Statistical analysis of the probability of globular clusters interactions with each other and with the galactic centre according to Gaia DR2 data on the cosmological time scale
Ishchenko, M, 1Sobolenko, M, 1Berczik, P, Panamarev, T 1Main Astronomical Observatory of the National Academy of Sciences of Ukraine, Kyiv, Ukraine |
Kinemat. fiz. nebesnyh tel (Online) 2023, 39(1):49-64 |
https://doi.org/10.15407/kfnt2023.01.049 |
Start Page: Extragalactic Astronomy |
Language: Ukrainian |
Abstract: The main idea of the work is to study the dynamic evolution of the orbits of globular clusters (GCs) lookback in time obtained from the cosmological models that are closest to the potential of the Galaxy. This allows us to estimate the probability of close passages (“collisions”) of the GC with each other and with the Galactic central in the Galaxy that dynamically changed in the past. To reproduce the dynamics of the Galaxy in time, we used five from 54 potentials, which were selected from the large-scale cosmological database IllustrisTNG-100, and which in their characteristics (mass and size of disk and halo) are similar to the physical values of the Milky Way. In these potentials variable in time, we reproduced the orbital trajectories of 143 GC in 10 Gyr lookback in time using our own high-order N-body parallel dynamic code φ-GPU. Each GCs was treated as a single physical particle assigned the position and velocity of the GCs center from the Gaia DR2 observations. For each of the potentials, 1000 initial data were generated with randomized initial velocities for the GC within the observation data errors. We assumed that passages with a relative distance of less than 100 pc and a relative velocity of less than 250 km/s are close passages. Clusters passages at farther distances and/or with more high velocities do not have a significant dynamical effect on GCs orbits. In our opinion, more changes in GCs’ orbits can be produced by clusters passages with low velocities and at distances less than (as an example, 4) several sums of half-mass radii. Therefore, we analyse such close passages aside (for short, such passages we name “collisions”). To identify clusters that had close passages with GC, we used the criteria of relative distance: it must be less than 100 pc. Applying these criteria, we obtained statistically significant rates of close passages of the GCs with each other and with the SMBH. We found that during their evolution, GCs have on average approximately 10 passages from each other and approximately 3-4 close passages of GCs near the Galactic central for 1 Gyr at a distance of 50 pc for each of the obtained potentials. |
Keywords: center of the Galaxy, evolution of the Galaxy, Galactic globular clusters, IllustrisTNG-100, kinematics and dynamics of the Galaxy, numerical methods |
1. Allen C., Moreno E., Pichardo B. (2006) The orbits of 48 globular clusters in a Milky Way-like barred galaxy. Astrophys. J. 652 (2). 1150-1169.
https://doi.org/10.1086/508676
2. Allen C., Moreno E., Pichardo B. (2008) Six new galactic orbits of globular clusters in a Milky Way-like galaxy. Astrophys. J. 674 (1). 237-246.
https://doi.org/10.1086/524982
3. Armstrong B. M., Bekki K., Ludlow A. D. (2021) The orbital evolution of UFDs and GCs in an evolving Galactic potential. Mon. Notic. Roy. Astron. Soc. 500 (3). 2937- 2957.
https://doi.org/10.1093/mnras/staa3391
4. Banik N., Bovy J. (2021) On N-body simulations of globular cluster streams. Mon. Notic. Roy. Astron. Soc. 504 (1). 648-653.
https://doi.org/10.1093/mnras/stab886
5. Bajkova A., Bobylev V. (2021) Orbits of 152 globular clusters of the Milky Way galaxy constructed from Gaia DR2. Res. Astron. and Astrophys. 21 (7). 173-188.
https://doi.org/10.1088/1674-4527/21/7/173
6. Baumgardt H., Hilker M., Sollima A., et al. (2019) Mean proper motions, space orbits, and velocity dispersion profiles of Galactic globular clusters derived from Gaia DR2 data. Mon. Notic. Roy. Astron. Soc. 482 (4). 5138-5155.
https://doi.org/10.1093/mnras/sty2997
7. Berczik P., Nitadori K., Zhong S., et al. (2011) High performance massively parallel direct N-body simulations on large GPU clusters. International conference on High Performance Computing, Kyiv, Ukraine, October 8-10. 8-18.
8. Bovy J. (2015) galpy: A python library for Galactic dynamics. Astrophys. J. Suppl. Ser. 216 (2). id. 29, 27.
https://doi.org/10.1088/0067-0049/216/2/29
9. Bovy J., Kawata D., Hunt J. (2018) Made-to-measure modelling of observed galaxy dynamics. Mon. Notic. Roy. Astron. Soc. 473 (2). 2288-2303.
https://doi.org/10.1093/mnras/stx2402
10. Chemerynska I. V., Ishchenko M. V., Sobolenko M. O., et al. (2022) Kinematic characteristics of the Milky Way globular clusters based on Gaia DR-2 data. Adv. Astron. and Space Phys. 12 (1-2).
https://doi.org/10.17721/2227-1481.12.18-24
11. Gaia Collaboration, Helmi A., van Leeuwen F., et al. (2018) Gaia Data Release 2. Kinematics of globular clusters and dwarf galaxies around the Milky Way. Astron. and Astrophys. 616. A12-A59.
12. Garro E. R., Minniti D., Gуmez M., et al. (2022) Inspection of 19 globular cluster candidates in the galactic bulge with the VVV survey. Astron. and Astrophys. 658. A120-A146.
https://doi.org/10.1051/0004-6361/202141819
13. Gnedin O. Y., Ostriker J. P. (1997) Destruction of the galactic globular cluster system. Astrophys. J. 474 (1). 223-255.
https://doi.org/10.1086/303441
14. Gravity Collaboration, Abuter R., Amorim A., et al. (2019) A geometric distance measurement to the Galactic center black hole with 0.3 % uncertainty. Astron. and Astrophys. 625. L10-L20.
https://doi.org/10.1051/0004-6361/201935656
15. Harfst S., Gualandris A., Merritt D., et al. (2007) Performance analysis of direct N-body algorithms on special-purpose supercomputers. New Astron. 12 (5). 357- 377.
https://doi.org/10.1016/j.newast.2006.11.003
16. Johnson D. R. H., Soderblom D. R. (1987) Calculating galactic space velocities and their uncertainties, with an application to the Ursa Major group. Astron. J. 93. 864-867.
https://doi.org/10.1086/114370
17. Kharchenko N. V., Piskunov A. E., Schilbach E., et al. (2013) Global survey of star clusters in the Milky Way. II. The catalogue of basic parameters. Astron. and Astrophys. 558. A53-A61.
https://doi.org/10.1051/0004-6361/201322302
18. Kruijssen J. M. D., Pfeffer J. L., Chevance M., et al. (2020) Kraken reveals itself - the merger history of the Milky Way reconstructed with the E-MOSAICS simulations. Mon. Notic. Roy. Astron. Soc. 498 (2). 2472-2491.
https://doi.org/10.1093/mnras/staa2452
19. Lebesgue H. L. (1904) Leons sur l'integration et la recherche des fonctions primitives. Gauthier-Villars, Paris, France. 138.
20. Mardini M. K., Placco V. M., Meiron Y., et al. (2020) Cosmological insights into the early accretion of r-process-enhanced stars. I. A comprehensive chemodynamical analysis of LAMOST J1109+0754. Astrophys. J. 903 (2). 88-106.
https://doi.org/10.3847/1538-4357/abbc13
21. Miyamoto M., Nagai R. (1975) Three-dimensional models for the distribution of mass in galaxies. Publs Astron. Soc. Jap. 27. 533-543.
22. Moreno E., Pichardo B., Velzquez H. (2014) Tidal radii and destruction rates of globular clusters in the Milky Way due to bulge-bar and disk shocking. Astrophys. J. 793 (2). 110-131.
https://doi.org/10.1088/0004-637X/793/2/110
23. Morton G. M. (1966) A computer oriented geodetic database and a new technique in file sequencing. IBM Ltd., Ottawa, Ontario, Canada. 20.
24. Navarro F., Frenk C., White S. (1997) A universal density profile from hierarchical clustering. Astrophys. J. 490(2). 493-508.
https://doi.org/10.1086/304888
25. Nelson D., Springel V., Pillepich A., et al. (2019) The IllustrisTNG simulations: public data release. Comput. Astrophys. and Cosmol. 6 (1). 2-31.
https://doi.org/10.1186/s40668-019-0028-x
26. Prez-Villegas A., Barbuy B., Kerber L. O., et al. (2020) Globular clusters in the inner Galaxy classified from dynamical orbital criteria. Mon. Notic. Roy. Astron. Soc. 491 (3). 3251-3265.
https://doi.org/10.1093/mnras/stz3162
27. Prez-Villegas A., Rossi L., Ortolani S., et al. (2018) Orbits of selected globular clusters in the Galactic Bulge. Publs Astron. Soc. Austral. 35. e021. 11.
https://doi.org/10.1017/pasa.2018.16
28. Phipps F., Khochfar S., Varri A. L. (2020) Hunting for globular clusters in the early universe. Proc. IAU: Star Clusters: From the Milky Way to the Early Universe. 351. 212-215.
https://doi.org/10.1017/S1743921319006914
29. Pichardo B., Martos M., Moreno E. (2004) Models for the gravitational field of the galactic bar: An application to stellar orbits in the galactic plane and orbits of some globular clusters. Astrophys. J. 609 (1). 144-165.
https://doi.org/10.1086/421008
30. Sagan H. (1994) Space-filling curves. Springer. New York. 193.
https://doi.org/10.1007/978-1-4612-0871-6
31. Schnrich R., Binney J., Dehnen W. (2010) Local kinematics and the local standard of rest. Mon. Notic. Roy. Astron. Soc. 403 (4). 1829-1833.
https://doi.org/10.1111/j.1365-2966.2010.16253.x
32. Vasiliev E. (2019) Proper motions and dynamics of the Milky Way globular cluster system from Gaia DR2. Mon. Notic. Roy. Astron. Soc. 484 (2). 2832-2850.
https://doi.org/10.1093/mnras/stz171