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Home All issues Volume 696 (April 2025) A&A, 696 (2025) A130 References
Open Access
Issue
A&A
Volume 696, April 2025
Article Number A130
Number of page(s) 11
Section Numerical methods and codes
DOI https://doi.org/10.1051/0004-6361/202453042
Published online 15 April 2025
  1. Annibali, F., & Tosi, M. 2022, Nat. Astron., 6, 48 [NASA ADS] [CrossRef] [Google Scholar]
  2. Belokurov, V., Zucker, D. B., Evans, N. W., et al. 2006, ApJ, 647, L111 [NASA ADS] [CrossRef] [Google Scholar]
  3. Belokurov, V., Zucker, D. B., Evans, N. W., et al. 2007, ApJ, 654, 897 [Google Scholar]
  4. Belokurov, V., Walker, M. G., Evans, N. W., et al. 2008, ApJ, 686, L83 [NASA ADS] [CrossRef] [Google Scholar]
  5. Bertin, E., & Arnouts, S. 1996, A&AS, 117, 393 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  6. Bullock, J. S. 2010, ArXiv e-prints [arXiv:1009.4505] [Google Scholar]
  7. Bullock, J. S., & Boylan-Kolchin, M. 2017, ARA&A, 55, 343 [Google Scholar]
  8. Byun, W., Sheen, Y.-K., Park, H. S., et al. 2020, ApJ, 891, 18 [NASA ADS] [CrossRef] [Google Scholar]
  9. Cai, J., Yan, Z., Yang, H., et al. 2024, A&A, 687, A15 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  10. Cao, Z., Yi, Z., Pan, J., et al. 2023, AJ, 165, 184 [Google Scholar]
  11. Cerny, W., Pace, A. B., Drlica-Wagner, A., et al. 2021, ApJ, 920, L44 [NASA ADS] [CrossRef] [Google Scholar]
  12. Choque-Challapa, N., Aguerri, J. A. L., Mancera Piña, P. E., et al. 2021, MNRAS, 507, 6045 [NASA ADS] [CrossRef] [Google Scholar]
  13. Collins, M. L. M., Charles, E. J. E., Martínez-Delgado, D., et al. 2022, MNRAS, 515, L72 [NASA ADS] [CrossRef] [Google Scholar]
  14. Crosby, E., Jerjen, H., Müller, O., et al. 2024, MNRAS, 527, 9118 [Google Scholar]
  15. Davies, J. I., Davies, L. J. M., & Keenan, O. C. 2016, MNRAS, 456, 1607 [Google Scholar]
  16. Dey, A., Schlegel, D. J., Lang, D., et al. 2019, AJ, 157, 168 [Google Scholar]
  17. Homma, D., Chiba, M., Komiyama, Y., et al. 2024, PASJ, 76, 733 [NASA ADS] [CrossRef] [Google Scholar]
  18. Hou, Q., Zhou, D., & Feng, J. 2021, in 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 13708 [CrossRef] [Google Scholar]
  19. Karachentsev, I. D., Makarov, D. I., & Kaisina, E. I. 2013, AJ, 145, 101 [Google Scholar]
  20. Klypin, A., Kravtsov, A. V., Valenzuela, O., & Prada, F. 1999, ApJ, 522, 82 [Google Scholar]
  21. Koribalski, B. S., Wang, J., Kamphuis, P., et al. 2018, MNRAS, 478, 1611 [NASA ADS] [CrossRef] [Google Scholar]
  22. Kumar, T., Brennan, R., Mileo, A., & Bendechache, M. 2024, IEEE Access, 12, 187536 [Google Scholar]
  23. La Marca, A., Peletier, R., Iodice, E., et al. 2022, A&A, 659, A92 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  24. LeCun, Y., Bengio, Y., & Hinton, G. 2015, Nature, 521, 436 [Google Scholar]
  25. Li, C., Zhang, Y., Cui, C., et al. 2023, MNRAS, 518, 513 [Google Scholar]
  26. Li, Q., Ma, W., Li, H., et al. 2024, Comp. Electron. Agri., 219, 108752 [Google Scholar]
  27. Liu, S., Qi, L., Qin, H., Shi, J., & Jia, J. 2018, in 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 8759 [CrossRef] [Google Scholar]
  28. Liu, S., Wang, Y., Yu, Q., Liu, H., & Peng, Z. 2022, IEEE Access, 10, 129116 [CrossRef] [Google Scholar]
  29. Madden, S. C. & Cormier, D. 2019, IAU Symp., 344, 240 [Google Scholar]
  30. Martin, N. F., McConnachie, A. W., Irwin, M., et al. 2009, ApJ, 705, 758 [NASA ADS] [CrossRef] [Google Scholar]
  31. Martínez-Delgado, D., Makarov, D., Javanmardi, B., et al. 2021, A&A, 652, A48 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  32. Martínez-Delgado, D., Karim, N., Charles, E. J. E., et al. 2022, MNRAS, 509, 16 [Google Scholar]
  33. Mau, S., Cerny, W., Pace, A. B., et al. 2020, ApJ, 890, 136 [NASA ADS] [CrossRef] [Google Scholar]
  34. McConnachie, A. W., Huxor, A., Martin, N. F., et al. 2008, ApJ, 688, 1009 [NASA ADS] [CrossRef] [Google Scholar]
  35. Müller, O., Jerjen, H., & Binggeli, B. 2015, A&A, 583, A79 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  36. Müller, O., Rejkuba, M., Pawlowski, M. S., et al. 2019, A&A, 629, A18 [Google Scholar]
  37. Mutlu-Pakdil, B., Sand, D. J., Crnojević, D., et al. 2022, ApJ, 926, 77 [NASA ADS] [CrossRef] [Google Scholar]
  38. Park, H. S., Moon, D.-S., Zaritsky, D., et al. 2017, ApJ, 848, 19 [NASA ADS] [CrossRef] [Google Scholar]
  39. Perivolaropoulos, L., & Skara, F. 2022, New A Rev., 95, 101659 [NASA ADS] [CrossRef] [Google Scholar]
  40. Poulain, M., Marleau, F. R., Habas, R., et al. 2021, MNRAS, 506, 5494 [NASA ADS] [CrossRef] [Google Scholar]
  41. Redmon, J., Divvala, S., Girshick, R., & Farhadi, A. 2016, in 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (Los Alamitos, CA, USA: IEEE Computer Society), 779 [CrossRef] [Google Scholar]
  42. Reefe, M., Satyapal, S., Sexton, R. O., et al. 2023, ApJ, 946, L38 [NASA ADS] [CrossRef] [Google Scholar]
  43. Saremi, E., Javadi, A., van Loon, J. T., et al. 2020, ApJ, 894, 135 [Google Scholar]
  44. Shi, J.-H., Qiu, B., Luo, A. L., et al. 2022, MNRAS, 516, 264 [Google Scholar]
  45. Shorten, C., & Khoshgoftaar, T. 2019, J. Big Data, 6, 60 [CrossRef] [Google Scholar]
  46. Sunkara, R., & Luo, T. 2023, in Machine Learning and Knowledge Discovery in Databases, eds. M.-R. Amini, S. Canu, A. Fischer, (Cham: Springer Nature Switzerland), 443 [Google Scholar]
  47. Teeninga, P., Moschini, U., Trager, S. C., & Wilkinson, M. H. F. 2015, in Mathematical Morphology and Its Applications to Signal and Image Processing, eds. J. A. Benediktsson, J. Chanussot, L. Najman, & H. Talbot (Cham: Springer International Publishing), 157 [Google Scholar]
  48. Tolstoy, E. 2003, Ap&SS, 284, 579 [Google Scholar]
  49. Torrealba, G., Koposov, S. E., Belokurov, V., & Irwin, M. 2016, MNRAS, 459, 2370 [NASA ADS] [CrossRef] [Google Scholar]
  50. Torrealba, G., Belokurov, V., Koposov, S. E., et al. 2018, MNRAS, 475, 5085 [NASA ADS] [CrossRef] [Google Scholar]
  51. Torrealba, G., Belokurov, V., Koposov, S. E., et al. 2019, MNRAS, 488, 2743 [NASA ADS] [CrossRef] [Google Scholar]
  52. Venhola, A., Peletier, R., Laurikainen, E., et al. 2018, A&A, 620, A165 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  53. Venhola, A., Peletier, R. F., Salo, H., et al. 2022, A&A, 662, A43 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  54. Wang, C.-Y., Bochkovskiy, A., & Liao, H.-Y. M. 2023, in 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 7464 [CrossRef] [Google Scholar]
  55. Willman, B., Blanton, M. R., West, A. A., et al. 2005a, AJ, 129, 2692 [NASA ADS] [CrossRef] [Google Scholar]
  56. Willman, B., Dalcanton, J. J., Martinez-Delgado, D., et al. 2005b, ApJ, 626, L85 [Google Scholar]
  57. Yang, H., Shi, C., Cai, J., et al. 2022, MNRAS, 517, 5496 [NASA ADS] [CrossRef] [Google Scholar]
  58. Yang, H., Zhou, L., Cai, J., et al. 2023a, MNRAS, 518, 5904 [Google Scholar]
  59. Yang, H.-F., Yin, X.-N., Cai, J.-H., et al. 2023b, Res. Astron. Astrophys., 23, 055006 [CrossRef] [Google Scholar]
  60. Yang, H.-F., Wang, R., Cai, J.-H., et al. 2024, ApJS, 272, 43 [NASA ADS] [CrossRef] [Google Scholar]
  61. Yasir, M., Shanwei, L., Mingming, X., et al. 2024, Appl. Soft Comp., 160, 111704 [Google Scholar]
  62. Yi, Z., Li, J., Du, W., et al. 2022, MNRAS, 513, 3972 [NASA ADS] [CrossRef] [Google Scholar]
  63. Zhou, R., Ferraro, S., White, M., et al. 2023, J. Cosmology Astropart. Phys., 2023, 097 [Google Scholar]

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