Data-driven Dynamics with Orbital Torus Imaging: A Flexible Model of the Vertical Phase Space of the Galaxy

TL;DR

This paper introduces Orbital Torus Imaging, a flexible, data-driven method for modeling the vertical phase space of stars in the Milky Way, enabling mass distribution inference without detailed global models.

Contribution

The paper presents a novel orbit foliation framework that fits stellar data directly, bypassing the need for a global mass model or detailed survey selection function modeling.

Findings

OTI accurately fits simulated stellar abundance data.

The framework derives vertical acceleration profiles and orbital parameters.

It does not require a global Milky Way mass model.

Abstract

The vertical kinematics of stars near the Sun can be used to measure the total mass distribution near the Galactic disk and to study out-of-equilibrium dynamics. With contemporary stellar surveys, the tracers of vertical dynamics are so numerous and so well measured that the shapes of underlying orbits are almost directly visible in the data through element abundances or even stellar density. These orbits can be used to infer a mass model for the Milky Way, enabling constraints on the dark matter distribution in the inner galaxy. Here we present a flexible model for foliating the vertical position-velocity phase space with orbits, for use in data-driven studies of dynamics. The vertical acceleration profile in the vicinity of the disk, along with the orbital actions, angles, and frequencies for individual stars, can all be derived from that orbit foliation. We show that this framework - "Orbital Torus Imaging" (OTI) - is rigorously justified in the context of dynamical theory, and does a good job of fitting orbits to simulated stellar abundance data with varying degrees of realism. OTI (1) does not require a global model for the Milky Way mass distribution, and (2) does not require detailed modeling of the selection function of the input survey data. We discuss the approximations and limitations of the OTI framework, which currently trades dynamical interpretability for flexibility in representing the data in some regimes, and which also presently separates the vertical and radial dynamics. We release an open-source tool, torusimaging, to accompany this article.