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Home All issues Volume 620 (December 2018) A&A, 620 (2018) A27 References
Open Access
Issue
A&A
Volume 620, December 2018
Article Number A27
Number of page(s) 20
Section Galactic structure, stellar clusters and populations
DOI https://doi.org/10.1051/0004-6361/201833042
Published online 26 November 2018
  1. Allison, R. J., Goodwin, S. P., Parker, R. J., et al. 2009, MNRAS, 395, 1449 [Google Scholar]
  2. Ballesteros-Paredes, J., Hartmann, L., & Vázquez-Semadeni, E. 1999, ApJ, 527, 285 [NASA ADS] [CrossRef] [Google Scholar]
  3. Barrow, J. D., Bhavsar, S. P., & Sonoda, D. H. 1985, MNRAS, 216, 17 [NASA ADS] [CrossRef] [MathSciNet] [Google Scholar]
  4. Bastian, N., Covey, K. R., & Meyer, M. R. 2010, ARA&A, 48, 339 [NASA ADS] [CrossRef] [Google Scholar]
  5. Bate, M. R., Bonnell, I. A., & Bromm, V. 2003, MNRAS, 339, 577 [NASA ADS] [CrossRef] [Google Scholar]
  6. Bressert, E., Bastian, N., Gutermuth, R., et al. 2010, MNRAS, 409, L54 [NASA ADS] [Google Scholar]
  7. Cartwright, A., & Whitworth, A. P. 2004, MNRAS, 348, 589 [NASA ADS] [CrossRef] [Google Scholar]
  8. Chapman, N. L., Goldsmith, P. F., Pineda, J. L., et al. 2011, ApJ, 741, 21 [NASA ADS] [CrossRef] [Google Scholar]
  9. Dijkstra, E. W. 1960, Some Theorems On Spanning Subtrees of a Graph : CWI Technical Report Stichting Mathematisch Centrum. [Google Scholar]
  10. Duchêne, G., & Kraus, A. 2013, ARA&A, 51, 269 [Google Scholar]
  11. Elmegreen, B. G., Efremov, Y., Pudritz, R. E., & Zinnecker, H. 2000, Protostars and Planets IV (Tucson: University of Arizona Press), 179 [Google Scholar]
  12. Ester, M., Kriegel, H., Sander, J., & Xu, X. 1996, Proc. Second International Conf. on Knowledge Discovery and Data Mining (Portland, OR: AAAI Press), 226 [Google Scholar]
  13. Everitt, B. S., Landau, S., Leese, M., & Stahl, D. 2011, Cluster Analysis, 5th edn. (New York, NY: John Wiley & Sons) [CrossRef] [Google Scholar]
  14. Farias, J. P., Tan, J. C., & Chatterjee, S. 2017, ApJ, 838, 116 [NASA ADS] [CrossRef] [Google Scholar]
  15. Filippone, M., Camastra, F., Masulli, F., & Rovetta, S. 2008, Pattern Recogn., 41, 176 [CrossRef] [Google Scholar]
  16. Fraley, C., & Raftery, A. E. 1998, Comput. J., 41, 578 [CrossRef] [Google Scholar]
  17. Fraley, C., & Raftery, A. E. 2002, J. Am. Stat. Assoc., 97, 611 [Google Scholar]
  18. Fraley, C., & Raftery, A. E. 2007, J. Classif., 24, 155 [CrossRef] [Google Scholar]
  19. Gladwin, P. P., Kitsionas, S., Boffin, H. M. J., & Whitworth, A. P. 1999, MNRAS, 302, 305 [NASA ADS] [CrossRef] [Google Scholar]
  20. Gomez, M., Hartmann, L., Kenyon, S. J., & Hewett, R. 1993, AJ, 105, 1927 [NASA ADS] [CrossRef] [Google Scholar]
  21. Gower, J. C., & Ross, G. J. S. 1969, Appl. Stat., 18, 54 [CrossRef] [Google Scholar]
  22. Gupta, M. R., & Chen, Y. 2011, Signal Process., 4, 223 [Google Scholar]
  23. Gutermuth, R. A., Megeath, S. T., Myers, P. C., et al. 2009, ApJS, 184, 18 [NASA ADS] [CrossRef] [Google Scholar]
  24. Hacar, A., Tafalla, M., Kauffmann, J., & Kovács, A. 2013, A&A, 554, A55 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  25. Hartigan, J. A. 1975, Clustering Algorithms, 99th edn. (New York, NY: John Wiley & Sons) [Google Scholar]
  26. Hartmann, L. 2002, ApJ, 578, 914 [NASA ADS] [CrossRef] [Google Scholar]
  27. Hartmann, L., & Burkert, A. 2007, ApJ, 654, 988 [NASA ADS] [CrossRef] [Google Scholar]
  28. Hartmann, L., Ballesteros-Paredes, J., & Bergin, E. A. 2001, ApJ, 562, 852 [NASA ADS] [CrossRef] [Google Scholar]
  29. Heithausen, A., Bensch, F., Stutzki, J., Falgarone, E., & Panis, J. F. 1998, A&A, 331, L65 [Google Scholar]
  30. Imai, H., & Inaba, M. 1995, in Proc. of the Third International Congress on Industrial and Applied Mathematics : ICIAM, 1st edn. (New York: John Wiley & Sons), 124 [Google Scholar]
  31. Inaba, M., Katoh, N., & Imai, H. 1994, in Proceedings of the Tenth Annual Symp. on Computational Geometry (New York: ACM), 332 [Google Scholar]
  32. Jain, A. K. 2010, Pattern Recogn. Lett., 31, 651 [Google Scholar]
  33. Joncour, I., Duchêne, G., & Moraux, E. 2017, A&A, 599, A14 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  34. Jones, B. F., & Herbig, G. H. 1979, AJ, 84, 1872 [NASA ADS] [CrossRef] [Google Scholar]
  35. Kanungo, T., Mount, D., Netanyahu, N., et al. 2002, IEEE Trans. Pattern Anal. Mach. Intell., 24, 881 [CrossRef] [Google Scholar]
  36. Kaufman, L., & Rousseeuw, P. J. 2008, Finding Groups in Data: An Introduction to Cluster Analysis (New York: John Wiley & Sons) [Google Scholar]
  37. Kenyon, S. J., Gómez, M., & Whitney, B. A. 2008, in Low Mass Star Formation in the Taurus-Auriga Clouds, ed. B. Reipurth, 405 [Google Scholar]
  38. Kirk, H., & Myers, P. C. 2011, ApJ, 727, 64 [NASA ADS] [CrossRef] [Google Scholar]
  39. Koch, P. M., Tang, Y.-W., Ho, P. T. P., et al. 2018, ApJ, 855, 39 [NASA ADS] [CrossRef] [Google Scholar]
  40. Könyves, V., André, P., Men’shchikov, A., et al. 2015, A&A, 584, A91 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  41. Kramer, C., Stutzki, J., & Winnewisser, G. 1996, A&A, 307, 915 [Google Scholar]
  42. Kraus, A. L., Herczeg, G. J., Rizzuto, A. C., et al. 2017, ApJ, 838, 150 [NASA ADS] [CrossRef] [Google Scholar]
  43. Kraus, A. L., & Hillenbrand, L. A. 2008, ApJ, 686, L111 [NASA ADS] [CrossRef] [Google Scholar]
  44. Krumholz, M. R., Matzner, C. D., & McKee, C. F. 2006, ApJ, 653, 361 [NASA ADS] [CrossRef] [Google Scholar]
  45. Kruskal, J. B. 1956, Proc. Amer. Math. Soc., 7, 48 [CrossRef] [MathSciNet] [Google Scholar]
  46. Kuhn, M. A., Feigelson, E. D., Getman, K. V., et al. 2014, ApJ, 787, 107 [Google Scholar]
  47. Küpper, A. H. W., Maschberger, T., Kroupa, P., & Baumgardt, H. 2011, MNRAS, 417, 2300 [NASA ADS] [CrossRef] [Google Scholar]
  48. Larson, R. B. 1995, MNRAS, 272, 213 [NASA ADS] [Google Scholar]
  49. Lee, C. W., & Myers, P. C. 1999, ApJS, 123, 233 [NASA ADS] [CrossRef] [Google Scholar]
  50. Lee, Y.-N., & Hennebelle, P. 2016, A&A, 591, A30 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  51. Li, H.-B., Fang, M., Henning, T., & Kainulainen, J. 2013, MNRAS, 436, 3707 [NASA ADS] [CrossRef] [Google Scholar]
  52. Liu, T., Wu, Y., & Zhang, H. 2012, ApJS, 202, 4 [NASA ADS] [CrossRef] [Google Scholar]
  53. Luhman, K. L., Allen, P. R., Espaillat, C., Hartmann, L., & Calvet, N. 2010, ApJS, 186, 111 [NASA ADS] [CrossRef] [Google Scholar]
  54. Marks, M., & Kroupa, P. 2012, A&A, 543, A8 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  55. Ménard, F., & Duchêne, G. 2004, A&A, 425, 973 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  56. Mirkin, B. 2005, Clustering For Data Mining: A Data Recovery Approach (London: Chapman & Hall/CRC) [CrossRef] [Google Scholar]
  57. Motte, F., André, P., Ward-Thompson, D., & Bontemps, S. 2001, A&A, 372, L41 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  58. Motte, F., Bontemps, S., & Louvet, F. 2018, ARA&A, in press, DOI: 10.1146/annurev-astro-091916-055235 [Google Scholar]
  59. Murtagh, F., & Contreras, P. 2012, Rev. Data Min. Knowl. Discovery, 2, 86 [CrossRef] [Google Scholar]
  60. Myers, P. C. 2009, ApJ, 700, 1609 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  61. Myers, P. C., Fuller, G. A., Goodman, A. A., & Benson, P. J. 1991, ApJ, 376, 561 [NASA ADS] [CrossRef] [Google Scholar]
  62. Onishi, T., Mizuno, A., Kawamura, A., Tachihara, K., & Fukui, Y. 2002, ApJ, 575, 950 [NASA ADS] [CrossRef] [Google Scholar]
  63. Palmeirim, P., André, P., Kirk, J., et al. 2013, A&A, 550, A38 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  64. Parker, R. J. 2014, MNRAS, 445, 4037 [NASA ADS] [CrossRef] [Google Scholar]
  65. Parker, R. J., & Goodwin, S. P. 2015, MNRAS, 449, 3381 [NASA ADS] [CrossRef] [Google Scholar]
  66. Pfalzner, S., Kirk, H., Sills, A., et al. 2016, A&A, 586, A68 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  67. Pineda, J. E., Offner, S. S. R., Parker, R. J., et al. 2015, Nature, 518, 213 [NASA ADS] [CrossRef] [Google Scholar]
  68. Planck Collaboration Int. XXXII (Adam, R., et al.) 2016, A&A, 586, A135 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  69. Pokhrel, R., Myers, P. C., Dunham, M. M., et al. 2018, ApJ, 853, 5 [NASA ADS] [CrossRef] [Google Scholar]
  70. Prim, R. C. 1957, Bell Syst. Tech. J., 36, 1389 [Google Scholar]
  71. Reipurth, B., & Mikkola, S. 2012, Nature, 492, 221 [Google Scholar]
  72. Sadavoy, S. I., Di Francesco, J., Bontemps, S., et al. 2010, ApJ, 710, 1247 [NASA ADS] [CrossRef] [Google Scholar]
  73. Sadavoy, S. I., & Stahler, S. W. 2017, MNRAS, 469, 3881 [NASA ADS] [CrossRef] [Google Scholar]
  74. Schmalzl, M., Kainulainen, J., Quanz, S. P., et al. 2010, ApJ, 725, 1327 [NASA ADS] [CrossRef] [Google Scholar]
  75. Schmeja, S. 2011, Astron. Nachr., 332, 172 [NASA ADS] [CrossRef] [Google Scholar]
  76. Schmeja, S., Kumar, M. S. N., & Ferreira, B. 2008, MNRAS, 389, 1209 [NASA ADS] [CrossRef] [Google Scholar]
  77. Scott, D. W. 1992, Multivariate Density Estimation: Theory, Practice, and Visualization (New York: John Wiley & Sons) [Google Scholar]
  78. Silverman, B. W. 1986, Density Estimation for Statistics and Data Analysis (London: Chapman & Hall/CRC) [Google Scholar]
  79. Simon, M. 1997, ApJ, 482, L81 [NASA ADS] [CrossRef] [Google Scholar]
  80. Smilgys, R., & Bonnell, I. A. 2017, MNRAS, 472, 4982 [NASA ADS] [CrossRef] [Google Scholar]
  81. Soler, J. D., & Hennebelle, P. 2017, A&A, 607, A2 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  82. Tafalla, M., & Hacar, A. 2015, A&A, 574, A104 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  83. Tan, P.-N., Steinbach, M., & Kumar, V. 2005, Introduction to Data Mining, 1st edn. (Boston: Addison-Wesley) [Google Scholar]
  84. Tan, J. C., Krumholz, M. R., & McKee, C. F. 2006, ApJ, 641, L121 [NASA ADS] [CrossRef] [Google Scholar]
  85. Tokovinin, A. 2017, MNRAS, 468, 3461 [NASA ADS] [CrossRef] [Google Scholar]
  86. Vazquez-Semadeni, E., Gonzalez-Samaniego, A., & Colin, P. 2017, MNRAS, 467, 1313 [Google Scholar]
  87. Wright, N. J., Parker, R. J., Goodwin, S. P., & Drake, J. J. 2014, MNRAS, 438, 639 [NASA ADS] [CrossRef] [Google Scholar]
  88. Xu, R., & Wunsch, D. 2005, IEEE Trans. Neural Networks, 16, 645 [Google Scholar]
  89. Zahn, C. T. 1971, IEEE Trans. Comput., 20, 68 [CrossRef] [Google Scholar]
  90. Zhang, Q., Qiu, K., Girart, J. M., et al. 2014, ApJ, 792, 116 [NASA ADS] [CrossRef] [Google Scholar]

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