Possibilities of identifying members from Milky Way satellite galaxies using unsupervised machine learning algorithms
Tóm tắt
A detailed study of stellar populations in Milky Way (MW) satellite galaxies remains an observational challenge due to their faintness and fewer spectroscopically confirmed member stars. We use unsupervised machine learning methods to identify new members for nine nearby MW satellite galaxies using Gaia data release-3 (Gaia DR3) astrometry, the Dark Energy Survey (DES) and the DECam Local Volume Exploration Survey (DELVE) photometry. Two density-based clustering algorithms, DBSCAN and HDBSCAN, have been used in the four-dimensional astrometric parameter space (
$$\alpha _{2016}$$
,
$$\delta _{2016}$$
,
$$\mu _{\alpha } \cos \delta $$
,
$$\mu _\delta $$
) to identify member stars belonging to MW satellite galaxies. Our results indicate that we can recover more than 80% of the known spectroscopically confirmed members in most satellite galaxies and also reject 95–100% of spectroscopic non-members. We have also added many new members using this method. We compare our results with previous studies using photometric and astrometric data and discuss the suitability of density-based clustering methods for MW satellite galaxies.
Tài liệu tham khảo
Abbott T. M. C., Adamów M., Aguena M. et al. 2021, ApJS, 255, 20
Abdallah H., Adam R., Aharonian F. et al. 2020, Phys. Rev. D, 102, 062001
Acciari V. A., Ansoldi S., Antonelli L. A. et al. 2022, Phys. Dark Universe, 35, 100912
Astropy Collaboration, Robitaille T. P., Tollerud E. J. et al. 2013, A &A, 558, A33
Ball N. M., Brunner R. J. 2010, Int. J. Mod. Phys. D, 19, 1049
Baron D. 2019, arXiv e-prints, arXiv:1904.07248
Baron D., Poznanski D. 2017, MNRAS, 465, 4530
Battaglia G., Taibi S., Thomas G. F., Fritz T. K. 2022, A &A, 657, A54
Bechtol K., Drlica-Wagner A., Balbinot E. et al. 2015, ApJ, 807, 50
Brown T. M., Tumlinson J., Geha M. et al. 2014, ApJ, 796, 91
Bruce J., Li T. S., Pace A. B. et al. 2023, arXiv e-prints, arXiv:2302.03708
Bullock J. S., Johnston K. V. 2005, ApJ, 635, 931
Campello R. J. G. B., Moulavi D., Sander J. 2013, in eds Pei J., Tseng V. S., Cao L., Motoda H., Xu G., Advances in Knowledge Discovery and Data Mining (Berlin, Heidelberg: Springer) p. 160
Carlin J. L., Grillmair C. J., Muñoz R. R., Nidever D. L., Majewski S. R. 2009, Astrophys. J., 702, L9
Carlin J. L., Sand D. J. 2018, ApJ, 865, 7
Casagrande L., VandenBerg D. A. 2014, MNRAS, 444, 392
Castro-Ginard A., Jordi C., Luri X. et al. 2022, A &A, 661, A118
Cerny W., Pace A. B., Drlica-Wagner A. et al. 2021, ApJ, 910, 18
Cerny W., Simon J. D., Li T. S. et al. 2023, ApJ, 942, 111
Chambers K. C., Magnier E. A., Metcalfe N. et al. 2016, arXiv e-prints, arXiv:1612.05560
Dall’Ora M., Clementini G., Kinemuchi K. et al. 2006, ApJL, 653, L109
Diehl H. T., Abbott T. M. C., Annis J. et al. 2014, in eds Peck A. B., Benn C. R., Seaman R. L., Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 9149, Observatory Operations: Strategies, Processes and Systems V, 91490V
Drlica-Wagner A., Bechtol K., Rykoff E. S. et al. 2015, ApJ, 813, 109
Drlica-Wagner A., Bechtol K., Allam S. et al. 2016, ApJL, 833, L5
Drlica-Wagner A., Ferguson P. S., Adamów M. et al. 2022, ApJS, 261, 38
Elvin-Poole J., Crocce M., Ross A. J. et al. 2018, Phys. Rev. D, 98, 042006
Ester M., Kriegel H.-P., Sander J., Xu X. 1996, AAAI, 226
Fabricius C., Luri X., Arenou F. et al. 2021, A &A, 649, A5
Fellhauer M., Wilkinson M. I., Evans N. W. et al. 2008, MNRAS, 385, 1095
Flaugher B., Diehl H. T., Honscheid K. et al. 2015, AJ, 150, 150
Frebel A., Bromm V. 2012, ApJ, 759, 115
Frebel A., Simon J. D., Kirby E. N. 2014, ApJ, 786, 74
Fritz T. K., Battaglia G., Pawlowski M. S. et al. 2018, A &A, 619, A103
Gaia Collaboration, Helmi A., van Leeuwen F. et al. 2018a, A &A, 616, A12
Gaia Collaboration, Brown A. G. A., Vallenari A. et al. 2018b, A &A, 616, A1
Gaia Collaboration, Vallenari, A., Brown, A. G. A. et al. 2022, arXiv:2208.00211
Green G. 2018, J. Open Source Softw., 3, 695
Grillmair C. J. 2009, ApJ, 693, 1118
Hargis J. R., Willman B., Peter A. H. G. 2014, ApJL, 795, L13
Homma D., Chiba M., Okamoto S. et al. 2016, ApJ, 832, 21
Homma D., Chiba M., Okamoto S. et al. 2018, PASJ, 70, S18
Jenkins S. A., Li T. S., Pace A. B. et al. 2021, ApJ, 920, 92
Ji A. P., Frebel A., Chiti A., Simon J. D. 2016, Nature, 531, 610
Ji A. P., Li T. S., Simon J. D. et al. 2020, ApJ, 889, 27
Kallivayalil N., Sales L. V., Zivick P. et al. 2018, ApJ, 867, 19
Kauffmann G., White S. D. M., Guiderdoni B. 1993, MNRAS, 264, 201
Kim D., Jerjen H. 2015, ApJL, 808, L39
Kim D., Jerjen H., Mackey D., Da Costa G. S., Milone A. P. 2015, ApJL, 804, L44
Kim S. Y., Peter A. H. G., Hargis J. R. 2018, PRL, 121, 211302
Kirby E. N., Cohen J. G., Guhathakurta P. et al. 2013, ApJ, 779, 102
Klypin A., Kravtsov A. V., Valenzuela O., Prada F. 1999, ApJ, 522, 82
Koch A., Wilkinson M. I., Kleyna J. T. et al. 2009, ApJ, 690, 453
Koposov S., Belokurov V., Evans N. W. et al. 2008, ApJ, 686, 279
Koposov S. E., Belokurov V., Torrealba G., Evans N. W. 2015a, ApJ, 805, 130
Koposov S. E., Casey A. R., Belokurov V. et al. 2015b, ApJ, 811, 62
Koposov S. E., Walker M. G., Belokurov V. et al. 2018, MNRAS, 479, 5343
Kravtsov A. V., Klypin A. A., Bullock J. S., Primack J. R. 1998, ApJ, 502, 48
Laevens B. P. M., Martin N. F., Ibata R. A. et al. 2015, ApJL, 802, L18
Laevens B. P. M., Martin N. F., Bernard E. J. et al. 2015, ApJ, 813, 44
Li H., Hammer F., Babusiaux C. et al. 2021, ApJ, 916, 8
Li T. S., Simon J. D., Pace A. B. et al. 2018a, ApJ, 857, 145
Li T. S., Simon J. D., Kuehn K. et al. 2018b, ApJ, 866, 22
Lindegren L., Klioner S. A., Hernández J. et al. 2021, A &A, 649, A2
Longeard N., Jablonka P., Arentsen A. et al. 2022, MNRAS, 516, 2348
MacQueen J. B. 1967, in eds Cam L. M. L., Neyman J. 1, Proceedings of the fifth Berkeley Symposium on Mathematical Statistics and Probability, Vol. 1, University of California Press, p. 281
Manwadkar V., Kravtsov A. V. 2022, MNRAS, 516, 3944
Martin N. F., Ibata R. A., Chapman S. C., Irwin M., Lewis G. F. 2007, MNRAS, 380, 281
Martínez-García A. M., del Pino A., Aparicio A., van der Marel R. P., Watkins L. L. 2021, MNRAS, 505, 5884
Massari D., Helmi A. 2018, A &A, 620, A155
Mau S., Cerny W., Pace A. B. et al. 2020, ApJ, 890, 136
McConnachie A. W., Venn K. A. 2020a, ApJ, 160, 124
McConnachie A. W., Venn K. A. 2020b, Res. Notes Am. Astron. Soc., 4, 229
McInnes L., Healy J. 2017, IEEE, https://doi.org/10.1109/icdmw.2017.12
McLachlan G. J., Peel D. 2000, Finite mixture models (New York: Wiley Series in Probability and Statistics)
Moore B., Ghigna S., Governato F. et al. 1999, ApJ, 524, L19
Muñoz R. R., Carlin J. L., Frinchaboy P. M. et al. 2006, ApJ, 650, L51
Muñoz R. R., Côté P., Santana F. A. et al. 2018, ApJ, 860, 66
Nadler E. O., Wechsler R. H., Bechtol K. et al. 2020, ApJ, 893, 48
Newton O., Cautun M., Jenkins A., Frenk C. S., Helly J. C. 2018, MNRAS, 479, 2853
Nidever D. L., Dey A., Fasbender K. et al. 2021, AJ, 161, 192
Odewahn S. C., Stockwell E. B., Pennington R. L., Humphreys R. M., Zumach W. A. 1992, AJ, 103, 318
Pace A. B., Erkal D., Li T. S. 2022, ApJ, 940, 136
Pace A. B., Li T. S. 2019, ApJ, 875, 77
Pasquato M., Milone A. 2019, arXiv e-prints, arXiv:1906.04983
Pietrinferni A., Hidalgo S., Cassisi S. et al. 2021, ApJ, 908, 102
Reis I., Rotman M., Poznanski D., Prochaska J., Wolf L. 2021, Astron. Comput., 34, 100437
Rey M. P., Pontzen A., Agertz O. et al. 2019, ApJL, 886, L3
Roderick T. A., Mackey A. D., Jerjen H., DaCosta G. S. 2016, MNRAS, 461, 3702
Rubin A., Gal-Yam A. 2016, ApJ, 828, 111
Sales L. V., Navarro J. F., Kallivayalil N., Frenk C. S. 2017, MNRAS, 465, 1879
Schlegel D. J., Finkbeiner D. P., Davis M. 1998, ApJ, 500, 525
Simon J. D. 2018, ApJ, 863, 89
Simon J. D., Drlica-Wagner A., Li T. S. et al. 2015, ApJ, 808, 95
Simon J. D., Li T. S., Drlica-Wagner A. et al. 2017, ApJ, 838, 11
Simon J. D., Li T. S., Erkal D. et al. 2020, ApJ, 892, 137
Taylor M. 2011, TOPCAT: Tool for Operations on Catalogues and Tables Astrophysics Source Code Library, record ascl:1101.010, ascl:1101.010
Tollerud E. J., Bullock J. S., Strigari L. E., Willman B. 2008, ApJ, 688, 277
Torrealba G., Belokurov V., Koposov S. E. et al. 2018, MNRAS, 475, 5085
Vasconcellos E. C., de Carvalho R. R., Gal R. R. et al. 2011, AJ, 141, 189
Vitral E. 2021, MNRAS, 504, 1355
Waller F., Venn K., Sestito F. et al. 2022, arXiv e-prints, arXiv:2208.07948
Walsh S. M., Willman B., Sand D., et al. 2008, ApJ, 688, 245.
Weir N., Fayyad U. M., Djorgovski S. 1995, AJ, 109, 2401
Weisz D. R., Dolphin A. E., Skillman E. D. et al. 2015, ApJ, 804, 136
York D. G., Adelman J., Anderson John E. J. et al. 2000, AJ, 120, 1579