D. Muñoz, N. Stone, C. Petrovich, and F. Rasio. (2022)cite arxiv:2204.06002Comment: 15 pages (before references and appendices), 11 figures, comments welcome.
J. Lewis, P. Ocvirk, Y. Dubois, D. Aubert, J. Chardin, N. Gillet, and É. Thélie. (2022)cite arxiv:2204.03949Comment: submitted to MNRAS, 1st report received: under revision Have partially addressed referee's concerns, namely that the model predicts high dust masses and redder bright galaxies than expected, by discussing this aspect around the relevant results. Work is being carried out to present a clearer parameter exploration of the dust model.
U. Schmitt, B. Moser, C. Lorenz, and A. Refregier. (2022)cite arxiv:2203.11945Comment: 28 pages, 5 figures, 5 tables, Link to package: https://cosmology.ethz.ch/research/software-lab/sympy2c.html, the described packaged sympy2c is used within arXiv:2112.08395.
M. Xiang, and H. Rix. (2022)cite arxiv:2203.12110Comment: 20 pages, 9 figures. Published in Nature in the issue of March 24, 2022. url: https://www.nature.com/articles/s41586-022-04496-5. This is the authors' version before final edits.
S. Menon, C. Federrath, M. Krumholz, R. Kuiper, B. Wibking, and M. Jung. (2022)cite arxiv:2203.12177Comment: 7 pages, 2 figures, to appear in the proceedings of IAUS362: The predictive power of computational astrophysics as discovery tool (D. Bisikalo, T. Hanawa, C. Boily, J. Stone, eds.). arXiv admin note: substantial text overlap with arXiv:2202.08778.
S. Cunnington. (2022)cite arxiv:2202.13828Comment: 18 pages, 10 figures. See Fig 4 for main forecast of turnover detection for different HI IM surveys. See Fig 7 for constraints possible on turnover scale and Fig 8 for demo of how this can be used for cosmology. Accepted for publication in MNRAS.