Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 300

The DOI matches its Crossref record; 106 of the 106 references it cites were found in a registry or an index.

Core Cosmology Library: Precision Cosmological Predictions for LSST

Open access
Chisari, Nora Elisa, Alonso, David, Krause, Elisabeth, Leonard, C. Danielle, Bull, Philip, Neveu, Jérémy, Villarreal, Antonio, Singh, Sukhdeep, McClintock, Thomas, Ellison, John, Du, Zilong, Zuntz, Joe, Mead, Alexander, Joudaki, Shahab, Lorenz, Christiane S., Tröster, Tilman, Sanchez, Javier, Lanusse, Francois, Ishak, Mustapha, Hlozek, Renée, Blazek, Jonathan, Campagne, Jean-Eric, Almoubayyed, Husni, Eifler, Tim, Kirby, Matthew, Kirkby, David, Plaszczynski, Stéphane, Slosar, Anže, Vrastil, Michal, Wagoner, Erika L., (LSST Dark Energy Science Collaboration)·2019·The Astrophysical Journal Supplement Series
DOI 10.3847/1538-4365/ab1658
Open this paper in CoChat — free account

Abstract

The Core Cosmology Library (CCL) provides routines to compute basic cosmological observables to a high degree of accuracy, which have been verified with an extensive suite of validation tests. Predictions are provided for many cosmological quantities, including distances, angular power spectra, correlation functions, halo bias, and the halo mass function through state-of-the-art modeling prescriptions available in the literature. Fiducial specifications for the expected galaxy distributions for the Large Synoptic Survey Telescope (LSST) are also included, together with the capability of computing redshift distributions for a user-defined photometric redshift model. A rigorous validation procedure, based on comparisons between CCL and independent software packages, allows us to establish a well-defined numerical accuracy for each predicted quantity. As a result, predictions for correlation functions of galaxy clustering, galaxy–galaxy lensing, and cosmic shear are demonstrated to be within a fraction of the expected statistical uncertainty of the observables for the models and in the range of scales of interest to LSST. CCL is an open source software package written in C, with a Python interface and publicly available at https://github.com/LSSTDESC/CCL.

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 · 10.3847/1538-4365/ab1658

Cites

106 of 106 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 106 references

Cited by

See all 300

Metadata

Authors
Chisari, N. E., Alonso, D., Krause, E., Leonard, C. D., Bull, P., Neveu, J., Villarreal, A., Singh, S., McClintock, T., Ellison, J., Du, Z., Zuntz, J., Mead, A., Joudaki, S., Lorenz, C. S., Tröster, T., Sanchez, J., Lanusse, F., Ishak, M., Hlozek, R., Blazek, J., Campagne, J.-E., Almoubayyed, H., Eifler, T., Kirby, M., Kirkby, D., Plaszczynski, S., Slosar, A., Vrastil, M., Wagoner, E. L., & (LSST Dark Energy Science Collaboration)
Venue
The Astrophysical Journal Supplement Series
Publisher
American Astronomical Society
Published
2019-05-01
Volume
242
Issue
1
Pages
2
ISSN
  • 0067-0049 (ISSN-L)
  • 1538-4365
DOI
10.3847/1538-4365/ab1658
OpenAlex
W2904691988
Cited by
300
References
106
FWCI
13.26
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: Core Cosmology Library: Precision Cosmological Predictions for LSST. https://app.cochat.ai/papers/10.3847/1538-4365/ab1658
The paper
Chisari, N. E., Alonso, D., Krause, E., Leonard, C. D., Bull, P., Neveu, J., Villarreal, A., Singh, S., McClintock, T., Ellison, J., Du, Z., Zuntz, J., Mead, A., Joudaki, S., Lorenz, C. S., Tröster, T., Sanchez, J., Lanusse, F., Ishak, M., . . . (LSST Dark Energy Science Collaboration). (2019). Core Cosmology Library: Precision Cosmological Predictions for LSST. The Astrophysical Journal Supplement Series. https://doi.org/10.3847/1538-4365/ab1658

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.