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The e-TidalGCs Project: Modeling the extra-tidal features generated by Galactic globular clusters

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arxiv 2301.05166 v1 pith:KSTW6IR4 submitted 2023-01-12 astro-ph.GA

The e-TidalGCs Project: Modeling the extra-tidal features generated by Galactic globular clusters

classification astro-ph.GA
keywords clustersglobularextra-tidalfoundgalacticmodelsdifferentfeatures
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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We present the e-TidalGCs Project which aims at modeling and predicting the extra-tidal features surrounding all Galactic globular clusters for which 6D phase space information, masses and sizes are available (currently 159 globular clusters). We focus the analysis and presentation of the results on the distribution of extra-tidal material on the sky, and on the different structures found at different heliocentric distances. We emphasize the wide variety of morphologies found: beyond the canonical tidal tails, our models reveal that the extra-tidal features generated by globular clusters take a wide variety of shapes, from thin and elongated shapes, to thick, and complex halo-like structures. We also compare some of the most well studied stellar streams found around Galactic globular clusters to our model predictions, namely those associated to the clusters NGC 3201, NGC 4590, NGC 5466 and Pal 5. Additionally, we investigate how the distribution and extension in the sky of the simulated streams vary with the Galactic potential by making use of three different models, containing or not a central spheroid, or a stellar bar. Overall, our models predict that the mass lost by the current globular cluster population in the field from the last 5 Gyrs is between $0.3-2.1\times10^{7}M_{\odot}$, an amount comparable between 7-55 % of current mass. Most of this lost mass is found in the inner Galaxy, with the half-mass radius of this population being between 4-6 kpc. The outputs of the simulations will be publicly available, at a time when the ESA Gaia mission and complementary spectroscopic surveys are delivering exquisite data to which these models can be compared.

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