Using action space clustering to constrain the recent accretion history of Milky Way-like galaxiesShow others and affiliations
2021 (English)In: Monthly notices of the Royal Astronomical Society, ISSN 0035-8711, E-ISSN 1365-2966, Vol. 509, no 4, p. 5882-5901Article in journal (Refereed) Published
Abstract [en]
In the currently favoured cosmological paradigm galaxies form hierarchically through the accretion of satellites. Since a satellite is less massive than the host, its stars occupy a smaller volume in action space. Actions are conserved when the potential of the host halo changes adiabatically, so stars from an accreted satellite would remain clustered in action space as the host evolves. In this paper, we identify recently disrupted accreted satellites in three Milky Way-like disc galaxies from the cosmological baryonic FIRE-2 simulations by tracking satellites through simulation snapshots. We try to recover these satellites by applying the cluster analysis algorithm Enlink to the orbital actions of accreted star particles in the z = 0 snapshot. Even with completely error-free mock data we find that only 35 per cent (14/39) satellites are well recovered while the rest (25/39) are poorly recovered (i.e. either contaminated or split up). Most (10/14 similar to 70 per cent) of the well-recovered satellites have infall times <7.1 Gyr ago and total mass >4 x10(8) M-circle dot (stellar mass more than 1.2 x10(6) M-circle dot, although our upper mass limit is likely to be resolution dependent). Since cosmological simulations predict that stellar haloes include a population of in situ stars, we test our ability to recover satellites when the data include 10-50 per cent in situ contamination. We find that most previously well-recovered satellites stay well recovered even with 50 per cent contamination. With the wealth of 6D phase space data becoming available we expect that cluster analysis in action space will be useful in identifying the majority of recently accreted and moderately massive satellites in the Milky Way.
Place, publisher, year, edition, pages
Oxford University Press (OUP) , 2021. Vol. 509, no 4, p. 5882-5901
Keywords [en]
methods: data analysis, methods: statistical, stars: kinematics and dynamics, galaxies: formation, galaxies: haloes
National Category
Astronomy, Astrophysics and Cosmology
Identifiers
URN: urn:nbn:se:kth:diva-313079DOI: 10.1093/mnras/stab3306ISI: 000780137000085Scopus ID: 2-s2.0-85123555413OAI: oai:DiVA.org:kth-313079DiVA, id: diva2:1662850
Note
QC 20221017
2022-06-012022-06-012022-10-27Bibliographically approved