The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Galaxies on FIRE (Feedback In Realistic Environments): stellar feedback explains cosmologically inefficient star formation
Open accessAbstract
We present a series of high-resolution cosmological simulations1 of galaxy formation to z = 0, spanning halo masses ∼108–1013 M⊙, and stellar masses ∼104–1011 M⊙. Our simulations include fully explicit treatment of the multiphase interstellar medium and stellar feedback. The stellar feedback inputs (energy, momentum, mass, and metal fluxes) are taken directly from stellar population models. These sources of feedback, with zero adjusted parameters, reproduce the observed relation between stellar and halo mass up to Mhalo ∼ 1012 M⊙. We predict weak redshift evolution in the M*–Mhalo relation, consistent with current constraints to z > 6. We find that the M*–Mhalo relation is insensitive to numerical details, but is sensitive to feedback physics. Simulations with only supernova feedback fail to reproduce observed stellar masses, particularly in dwarf and high-redshift galaxies: radiative feedback (photoheating and radiation pressure) is necessary to destroy giant molecular clouds and enable efficient coupling of later supernovae to the gas. Star formation rates (SFRs) agree well with the observed Kennicutt relation at all redshifts. The galaxy-averaged Kennicutt relation is very different from the numerically imposed law for converting gas into stars, and is determined by self-regulation via stellar feedback. Feedback reduces SFRs and produces reservoirs of gas that lead to rising late-time star formation histories, significantly different from halo accretion histories. Feedback also produces large short-time-scale variability in galactic SFRs, especially in dwarfs. These properties are not captured by common ‘sub-grid’ wind models.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The cosmological simulation code gadget-2
Springel, V. (2005) · Monthly Notices of the Royal Astronomical Society · doi:10.1111/j.1365-2966.2005.09655.x · Cited by 6,368
THE AVERAGE STAR FORMATION HISTORIES OF GALAXIES IN DARK MATTER HALOS FROM z = 0-8
Behroozi, P. S., Wechsler, R. H., & Conroy, C. (2013) · The Astrophysical Journal · doi:10.1088/0004-637x/770/1/57 · Cited by 2,167
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 Galaxy in Context: Structural, Kinematic, and Integrated Properties
Bland-Hawthorn, J., & Gerhard, O. (2016) · Annual Review of Astronomy and Astrophysics · doi:10.1146/annurev-astro-081915-023441 · Cited by 1,656
The EAGLE simulations of galaxy formation: calibration of subgrid physics and model variations
Crain, R. A., Schaye, J., Bower, R. G., Furlong, M., Schaller, M., Theuns, T., Dalla Vecchia, C., Frenk, C. S., McCarthy, I. G., Helly, J. C., et al. (2015) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/stv725 · Cited by 1,451
Dark matter self-interactions and small scale structure
Tulin, S., & Yu, H.-B. (2018) · Physics Reports · doi:10.1016/j.physrep.2017.11.004 · Cited by 1,111
Theoretical Challenges in Galaxy Formation
Naab, T., & Ostriker, J. P. (2017) · Annual Review of Astronomy and Astrophysics · doi:10.1146/annurev-astro-081913-040019 · Cited by 722
Metadata
- Authors
- Hopkins, P. F., Kereš, D., Oñorbe, J., Faucher-Giguère, C.-A., Quataert, E., Murray, N., & Bullock, J. S.
- Venue
- Monthly Notices of the Royal Astronomical Society
- Publisher
- Oxford University Press (OUP)
- Published
- 2014-09-29
- Volume
- 445
- Issue
- 1
- Pages
- 581-603
- ISSN
- 0035-8711 (ISSN-L)
- 1365-2966
- OpenAlex
- W2076246932
- Cited by
- 1,468
- References
- 2
- FWCI
- 78.03
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Galaxies on FIRE (Feedback In Realistic Environments): stellar feedback explains cosmologically inefficient star formation. https://app.cochat.ai/papers/10.1093/mnras/stu1738
- The paper
- Hopkins, P. F., Kereš, D., Oñorbe, J., Faucher-Giguère, C.-A., Quataert, E., Murray, N., & Bullock, J. S. (2014). Galaxies on FIRE (Feedback In Realistic Environments): stellar feedback explains cosmologically inefficient star formation. Monthly Notices of the Royal Astronomical Society. https://doi.org/10.1093/mnras/stu1738
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.