The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Galacticus: A semi-analytic model of galaxy formation
Open accessAbstract
We describe a new, free and open source semi-analytic model of galaxy formation, GALACTICUS. The GALACTICUS model was designed to be highly modular to facilitate expansion and the exploration of alternative descriptions of key physical ingredients. We detail the GALACTICUS engine for evolving galaxies through a merging hierarchy of dark matter halos and give details of the specific implementations of physics currently available in GALACTICUS. Finally, we show results from an example model that is in reasonably good agreement with several observational datasets. We use this model to explore numerical convergence and to demonstrate the types of information which can be extracted from GALACTICUS.
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Cites
A Universal Density Profile from Hierarchical Clustering
Navarro, J. F., Frenk, C. S., & White, S. D. M. (1997) · The Astrophysical Journal · doi:10.1086/304888 · Cited by 9,917
Core condensation in heavy halos: a two-stage theory for galaxy formation and clustering
White, S. D. M., & Rees, M. J. (1978) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/183.3.341 · Cited by 3,919
The statistics of peaks of Gaussian random fields
Bardeen, J. M., Bond, J. R., Kaiser, N., & Szalay, A. S. (1986) · The Astrophysical Journal · doi:10.1086/164143 · Cited by 3,270
Cited by
Simulating galaxy formation with the IllustrisTNG model
Pillepich, A., Springel, V., Nelson, D., Genel, S., Naiman, J., Pakmor, R., Hernquist, L., Torrey, P., Vogelsberger, M., Weinberger, R., et al. (2018) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/stx2656 · Cited by 2,007
The current status of galaxy formation
Silk, J., & Mamon, G. A. (2012) · Research in Astronomy and Astrophysics · doi:10.1088/1674-4527/12/8/004 · Cited by 294
Gilman, D., Birrer, S., Nierenberg, A., Treu, T., Du, X., & Benson, A. (2020) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/stz3480 · Cited by 268
Self-citationHInet: Generating Neutral Hydrogen from Dark Matter with Neural Networks
Wadekar, D., Villaescusa-Navarro, F., Ho, S., & Perreault-Levasseur, L. (2021) · The Astrophysical Journal · doi:10.3847/1538-4357/ac033a · Cited by 32
Simulation-based inference of dynamical galaxy cluster masses with 3D convolutional neural networks
Kodi Ramanah, D., Wojtak, R., & Arendse, N. (2021) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/staa3922 · Cited by 31
Metadata
- Authors
- Benson, A. J.
- Venue
- New Astronomy
- Publisher
- Elsevier BV
- Published
- 2012-02
- Volume
- 17
- Issue
- 2
- Pages
- 175-197
- ISSN
- 1384-1076 (ISSN-L)
- OpenAlex
- W2008877686
- Cited by
- 357
- References
- 3
- FWCI
- 7.78
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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