Characterizing the Galactic warp with Gaia: I. The tilted ring model with a twist

TL;DR

This study demonstrates how Gaia data, combined with a family of GC3 methods and kinematic information, can effectively detect and characterize the warp and twist of the Milky Way's stellar disc, especially using OB stars.

Contribution

It introduces a novel application of GC3 methods with Gaia data to accurately measure the Galactic warp and twist, incorporating realistic observational effects and stellar tracers.

Findings

OB stars can determine the warp tilt with better than 0.5° accuracy up to 16 kpc.

Kinematic data improves the accuracy of warp parameter recovery.

The twist angle can be measured within 3° accuracy across all distances.

Abstract

We explore the possibility of detecting and characterizing the warp of the stellar disc of our Galaxy using synthetic Gaia data. The availability of proper motions and, for the brightest stars radial velocities, adds a new dimension to this study. A family of Great Circle Cell Counts (GC3) methods is used. They are ideally suited to find the tilt and twist of a collection of rings, which allow us to detect and measure the warp parameters. To test them, we use random realizations of test particles which evolve in a realistic Galactic potential warped adiabatically to various final configurations. In some cases a twist is introduced additionally. The Gaia selection function, its errors model and a realistic 3D extinction map are applied to mimic three tracer populations: OB, A and Red Clump stars. We show how the use of kinematics improves the accuracy in the recovery of the warp parameters. The OB stars are demonstrated to be the best tracers determining the tilt angle with accuracy better than $\sim0.5$ up to Galactocentric distance of $\sim16$ kpc. Using data with good astrometric quality, the same accuracy is obtained for A type stars up to $\sim13$ kpc and for Red Clump up to the expected stellar cut-off. Using OB stars the twist angle is recovered to within $< 3^\circ$ for all distances.