Open Access
Issue |
A&A
Volume 696, April 2025
|
|
---|---|---|
Article Number | A214 | |
Number of page(s) | 22 | |
Section | Numerical methods and codes | |
DOI | https://doi.org/10.1051/0004-6361/202453152 | |
Published online | 25 April 2025 |
- Acevedo Barroso, J. A., O’Riordan, C. M., & Clément, B., e. a. 2025, A&A, 697, A14 [Google Scholar]
- Amara, A., de la Bella, L., Birrer, S., et al. 2021, J. Open Source Softw., 6, 3056 [Google Scholar]
- Andika, I. T., Jahnke, K., van der Wel, A., et al. 2023a, ApJ, 943, 150 [NASA ADS] [CrossRef] [Google Scholar]
- Andika, I. T., Suyu, S. H., Cañameras, R., et al. 2023b, A&A, 678, A103 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Astropy Collaboration (Robitaille, T. P., et al.) 2013, A&A, 558, A33 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Astropy Collaboration (Price-Whelan, A. M., et al.) 2018, AJ, 156, 123 [Google Scholar]
- Astropy Collaboration (Price-Whelan, A. M., et al.) 2022, ApJ, 935, 167 [NASA ADS] [CrossRef] [Google Scholar]
- Auger, M., Treu, T., Bolton, A., et al. 2009, ApJ, 705, 1099 [Google Scholar]
- Birrer, S., & Amara, A. 2018, Phys. Dark Universe, 22, 189 [NASA ADS] [CrossRef] [Google Scholar]
- Bolton, A. S., Burles, S., Koopmans, L. V. E., et al. 2008, ApJ, 682, 964 [Google Scholar]
- Buscema, M. 1998, Substance Use Misuse, 33, 233 [CrossRef] [PubMed] [Google Scholar]
- Caminha, G. B., Suyu, S. H., Grillo, C., & Rosati, P. 2022, A&A, 657, A83 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Cañameras, R., Schuldt, S., Suyu, S., et al. 2020, A&A, 644, A163 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Chen, T., Kornblith, S., Norouzi, M., & Hinton, G. 2020a, in Proceedings of Machine Learning Research, 119, Proceedings of the 37th International Conference on Machine Learning, eds. III, H. D., & Singh, A. (PMLR), 1597 [Google Scholar]
- Chen, T., Kornblith, S., Swersky, K., Norouzi, M., & Hinton, G. E. 2020b, in Advances in Neural Information Processing Systems, 33, eds. Larochelle, H., Ranzato, M., Hadsell, R., Balcan, M., & Lin, H. (Curran Associates, Inc.), 22243 [Google Scholar]
- Christ, C., Nord, B., Gozman, K., & Ottenbreit, K. 2020, in American Astronomical Society Meeting Abstracts, 235, 303.03 [Google Scholar]
- Collett, T. E. 2015, ApJ, 811, 20 [NASA ADS] [CrossRef] [Google Scholar]
- Collett, T. E., & Auger, M. W. 2014, MNRAS, 443, 969 [NASA ADS] [CrossRef] [Google Scholar]
- Cropper, M., Pottinger, S., Niemi, S., et al. 2016, in Space Telescopes and Instrumentation 2016: Optical, Infrared, and Millimeter Wave, 9904, eds. MacEwen, H. A., Fazio, G. G., Lystrup, M., Batalha, N., Siegler, N., & Tong, E. C. (SPIE) [Google Scholar]
- Cuillandre, J.-C., Bertin, E., Bolzonella, M., et al. 2025a, A&A, 697, A6 [Google Scholar]
- Cuillandre, J. C., Bolzonella, M., Boselli, A., et al. 2025b, A&A, 697, A11 [Google Scholar]
- Davies, A., Serjeant, S., & Bromley, J. M. 2019, MNRAS, 487, 5263 [NASA ADS] [CrossRef] [Google Scholar]
- de Jong, J. T., Verdoes Kleijn, G. A., Kuijken, K. H., & Valentijn, E. A. 2013, Exp. Astron., 35, 25 [NASA ADS] [CrossRef] [Google Scholar]
- Denzel, P., Mukherjee, S., & Saha, P. 2021, MNRAS, 506, 1815 [Google Scholar]
- Domínguez Sánchez, H., Huertas-Company, M., Bernardi, M., Tuccillo, D., & Fischer, J. L. 2018, MNRAS, 476, 3661 [Google Scholar]
- Euclid Collaboration (Schirmer, M., et al.) 2022, A&A, 662, A92 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Euclid Collaboration (Ilic´, S., et al.) 2022, A&A, 657, A91 [CrossRef] [EDP Sciences] [Google Scholar]
- Euclid Collaboration (Scaramella, R., et al.) 2022, A&A, 662, A112 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Euclid Collaboration (Aussel, B., et al.) 2024, A&A, 689, A274 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Euclid Collaboration (Leuzzi, L., et al.) 2024, A&A, 681, A68 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Euclid Collaboration (Castander, F., et al.) 2025, A&A, 697, A5 [Google Scholar]
- Euclid Collaboration (Cropper, M., et al.) 2025, A&A, 697, A2 [Google Scholar]
- Euclid Collaboration (Jahnke, K., et al.) 2025, A&A, 697, A3 [Google Scholar]
- Euclid Collaboration (Mellier, Y., et al.) 2025, A&A, 697, A1 [Google Scholar]
- European Space Agency 2024, Euclid Early Release Observations, https://doi.org/10.57780/esa-qmocze3 [Google Scholar]
- Faber, S., & Jackson, R. E. 1976, ApJ, 204, 668 [NASA ADS] [CrossRef] [Google Scholar]
- Gentile, F., Tortora, C., Covone, G., et al. 2022, MNRAS, 510, 500 [Google Scholar]
- Harris, C. R., Millman, K. J., van der Walt, S. J., et al. 2020, Nature, 585, 357 [NASA ADS] [CrossRef] [Google Scholar]
- Hayat, M. A., Stein, G., Harrington, P., Lukic´, Z., & Mustafa, M. 2021, ApJ, 911, L33 [NASA ADS] [CrossRef] [Google Scholar]
- He, K., Zhang, X., Ren, S., & Sun, J. 2016, in Proceedings of the IEEE conference on computer vision and pattern recognition, 770 [Google Scholar]
- He, K., Gkioxari, G., Dollár, P., & Girshick, R. 2017, in 2017 IEEE International Conference on Computer Vision (ICCV), 2980 [Google Scholar]
- He, K., Fan, H., Wu, Y., Xie, S., & Girshick, R. 2020, in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) [Google Scholar]
- Hecht-Nielsen, R. 1992, in Neural Networks for Perception (Elsevier), 65 [CrossRef] [Google Scholar]
- Howard, A., Sandler, M., Chu, G., et al. 2019, in Proceedings of the IEEE/CVF International Conference on Computer Vision, 1314 [Google Scholar]
- Hu, J., Shen, L., & Sun, G. 2018, in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 7132 [Google Scholar]
- Huang, G., Liu, Z., Van Der Maaten, L., & Weinberger, K. Q. 2017, in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 4700 [Google Scholar]
- Huertas-Company, M., Guo, Y., Ginzburg, O., et al. 2020, MNRAS, 499, 814 [NASA ADS] [CrossRef] [Google Scholar]
- Huertas-Company, M., Sarmiento, R., & Knapen, J. H. 2023, RAS Tech. Instrum., 2, 441 [NASA ADS] [CrossRef] [Google Scholar]
- Hunter, J. D. 2007, Comput. Sci. Eng., 9, 90 [NASA ADS] [CrossRef] [Google Scholar]
- Jacobs, C., Glazebrook, K., Qin, A., & Collett, T. 2022, Astron. Comput., 38, 100535 [NASA ADS] [CrossRef] [Google Scholar]
- Kingma, D. P., & Ba, J. 2015, in 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7-9, 2015, Conference Track Proceedings, eds. Bengio, Y., & LeCun, Y. [Google Scholar]
- Koopmans, L. V. E., Bolton, A., Treu, T., et al. 2009, ApJ, 703, L51 [NASA ADS] [CrossRef] [Google Scholar]
- Lanusse, F., Ma, Q., Li, N., et al. 2018, MNRAS, 473, 3895 [Google Scholar]
- Laureijs, R., Amiaux, J., Arduini, S., et al. 2011, arXiv e-prints [arXiv:1110.3193] [Google Scholar]
- LeCun, Y., Boser, B., Denker, J. S., et al. 1989, Neural Computat., 1, 541 [CrossRef] [Google Scholar]
- Lehar, J., Falco, E. E., Kochanek, C. S., et al. 2000, ApJ, 536, 584 [NASA ADS] [CrossRef] [Google Scholar]
- Li, R., Shu, Y., & Wang, J. 2018, MNRAS, 480, 431 [NASA ADS] [CrossRef] [Google Scholar]
- Li, R., Napolitano, N. R., Tortora, C., et al. 2020, ApJ, 899, 30 [Google Scholar]
- Li, R., Napolitano, N. R., Spiniello, C., et al. 2021, ApJ, 923, 16 [NASA ADS] [CrossRef] [Google Scholar]
- Li, T., Collett, T. E., Krawczyk, C. M., & Enzi, W. 2024, MNRAS, 527, 5311 [Google Scholar]
- Limousin, M., Kneib, J.-P., & Natarajan, P. 2005, MNRAS, 356, 309 [Google Scholar]
- Manjón-García, A. 2021, PhD thesis, University of Cantabria (Spain) [Google Scholar]
- Masters, K. L. 2019, Proc. Int. Astron. Union, 14, 205 [CrossRef] [Google Scholar]
- Meneghetti, Bartelmann, M., Dolag, K., et al. 2005, A&A, 442, 413 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Metcalf, Meneghetti, M., Avestruz, C., et al. 2019, A&A, 625, A119 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Miralda-Escude, J. 1991, ApJ, 370, 1 [Google Scholar]
- Möller, O., Natarajan, P., Kneib, J.-P., & Blain, A. 2002, ApJ, 573, 562 [Google Scholar]
- More, A., Cañameras, R., Jaelani, A. T., et al. 2024, MNRAS, 533, 525 [CrossRef] [Google Scholar]
- Nagam, B., Koopmans, L. V. E., Valentijn, E. A., et al. 2023, MNRAS, 523, 4188 [NASA ADS] [CrossRef] [Google Scholar]
- Nagam, B., Koopmans, L. V. E., Valentijn, E. A., et al. 2024, MNRAS, 533, 1426 [Google Scholar]
- Newton, E. R., Marshall, P. J., Treu, T., et al. 2011, ApJ, 734, 104 [NASA ADS] [CrossRef] [Google Scholar]
- Nord, B., Buckley-Geer, E., Lin, H., et al. 2016, ApJ, 827, 51 [NASA ADS] [CrossRef] [Google Scholar]
- O’Riordan, C. M., Oldham, L. J., Nersesian, A., et al. 2025, A&A, 694, A145 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Petrillo, C. E., Tortora, C., Chatterjee, S., et al. 2017, MNRAS, 472, 1129 [Google Scholar]
- Petrillo, C. E., Tortora, C., Chatterjee, S., et al. 2019a, MNRAS, 482, 807 [NASA ADS] [Google Scholar]
- Petrillo, C. E., Tortora, C., Vernardos, G., et al. 2019b, MNRAS, 484, 3879 [Google Scholar]
- Pourrahmani, M., Nayyeri, H., & Cooray, A. 2018, ApJ, 856, 68 [NASA ADS] [CrossRef] [Google Scholar]
- Powell, D. M., Vegetti, S., McKean, J. P., et al. 2023, MNRAS, 524, L84 [NASA ADS] [CrossRef] [Google Scholar]
- Radosavovic, I., Johnson, J., Xie, S., Lo, W.-Y., & Dollar, P. 2020, in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 10428 [Google Scholar]
- Rezaei, S., McKean, J. P., Biehl, M., de Roo, W., & Lafontaine, A. 2022, MNRAS, 517, 1156 [NASA ADS] [CrossRef] [Google Scholar]
- Ronneberger, O., Fischer, P., & Brox, T. 2015, in International Conference on Medical image computing and computer-assisted intervention (Springer), 234 [Google Scholar]
- Schaefer, C., Geiger, M., Kuntzer, T., & Kneib, J.-P. 2018, A&A, 611, A2 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Scoville, N., Aussel, H., Brusa, M., et al. 2007, ApJS, 172, 1 [Google Scholar]
- Shu, Y., Brownstein, J. R., Bolton, A. S., et al. 2017, ApJ, 851, 48 [Google Scholar]
- Simonyan, K., & Zisserman, A. 2015, in 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7-9, 2015, Conference Track Proceedings [Google Scholar]
- Spiniello, C., Barnabè, M., Koopmans, L. V. E., & Trager, S. C. 2015, MNRAS, 452, L21 [Google Scholar]
- Stein, G., Blaum, J., Harrington, P., Medan, T., & Lukic´, Z. 2022, ApJ, 932, 107 [NASA ADS] [CrossRef] [Google Scholar]
- Storfer, C., Huang, X., Gu, A., et al. 2022, ApJ, submitted [arXiv:2206:02764] [Google Scholar]
- Suyu, S. H., Marshall, P. J., Auger, M. W., et al. 2010, ApJ, 711, 201 [Google Scholar]
- Szegedy, C., Liu, Wei, Jia, Yangqing, et al. 2015, in Proceedings of the IEEE conference on computer vision and pattern recognition, 1 [Google Scholar]
- Szegedy, C., Vanhoucke, V., Ioffe, S., Shlens, J., & Wojna, Z. 2016, in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2818 [Google Scholar]
- Tan, M., & Le, Q. 2019, in Proceedings of the 36th International Conference on Machine Learning, 97, eds. Chaudhuri, K., & Salakhutdinov, R. (PMLR), 6105 [Google Scholar]
- Tan, M., & Le, Q. 2021, in Proceedings of Machine Learning Research, 139, Proceedings of the 38th International Conference on Machine Learning, eds. Meila, M., & Zhang, T. (PMLR), 10096 [Google Scholar]
- Teimoorinia, H., Bluck, A. F., & Ellison, S. L. 2016, MNRAS, 457, 2086 [NASA ADS] [CrossRef] [Google Scholar]
- Thuruthipilly, H., Zadrozny, A., Pollo, A., & Biesiada, M. 2022, A&A, 664, A4 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Treu, T., & Koopmans, L. V. E. 2002, ApJ, 575, 87 [NASA ADS] [CrossRef] [Google Scholar]
- van den Oord, A., Li, Y., & Vinyals, O. 2018, arXiv e-prints [arXiv:1807.03748] [Google Scholar]
- Vegetti, S., Birrer, S., Despali, G., et al. 2024, Space Sci. Rev., 220, 58 [CrossRef] [Google Scholar]
- Walmsley, M., Scaife, A. M. M., Lintott, C., et al. 2022, MNRAS, 513, 1581 [NASA ADS] [CrossRef] [Google Scholar]
- Walmsley, M., Allen, C., Aussel, B., et al. 2023, J. Open Source Softw., 8, 5312 [NASA ADS] [CrossRef] [Google Scholar]
- Wilde, J., Serjeant, S., Bromley, J. M., et al. 2022, MNRAS, 512, 3464 [Google Scholar]
- Wilde, J. W. 2023, PhD thesis, The Open University, https://oro.open.ac.uk/94777/ [Google Scholar]
- Willett, K. W., Lintott, C. J., Bamford, S. P., et al. 2013, MNRAS, 435, 2835 [Google Scholar]
- Xie, S., Girshick, R. B., Dollár, P., Tu, Z., & He, K. 2016, in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 5987 [Google Scholar]
- You, K., Kou, Z., Long, M., & Wang, J. 2020, in Neural Information Processing Systems [Google Scholar]
- Zitrin, A., Rosati, P., Nonino, M., et al. 2012, ApJ, 749, 97 [NASA ADS] [CrossRef] [Google Scholar]
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