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Reionization with Simba: How much does astrophysics matter in modeling cosmic reionization?

, , , , , , , and . (2021)cite arxiv:2109.03840Comment: 13 pages, 7figures, submitted to ApJ.

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Multifield Cosmology with Artificial Intelligence, , , , , , , , , and 3 other author(s). (2021)cite arxiv:2109.09747Comment: 11 pages, 7 figures. First paper of a series of four. All 2D maps, codes, and networks weights publicly available at https://camels-multifield-dataset.readthedocs.io.Robust marginalization of baryonic effects for cosmological inference at the field level, , , , , , , , , and 4 other author(s). (2021)cite arxiv:2109.10360Comment: 7 pages, 4 figures. Second paper of a series of four. The 2D maps, codes, and network weights used in this paper are publicly available at https://camels-multifield-dataset.readthedocs.io.Can galaxy evolution mimic cosmic reionization?, and . (2020)cite arxiv:2010.00023Comment: to be submitted to ApJ, comments are welcome.ICE: an iterative combinatorial exchange., , , , , , , , and . EC, page 249-258. ACM, (2005)Reionization with Simba: How much does astrophysics matter in modeling cosmic reionization?, , , , , , , and . (2021)cite arxiv:2109.03840Comment: 13 pages, 7figures, submitted to ApJ.Towards out-of-distribution generalization in large-scale astronomical surveys: robust networks learn similar representations., , , and . CoRR, (2023)The CAMELS project: Cosmology and Astrophysics with MachinE Learning Simulations, , , , , , , , , and 11 other author(s). (2020)cite arxiv:2010.00619Comment: 33 pages, 18 figures, CAMELS webpage at https://www.camel-simulations.org.Hybrid analytic and machine-learned baryonic property insertion into galactic dark matter haloes, , , , and . (2020)cite arxiv:2012.05820Comment: 13 pages, 8 figures, preprint submitted to MNRAS.Bridging the Gap between Cosmic Dawn and Reionization favors Faint Galaxies-dominated Models, , , , , , and . (2022)cite arxiv:2209.14312Comment: 12 pages, 5 figures, submitted to ApJ, comments are welcome.Emulating cosmological multifields with generative adversarial networks, , and . (2022)cite arxiv:2211.05000Comment: 6 pages, 3 figures, Accepted at the Workshop on Machine Learning and the Physical Sciences, Neural Information Processing Systems (NeurIPS) 2022.