Tidal Debris as a Dark Matter Probe

Part of the Astrophysics and Space Science Library book series (ASSL, volume 420)

Abstract

Tidal debris streams from galaxy satellites can provide insight into the dark matter distribution in halos. This is because we have more information about stars in a debris structure than about a purely random population of stars: we know that in the past they were all bound to the same dwarf galaxy; and we know that they form a dynamically cold population moving on similar orbits. They also probe a different region of the matter distribution in a galaxy than many other methods of mass determination, as their orbits take them far beyond the typical extent of those for the bulk of stars. Although conclusive results from this information have yet to be obtained, significant progress has been made in developing the methodologies for determining both the global mass distribution of the Milky Way’s dark matter halo and the amount of dark matter substructure within it. Methods for measuring the halo shape are divided into “predictive methods,” which predict the tidal debris properties from the progenitor satellite’s mass and orbit, given an assumed parent galaxy mass distribution; and “fundamental methods,” which exploit properties fundamental to the nature of tidal debris as global potential constraints. Methods for quantifying the prevalence of dark matter subhalos within halos through the analysis of the gaps left in tidal streams after these substructures pass through them are reviewed.

Keywords

Dark Matter Globular Cluster Dwarf Galaxy Dark Matter Halo Large Magellanic Cloud 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

KVJ thanks her postdocs and graduate students for invaluable discussions throughout the year (Andreas Kuepper, Allyson Sheffield, Lauren Corlies, Adrian Price-Whelan, David Hendel and Sarah Pearson). Her work on this volume was supported in part by NSF grant AST-1312196. RGC thanks his graduate student Wayne Ngan and support from CIfAR and NSERC is gratefully acknowledged.

References

  1. Barber, C., Starkenburg, E., Navarro, J. F., McConnachie, A. W., & Fattahi, A. 2014, MNRAS, 437, 959ADSCrossRefGoogle Scholar
  2. Belokurov, V., Koposov, S. E., Evans, N. W., et al. 2014, MNRAS, 437, 116ADSCrossRefGoogle Scholar
  3. Binney, J. 2008, MNRAS, 386, L47ADSCrossRefGoogle Scholar
  4. Bonaca, A., Geha, M., Küpper, A. H. W., et al. 2014, ApJ, 795, 94ADSCrossRefGoogle Scholar
  5. Bovy, J. 2014, ApJ, 795, 95ADSCrossRefGoogle Scholar
  6. Boylan-Kolchin, M., Bullock, J. S., & Kaplinghat, M. 2011, MNRAS, 415, L40ADSCrossRefGoogle Scholar
  7. Bullock, J. S., Stewart, K. R., Kaplinghat, M., Tollerud, E. J., & Wolf, J. 2010, ApJ, 717, 1043ADSCrossRefGoogle Scholar
  8. Carlberg, R. G. 2009, ApJ Lett, 705, L223ADSCrossRefGoogle Scholar
  9. Carlberg, R. G. 2012, ApJ, 748, 20ADSCrossRefGoogle Scholar
  10. Carlberg, R. G., & Grillmair, C. J. 2013, ApJ, 768, 171ADSCrossRefGoogle Scholar
  11. Carlberg, R. G. 2013, ApJ, 775, 90ADSCrossRefGoogle Scholar
  12. Carlberg, R. G. 2014, arXiv:1412.2405Google Scholar
  13. Cooper, A. P., Cole, S., Frenk, C. S., et al. 2010, MNRAS, 406, 744ADSCrossRefGoogle Scholar
  14. Côté, P., McLaughlin, D. E., Cohen, J. G., & Blakeslee, J. P. 2003, ApJ, 591, 850ADSCrossRefGoogle Scholar
  15. Deg, N., & Widrow, L. 2013, MNRAS, 428, 912ADSCrossRefGoogle Scholar
  16. Deg, N., & Widrow, L. 2014, MNRAS, 439, 2678ADSCrossRefGoogle Scholar
  17. Erkal, D., & Belokurov, V. 2015, MNRAS, 450, 1136ADSCrossRefGoogle Scholar
  18. Eyre, A., & Binney, J. 2011, MNRAS, 413, 1852ADSCrossRefGoogle Scholar
  19. Gibbons, S. L. J., Belokurov, V., & Evans, N. W. 2014, MNRAS, 445, 3788ADSCrossRefGoogle Scholar
  20. Gómez, F. A., Helmi, A., Brown, A. G. A., & Li, Y.-S. 2010, MNRAS, 408, 935ADSCrossRefGoogle Scholar
  21. Helmi, A., & White, S. D. M. 1999, MNRAS, 307, 495ADSCrossRefGoogle Scholar
  22. Helmi, A., & de Zeeuw, P. T. 2000, MNRAS, 319, 657ADSCrossRefGoogle Scholar
  23. Helmi, A. 2004, ApJ Lett, 610, L97ADSCrossRefGoogle Scholar
  24. Ibata, R., Lewis, G. F., Irwin, M., Totten, E., & Quinn, T. 2001, ApJ, 551, 294ADSCrossRefGoogle Scholar
  25. Ibata, R. A., Lewis, G. F., Irwin, M. J., & Quinn, T. 2002, MNRAS, 332, 915ADSCrossRefGoogle Scholar
  26. Jing, Y. P., & Suto, Y. 2002, ApJ, 574, 538ADSCrossRefGoogle Scholar
  27. Johnston, K. V. 1998, ApJ, 495, 297ADSCrossRefGoogle Scholar
  28. Johnston, K. V., Zhao, H., Spergel, D. N., & Hernquist, L. 1999a, ApJ Lett, 512, L109ADSCrossRefGoogle Scholar
  29. Johnston, K. V., Majewski, S. R., Siegel, M. H., Reid, I. N., & Kunkel, W. E. 1999b, AJ, 118, 1719ADSCrossRefGoogle Scholar
  30. Johnston, K. V., Sackett, P. D., & Bullock, J. S. 2001, ApJ, 557, 137ADSCrossRefGoogle Scholar
  31. Johnston, K. V., Spergel, D. N., & Haydn, C. 2002, ApJ, 570, 656ADSCrossRefGoogle Scholar
  32. Johnston, K. V., Law, D. R., & Majewski, S. R. 2005, ApJ, 619, 800ADSCrossRefGoogle Scholar
  33. Klypin, A., Kravtsov, A. V., Valenzuela, O., & Prada, F. 1999, ApJ, 522, 82ADSCrossRefGoogle Scholar
  34. Koposov, S. E., Yoo, J., Rix, H.-W., et al. 2009, ApJ, 696, 2179ADSCrossRefGoogle Scholar
  35. Koposov, S. E., Rix, H.-W., & Hogg, D. W. 2010, ApJ, 712, 260ADSCrossRefGoogle Scholar
  36. Küpper, A. H. W., Lane, R. R., & Heggie, D. C. 2012, MNRAS, 420, 2700ADSCrossRefGoogle Scholar
  37. Law, D. R., Johnston, K. V., & Majewski, S. R. 2005, ApJ, 619, 807ADSCrossRefGoogle Scholar
  38. Law, D. R., & Majewski, S. R. 2010, ApJ, 714, 229ADSCrossRefGoogle Scholar
  39. Lux, H., Read, J. I., Lake, G., & Johnston, K. V. 2013, MNRAS, 436, 2386ADSCrossRefGoogle Scholar
  40. Madore, B. F., & Freedman, W. L. 2012, ApJ, 744, 132ADSCrossRefGoogle Scholar
  41. Majewski, S. R., Skrutskie, M. F., Weinberg, M. D., & Ostheimer, J. C. 2003, ApJ, 599, 1082ADSCrossRefGoogle Scholar
  42. Majewski, S. R., Kunkel, W. E., Law, D. R., et al. 2004, AJ, 128, 245ADSCrossRefGoogle Scholar
  43. Moore, B., Ghigna, S., Governato, F., et al. 1999, ApJ Lett, 524, L19ADSCrossRefGoogle Scholar
  44. Navarro, J. F., Frenk, C. S., & White, S. D. M. 1997, ApJ, 490, 493ADSCrossRefGoogle Scholar
  45. Newberg, H. J., Willett, B. A., Yanny, B., & Xu, Y. 2010, ApJ, 711, 32ADSCrossRefGoogle Scholar
  46. Peñarrubia, J., Belokurov, V., Evans, N. W., et al. 2010, MNRAS, 408, L26ADSCrossRefGoogle Scholar
  47. Peñarrubia, J., Koposov, S. E., & Walker, M. G. 2012, ApJ, 760, 2ADSCrossRefGoogle Scholar
  48. Price-Whelan, A. M., & Johnston, K. V. 2013, ApJ Lett, 778, L12ADSCrossRefGoogle Scholar
  49. Price-Whelan, A. M., Hogg, D. W., Johnston, K. V., & Hendel, D. 2014, ApJ, 794, 4ADSCrossRefGoogle Scholar
  50. Rockosi, C. M., Odenkirchen, M., Grebel, E. K., et al. 2002, AJ, 124, 349ADSCrossRefGoogle Scholar
  51. Rubin, V. C., & Ford, Jr., W. K. 1970, ApJ, 159, 379ADSCrossRefGoogle Scholar
  52. Sanders, J. L. 2012, MNRAS, 426, 128ADSCrossRefGoogle Scholar
  53. Sanders, J. L. 2014, MNRAS, 443, 423ADSCrossRefGoogle Scholar
  54. Sanders, J. L., & Binney, J. 2013a, MNRAS, 433, 1813ADSCrossRefGoogle Scholar
  55. Sanders, J. L., & Binney, J. 2013b, MNRAS, 433, 1826ADSCrossRefGoogle Scholar
  56. Sanders, J. L., & Binney, J. 2015, MNRAS, 447, 2479ADSCrossRefGoogle Scholar
  57. Sanderson, R. E., Helmi, A., & Hogg, D. W. 2014, IAU Symposium, 298, 207 (arXiv:1404.6534)ADSGoogle Scholar
  58. Siegal-Gaskins, J. M., & Valluri, M. 2008, ApJ, 681, 40ADSCrossRefGoogle Scholar
  59. Tollerud, E. J., Bullock, J. S., Strigari, L. E., & Willman, B. 2008, ApJ, 688, 277ADSCrossRefGoogle Scholar
  60. Varghese, A., Ibata, R., & Lewis, G. F. 2011, MNRAS, 417, 198ADSCrossRefGoogle Scholar
  61. Vegetti, S., Koopmans, L. V. E., Bolton, A., Treu, T., & Gavazzi, R 2010, MNRAS, 408, 1969ADSCrossRefGoogle Scholar
  62. Yoon, J. H., Johnston, K. V., & Hogg, D. W. 2010, ApJ, 731, 58ADSCrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Columbia UniversityNew YorkUSA
  2. 2.University of TorontoTorontoCanada

Personalised recommendations