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Satellite galaxies as better tracers of the Milky Way halo mass

Published online by Cambridge University Press:  14 May 2020

Jiaxin Han
Affiliation:
Department of Astronomy, Shanghai Jiao Tong University, Shanghai200240, China Kavli IPMU (WPI), UTIAS, The University of Tokyo, Kashiwa, Chiba277-8583, Japan email: jiaxin.han@sjtu.edu.cn
Wenting Wang
Affiliation:
Department of Astronomy, Shanghai Jiao Tong University, Shanghai200240, China Kavli IPMU (WPI), UTIAS, The University of Tokyo, Kashiwa, Chiba277-8583, Japan email: jiaxin.han@sjtu.edu.cn
Zhaozhou Li
Affiliation:
Department of Astronomy, Shanghai Jiao Tong University, Shanghai200240, China
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Abstract

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The inference of the Milky Way halo mass requires modelling the phase space structure of dynamical tracers, with different tracers following different models and having different levels of sensitivity to the halo mass. For steady-state models, deviations from steady-state in the tracer distribution lead to an irreducible stochastic bias. This bias is small for satellite galaxies and dark matter particles, but as large as a factor of 2 for halo stars. This is consistent with the picture that satellite galaxies closely trace the underlying phase space distribution of dark matter particles, while halo stars are less phase-mixed. As a result, the use of only ~100 satellite galaxies can achieve a significantly higher accuracy than that achievable with a much larger sample of halo stars.

Type
Contributed Papers
Copyright
© International Astronomical Union 2020

References

Boylan-Kolchin, M., Springel, V., White, S. D. M., Jenkins, A., & Lemson, G. 2009, MNRAS, 398, 1150CrossRefGoogle Scholar
Deng, L.-C., Newberg, H. J., Liu, C., et al. 2012, Research in Astron. and Astrophy., 12, 735CrossRefGoogle Scholar
Guo, Q., White, S., Boylan-Kolchin, M., et al. 2011, MNRAS, 413, 101CrossRefGoogle Scholar
Han, J., Cole, S., Frenk, C. S., Benitez-Llambay, A., & Helly, J. 2018, MNRAS, 474, 60410.1093/mnras/stx2792CrossRefGoogle Scholar
Han, J., Cole, S., Frenk, C. S., & Jing, Y. 2016a, MNRAS, 457, 120810.1093/mnras/stv2900CrossRefGoogle Scholar
Han, J., Wang, W., Cole, S., & Frenk, C. S. 2016b, MNRAS, 456, 100310.1093/mnras/stv2707CrossRefGoogle Scholar
Han, J., Wang, W., Cole, S., & Frenk, C. S.. 2016c, MNRAS, 456, 1017CrossRefGoogle Scholar
Helmi, A., Irwin, M., Deason, A., et al. 2019, The Messenger, 175, 23Google Scholar
Li, Z., Qian, Y., Han, J., Wang, W., & Jing, Y. 2019, ApJ, 886, 69CrossRefGoogle Scholar
Navarro, J. F., Frenk, C. S., & White, S. D. M. 1997, ApJ, 490, 493CrossRefGoogle Scholar
Perryman, M. A. C., de Boer, K. S., Gilmore, G., et al. 2001, Astron. & Astrophy., 369, 33910.1051/0004-6361:20010085CrossRefGoogle Scholar
Sawala, T., Frenk, C. S., Fattahi, A., et al. 2016, MNRAS, 457, 1931CrossRefGoogle Scholar
Wang, W., Han, J., Cole, S., et al. 2018, MNRAS, 476, 5669CrossRefGoogle Scholar
Wang, W., Han, J., Cole, S., Frenk, C., & Sawala, T. 2017, MNRAS, 470, 2351CrossRefGoogle Scholar
Wang, W., Han, J., Cooper, A. P., et al. 2015, MNRAS, 453, 37710.1093/mnras/stv1647CrossRefGoogle Scholar
Wang, W., Han, J., Cautun, M., Li, Z., & Ishigaki, M. N. 2020, Science China Physics, Mechanics & Astronomy, in press, arXiv:1912.02599Google Scholar