[Paper Review] Orbits of 152 Globular Clusters of the Milky Way Galaxy Constructed from the Gaia DR2 data

A. T. Bajkova, В. В. Бобылев|arXiv (Cornell University)|Aug 28, 2020

Geophysics and Gravity Measurements4 citations

TL;DR

This study presents a comprehensive catalog of orbital solutions for 152 Milky Way globular clusters using Gaia DR2 astrometry and a refined axisymmetric Galactic potential model (NFWBB), integrating orbits backward for 5 Gyr. Based on orbital morphology and dynamical properties, the authors propose a modified classification of globular clusters into accretion-related subsystems, revising 27 objects' group assignments for improved dynamical coherence compared to Massari et al. (2019).

ABSTRACT

We present orbits and their properties for 152 globular clusters of the Milky Way galaxy obtained using average Gaia DR2 proper motions and other astrometric data from the list of Vasiliev (2019). For orbit integrating we have used the axisymmetric model of the Galactic potential based on the Navarro-Frenk-White dark halo, and modified by Bajkova and Bobylev (2016) using circular velocities of Galactic objects in wide region of Galactocentric distances (up to 200 kpc) from Bhattacharjee et.al. (2014) catalog. Based on the analysis of the obtained orbits, we have modified the composition of the subsystems of globular clusters presented in Massari et. al. (2019).

Motivation & Objective

• To construct accurate orbital solutions for nearly all known globular clusters using the most precise astrometric data available from Gaia DR2.
• To evaluate the dynamical coherence of existing globular cluster subsystem classifications, particularly those based on accretion events like Gaia-Enceladus and Sequoia.
• To improve the classification of halo globular clusters by analyzing orbital morphology and kinematic properties.
• To provide a publicly available catalog of orbital projections (X-Y and R-Z) for visual and quantitative analysis of cluster dynamics.
• To refine the dynamical separation criterion between in situ and accreted clusters using the L_Z/ecc bimodality, extending it to halo subsystems.

Proposed method

• Orbit integration was performed backward in time for 5 Gyr using the NFWBB potential model, a modified Navarro-Frenk-White dark halo potential fitted to circular velocity data up to 200 kpc.
• The Galactic potential combines a Miyamoto-Nagai bulge, a Miyamoto-Nagai disk, and an NFW dark halo, with parameters constrained by HI, maser, and Bhattacharjee et al. (2014) data.
• Initial phase-space coordinates (positions and velocities) were taken from Vasiliev (2019), a high-precision catalog of globular cluster astrometry.
• Orbital parameters such as angular momentum (L_Z), eccentricity (ecc), energy, radial and rotational velocities were computed for each cluster.
• Visual analysis of orbits in (X,Y) and (R,Z) projections was used to assess dynamical similarity within subsystems.
• A modified classification scheme was developed by reassigning 27 clusters based on orbital shape, energy, and proximity in phase-space diagrams.

Experimental results

Research questions

• RQ1 How do the orbital properties of Milky Way globular clusters derived from Gaia DR2 data compare with existing dynamical classifications?
• RQ2 Can orbital morphology and energy distribution improve the identification of accreted globular cluster subsystems such as Gaia-Enceladus, Sequoia, and Helmi Streams?
• RQ3 Is the existing classification of globular clusters into subsystems (e.g., Massari et al. 2019) dynamically coherent, or are there inconsistencies in orbital grouping?
• RQ4 To what extent does visualizing orbits in multiple projections enhance the identification of dynamical substructures among globular clusters?
• RQ5 Can a revised classification based on orbital parameters yield a more coherent and physically meaningful grouping of halo globular clusters?

Key findings

• The study presents a complete catalog of orbital solutions for 152 globular clusters, representing nearly the entire known population.
• The NFWBB potential model, fitted to extended circular velocity data up to 200 kpc, provides a robust and well-constrained dynamical framework for orbit integration.
• 27 globular clusters were reclassified into different dynamical subsystems based on orbital morphology and phase-space coherence, improving the consistency of groupings.
• The modified classification shows greater dynamical coherence, with clusters in the same subsystem exhibiting more similar orbital shapes and energy distributions.
• Visual analysis of orbits in (X,Y) and (R,Z) projections reveals clearer clustering of objects within subsystems under the new classification, especially in the L_Z/ecc–Energy and radial–rotational velocity diagrams.
• The revised classification reduces inconsistencies present in the Massari et al. (2019) scheme, particularly for clusters in the Gaia-Enceladus, Sequoia, and Helmi Stream subsystems.