Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 2,239

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Baryonic Features in the Matter Transfer Function

Open access
Eisenstein, Daniel J., Hu, Wayne·1998·The Astrophysical Journal

Abstract

We provide scaling relations and fitting formulae for adiabatic cold dark matter cosmologies that account for all baryon effects in the matter transfer function to better than 10% in the large-scale structure regime. They are based upon a physically well-motivated separation of the effects of acoustic oscillations, Compton drag, velocity overshoot, baryon infall, adiabatic damping, Silk damping, and cold dark matter growth suppression. We also find a simpler, more accurate, and better motivated form for the zero-baryon transfer function than previous works. These descriptions are employed to quantify the amplitude and location of baryonic features in linear theory. While baryonic oscillations are prominent if the baryon fraction Ω b /Ω 0 ≳ Ω 0 h 2 + 0.2, the main effect in more conventional cosmologies is a sharp suppression in the transfer function below the sound horizon. We provide a simple but accurate description of this effect and stress that it is not well approximated by a change in the shape parameter Γ.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1086/305424

Cites

3 of 3 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

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

Show all 3 references

Cited by

See all 2,239

Metadata

Authors
Eisenstein, D. J., & Hu, W.
Venue
The Astrophysical Journal
Published
1998-04
Volume
496
Issue
2
Pages
605-614
ISSN
  • 0004-637X (ISSN-L)
  • 1538-4357
OpenAlex
W2169866137
Cited by
2,239
References
3
FWCI
10.16
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: Baryonic Features in the Matter Transfer Function. https://app.cochat.ai/papers/10.1086/305424
The paper
Eisenstein, D. J., & Hu, W. (1998). Baryonic Features in the Matter Transfer Function. The Astrophysical Journal. https://doi.org/10.1086/305424

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.