergoing compression and rarefaction.