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Early structure formation in the THESAN radiation-magneto-hydrodynamics simulations

Published online by Cambridge University Press:  20 January 2023

E. Garaldi Open the ORCID record for E. Garaldi [Opens in a new window] ,
R. Kannan ,
A. Smith ,
V. Springel ,
R. Pakmor ,
M. Vogelsberger  and
L. Hernquist
E. Garaldi
Affiliation:
Max-Planck Institute for Astrophysics, Karl-Schwarzschild-Str. 1, D-85741 Garching, Germany
R. Kannan
Affiliation:
Center for Astrophysics Harvard Smithsonian, 60 Garden Street, Cambridge, MA 02138, USA
A. Smith
Affiliation:
Department of Physics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
V. Springel
Affiliation:
Max-Planck Institute for Astrophysics, Karl-Schwarzschild-Str. 1, D-85741 Garching, Germany
R. Pakmor
Affiliation:
Max-Planck Institute for Astrophysics, Karl-Schwarzschild-Str. 1, D-85741 Garching, Germany
M. Vogelsberger
Affiliation:
Department of Physics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
L. Hernquist
Affiliation:
Center for Astrophysics Harvard Smithsonian, 60 Garden Street, Cambridge, MA 02138, USA
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Abstract

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The formation of the first galaxies in the Universe is the new frontier of both galaxy formation and reionization studies. This creates a fierce new challenge, i.e. to simultaneously understand in a unique and coherent picture the processes of galaxy formation and reionization, and – crucially – their connection. To this end, we present the thesan suite of cosmological radiation-magneto-hydrodynamical simulations. They are unique since they: (i) cover a very broad range of spatial and temporal scales; (ii) include an unprecedentedly-broad range of physical processes for simulations of such scales and resolution; (iii) exploit knowledge accumulated at low redshift to minimize the number of free parameters in the physical model; (iv) use a variance-suppression technique in the production of initial conditions to increase their statistical fidelity. Finally, the thesan suite includes multiple runs of the same initial conditions, exploring current unknowns in the physics of dark matter and ionizing sources.

Keywords

galaxies: high-redshiftcosmology: large-scale structure of universeradiative transfermethods: numerical
Type
Contributed Paper
Information
Proceedings of the International Astronomical Union , Volume 16 , Symposium S362: The Predictive Power of Computational Astrophysics as a Discovery Tool , June 2020 , pp. 1 - 7
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of International Astronomical Union

Footnotes

†

NHFP Einstein Fellow.

References

Ota, K., et al., 2008, ApJ, 677, 12 CrossRefGoogle Scholar
Ono, Y., et al., 2012, ApJ, 744, 83 10.1088/0004-637X/744/2/83CrossRefGoogle Scholar
Pentericci, L., et al., 2014, ApJ, 793, 113 CrossRefGoogle Scholar
Choudhury, T. R., Puchwein, E., Haehnelt, M. G., Bolton, J. S., 2015, MNRAS, 452, 261 CrossRefGoogle Scholar
Tilvi, V., et al., 2014, ApJ, 794, 5 10.1088/0004-637X/794/1/5CrossRefGoogle Scholar
Mesinger, A., Aykutalp, A., Vanzella, E., Pentericci, L., Ferrara, A., Dijkstra, M., 2014, MNRAS, 446, 566 Google Scholar
McGreer, I. D., Mesinger, A., Fan, X., 2011, MNRAS, 415, 3237 CrossRefGoogle Scholar
McGreer, I. D., Mesinger, A., D’Odorico, V., 2015, MNRAS, 447, 499 10.1093/mnras/stu2449CrossRefGoogle Scholar
Lu, T.-Y., et al., 2020, ApJ, 893, 69 10.3847/1538-4357/ab7db7CrossRefGoogle Scholar
Totani, T., Kawai, N., Kosugi, G., Aoki, K., Yamada, T., Iye, M., Ohta, K., Hattori, T., 2006, PASJ, 58, 485 CrossRefGoogle Scholar
Chornock, R., Berger, E., Fox, D. B., Lunnan, R., Drout, M. R., Fong, W.-F., Laskar, T., Roth, K. C., 2013, ApJ, 774, 2610.1088/0004-637X/774/1/26CrossRefGoogle Scholar
Bolton, J. S., Becker, G. D., Raskutti, S., Wyithe, J. S. B., Haehnelt, M. G., Sargent, W. L. W., 2012, MNRAS, 419, 2880 10.1111/j.1365-2966.2011.19929.xCrossRefGoogle Scholar
Mortlock, D. J., et al., 2011, Nature, 474, 616 10.1038/nature10159CrossRefGoogle Scholar
Schroeder, J., Mesinger, A., Haiman, Z., 2013, MNRAS, 428, 3058 CrossRefGoogle Scholar
Greig, B., Mesinger, A., Haiman, Z., Simcoe, R. A., 2017, MNRAS, 466, 4239 CrossRefGoogle Scholar
Greig, B., Mesinger, A., Bañados, E., 2019, MNRAS, 484, 5094 CrossRefGoogle Scholar
Wang, F., et al., 2020, ApJ, 896, 23 CrossRefGoogle Scholar
Robertson, B. E., et al., 2013, ApJ, 768, 71 10.1088/0004-637X/768/1/71CrossRefGoogle Scholar
Fan, X., et al., 2006, AJ, 132, 117 10.1086/504836CrossRefGoogle Scholar
Davies, F. B., et al., 2018, ApJ, 864, 142 CrossRefGoogle Scholar
Yang, J., et al., 2020, ApJ, 904, 26 CrossRefGoogle Scholar
Bosman, S. E. I., et al., 2021, arXiv e-prints, p. arXiv:2108.03699Google Scholar
Sobacchi, E., Mesinger, A., 2015, MNRAS, 453, 1843 CrossRefGoogle Scholar
Schenker, M. A., Ellis, R. S., Konidaris, N. P., Stark, D. P., 2014, ApJ, 795, 20 CrossRefGoogle Scholar
Mason, C. A., Treu, T., Dijkstra, M., Mesinger, A., Trenti, M., Pentericci, L., de Barros, S., Vanzella, E., 2018, ApJ, 856, 2 CrossRefGoogle Scholar
Mason, C. A., et al., 2019, MNRAS, 485, 3947 CrossRefGoogle Scholar
Hoag, A., et al., 2019, ApJ, 878, 12 CrossRefGoogle Scholar
Jung, I., et al., 2020, ApJ, 904, 144 10.3847/1538-4357/abbd44CrossRefGoogle Scholar
Ouchi, M., et al., 2010, ApJ, 723, 869 10.1088/0004-637X/723/1/869CrossRefGoogle Scholar
Dijkstra, M., Mesinger, A., Wyithe, J. S. B., 2011, MNRAS, 414, 2139 CrossRefGoogle Scholar
Haardt, F., Madau, P., 2012, ApJ, 746, 125 CrossRefGoogle Scholar
Springel, V., 2010, MNRAS, 401, 791 10.1111/j.1365-2966.2009.15715.xCrossRefGoogle Scholar
Weinberger, R., Springel, V., Hernquist, L., Pillepich, A. et al., 2017, MNRAS, 465, 3291 CrossRefGoogle Scholar
Pillepich, A., Nelson, D., Hernquist, L., Springel, V., Pakmor, R., et al., 2018, MNRAS, 473, 4077 CrossRefGoogle Scholar
McKinnon, R., Torrey, P., Vogelsberger, M., Hayward, C. C., Marinacci, F., 2017, MNRAS, 468, 1505 10.1093/mnras/stx467CrossRefGoogle Scholar
Levermore, C. D., 1984, J. Quant. Spectrosc. Radiative Transfer, 31, 149 Google Scholar
Kannan, R., Vogelsberger, M., Marinacci, F., McKinnon, R., et al. 2019, MNRAS, 485, 117 CrossRefGoogle Scholar
Eldridge, J. J., Stanway, E. R., Xiao, L.,et al. 2017, Publ. Astron. Soc. Australia, 34, e058 CrossRefGoogle Scholar
Fan, X., Strauss, M. A., Becker, R. H. White, R. L. et al., 2006, AJ, 132, 117 CrossRefGoogle Scholar
Becker, G. D., Bolton, J. S., Madau, P., Pettini, M. et al., 2015, MNRAS, 447, 3402 10.1093/mnras/stu2646CrossRefGoogle Scholar
Bosman, S. E. I., Fan, X., Jiang, L., Reed, S., Matsuoka, Y. et al., 2018, MNRAS, 479, 1055 Google Scholar
Bosman, S. E. I., Davies, F. B., Becker, G., Keating, L. et al., 2021, arXiv e-prints (2108.03699)Google Scholar
Eilers, A.-C., Davies, F. B., Hennawi, J. F., 2018, ApJ, 864, 53 10.3847/1538-4357/aad4fdCrossRefGoogle Scholar
Yang, J., Wang, F., Fan, X., Hennawi, J., Davies, F. et al., 2020, ApJ, 904, 26 10.3847/1538-4357/abbc1bCrossRefGoogle Scholar
Kakiichi, K., Ellis, R. S., Laporte, N., Zitrin, A., Eilers, A.-C. et al., 2018, MNRAS, 479, 43 CrossRefGoogle Scholar
Meyer, R. A., Bosman, S. E. I., Kakiichi, K., Ellis, R. S., 2019, MNRAS, 483, 19 10.1093/mnras/sty2954CrossRefGoogle Scholar
Meyer, R. A., Kakiichi, K., Bosman, S. E. I., Ellis, R. S. et al., 2020, MNRAS, 494, 1560 10.1093/mnras/staa746CrossRefGoogle Scholar