Efficient Reionization in a Large Hydrodynamic Galaxy Formation Simulation Article Swipe
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2306.07861
Accuracy in the topology and statistics of a simulated Epoch of Reionization (EoR) are vital to draw connections between observations and physical processes. While full radiative transfer models produce the most accurate reionization models, they are highly computationally expensive, and are infeasible for the largest cosmological simulations. Instead, large simulations often include EoR models that are pre-computed via the initial density field, or post-processed where feedback effects are ignored. We introduce Astrid-ES, a resimulation of the Astrid epoch of reionisation $20 > z > 5.5$ which includes an on-the-fly excursion-set reionization algorithm. Astrid-ES produces more accurate reionization histories without significantly impacting the computational time. This model directly utilises the star particles produced in the simulation to calculate the EoR history and includes a UV background which heats the gas particles after their reionization. We contrast the reionization topology and statistics in Astrid-ES with the previously employed parametric reionisation model, finding that in Astrid-ES, ionised regions are more correlated with galaxies, and the 21cm power-spectrum shows an increase in large scale power. We calculate the relation between the size of HII regions and the UV luminosity of the brightest galaxy within them. Prior to the overlap phase, we find a power-law fit of $\mathrm{log} (R) = -0.314 M_\mathrm{UV} - 2.550 \mathrm{log}(1+z) + 7.408$ with a standard deviation $σ_R < 0.15 \mathrm{dex}$ across all mass bins. We also examine the properties of halos throughout reionization, finding that while the properties of halos in the simulation are correlated with the redshift of reionisation, they are not greatly affected by reionisation itself.
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2306.07861
- https://arxiv.org/pdf/2306.07861
- OA Status
- green
- Cited By
- 1
- Related Works
- 10
- OpenAlex ID
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Raw OpenAlex JSON
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https://openalex.org/W4380715433Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2306.07861Digital Object Identifier
- Title
-
Efficient Reionization in a Large Hydrodynamic Galaxy Formation SimulationWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-06-13Full publication date if available
- Authors
-
J. Davies, Simeon Bird, Simon J. Mutch, Yueying Ni, Yu Feng, Rupert A. C. Croft, Tiziana Di Matteo, J. Stuart B. WyitheList of authors in order
- Landing page
-
https://arxiv.org/abs/2306.07861Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2306.07861Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2306.07861Direct OA link when available
- Concepts
-
Reionization, Physics, Astrophysics, Galaxy, Star formation, Spectral density, Halo, Radiative transfer, Cosmology, Luminosity, Statistics, Redshift, Quantum mechanics, MathematicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
- Citations by year (recent)
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2023: 1Per-year citation counts (last 5 years)
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.model, | 148 |
| abstract_inverted_index.models | 27, 53 |
| abstract_inverted_index.phase, | 195 |
| abstract_inverted_index.power. | 170 |
| abstract_inverted_index.within | 189 |
| abstract_inverted_index.between | 18, 175 |
| abstract_inverted_index.density | 60 |
| abstract_inverted_index.effects | 66 |
| abstract_inverted_index.examine | 226 |
| abstract_inverted_index.finding | 149, 233 |
| abstract_inverted_index.greatly | 253 |
| abstract_inverted_index.history | 119 |
| abstract_inverted_index.include | 51 |
| abstract_inverted_index.initial | 59 |
| abstract_inverted_index.ionised | 153 |
| abstract_inverted_index.itself. | 257 |
| abstract_inverted_index.largest | 44 |
| abstract_inverted_index.models, | 33 |
| abstract_inverted_index.overlap | 194 |
| abstract_inverted_index.produce | 28 |
| abstract_inverted_index.regions | 154, 180 |
| abstract_inverted_index.without | 98 |
| abstract_inverted_index.Accuracy | 0 |
| abstract_inverted_index.Instead, | 47 |
| abstract_inverted_index.accurate | 31, 95 |
| abstract_inverted_index.affected | 254 |
| abstract_inverted_index.contrast | 134 |
| abstract_inverted_index.directly | 106 |
| abstract_inverted_index.employed | 145 |
| abstract_inverted_index.feedback | 65 |
| abstract_inverted_index.ignored. | 68 |
| abstract_inverted_index.includes | 86, 121 |
| abstract_inverted_index.increase | 166 |
| abstract_inverted_index.physical | 21 |
| abstract_inverted_index.produced | 111 |
| abstract_inverted_index.produces | 93 |
| abstract_inverted_index.redshift | 247 |
| abstract_inverted_index.relation | 174 |
| abstract_inverted_index.standard | 214 |
| abstract_inverted_index.topology | 3, 137 |
| abstract_inverted_index.transfer | 26 |
| abstract_inverted_index.utilises | 107 |
| abstract_inverted_index.Astrid-ES | 92, 141 |
| abstract_inverted_index.brightest | 187 |
| abstract_inverted_index.calculate | 116, 172 |
| abstract_inverted_index.deviation | 215 |
| abstract_inverted_index.galaxies, | 159 |
| abstract_inverted_index.histories | 97 |
| abstract_inverted_index.impacting | 100 |
| abstract_inverted_index.introduce | 70 |
| abstract_inverted_index.particles | 110, 129 |
| abstract_inverted_index.power-law | 199 |
| abstract_inverted_index.radiative | 25 |
| abstract_inverted_index.simulated | 8 |
| abstract_inverted_index.Astrid-ES, | 71, 152 |
| abstract_inverted_index.algorithm. | 91 |
| abstract_inverted_index.background | 124 |
| abstract_inverted_index.correlated | 157, 244 |
| abstract_inverted_index.expensive, | 38 |
| abstract_inverted_index.infeasible | 41 |
| abstract_inverted_index.luminosity | 184 |
| abstract_inverted_index.on-the-fly | 88 |
| abstract_inverted_index.parametric | 146 |
| abstract_inverted_index.previously | 144 |
| abstract_inverted_index.processes. | 22 |
| abstract_inverted_index.properties | 228, 237 |
| abstract_inverted_index.simulation | 114, 242 |
| abstract_inverted_index.statistics | 5, 139 |
| abstract_inverted_index.throughout | 231 |
| abstract_inverted_index.connections | 17 |
| abstract_inverted_index.simulations | 49 |
| abstract_inverted_index.Reionization | 11 |
| abstract_inverted_index.cosmological | 45 |
| abstract_inverted_index.observations | 19 |
| abstract_inverted_index.pre-computed | 56 |
| abstract_inverted_index.reionisation | 79, 147, 256 |
| abstract_inverted_index.reionization | 32, 90, 96, 136 |
| abstract_inverted_index.resimulation | 73 |
| abstract_inverted_index.simulations. | 46 |
| abstract_inverted_index.$\mathrm{log} | 202 |
| abstract_inverted_index.M_\mathrm{UV} | 206 |
| abstract_inverted_index.\mathrm{dex}$ | 219 |
| abstract_inverted_index.computational | 102 |
| abstract_inverted_index.excursion-set | 89 |
| abstract_inverted_index.reionisation, | 249 |
| abstract_inverted_index.reionization, | 232 |
| abstract_inverted_index.reionization. | 132 |
| abstract_inverted_index.significantly | 99 |
| abstract_inverted_index.post-processed | 63 |
| abstract_inverted_index.power-spectrum | 163 |
| abstract_inverted_index.computationally | 37 |
| abstract_inverted_index.\mathrm{log}(1+z) | 209 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 8 |
| citation_normalized_percentile |