Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 687

The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.

A distance to the Large Magellanic Cloud that is precise to one per cent

Open access
Pietrzyński, G., Graczyk, D., Gallenne, A., Gieren, W., Thompson, I. B., Pilecki, B., Karczmarek, P., Górski, M., Suchomska, K., Taormina, M., Zgirski, B., Wielgórski, P., Kołaczkowski, Z., Konorski, P., Villanova, S., Nardetto, N., Kervella, P., Bresolin, F., Kudritzki, R. P., Storm, J., Smolec, R., Narloch, W.·2019·Nature

Abstract

In the era of precision cosmology, it is essential to determine the Hubble constant empirically with an accuracy of one per cent or better1. At present, the uncertainty on this constant is dominated by the uncertainty in the calibration of the Cepheid period–luminosity relationship2,3 (also known as the Leavitt law). The Large Magellanic Cloud has traditionally served as the best galaxy with which to calibrate Cepheid period–luminosity relations, and as a result has become the best anchor point for the cosmic distance scale4,5. Eclipsing binary systems composed of late-type stars offer the most precise and accurate way to measure the distance to the Large Magellanic Cloud. Currently the limit of the precision attainable with this technique is about two per cent, and is set by the precision of the existing calibrations of the surface brightness–colour relation5,6. Here we report a calibration of the surface brightness–colour relation with a precision of 0.8 per cent. We use this calibration to determine a geometrical distance to the Large Magellanic Cloud that is precise to 1 per cent based on 20 eclipsing binary systems. The final distance is 49.59 ± 0.09 (statistical) ± 0.54 (systematic) kiloparsecs. A new calibration of the surface brightness–colour relation of eclipsing binary stars gives a distance to the Large Magellanic Cloud that is precise to one per cent.

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 · 10.1038/s41586-019-0999-4

Cites

29 of 29 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 29 references

Cited by

See all 687

Metadata

Authors
Pietrzyński, G., Graczyk, D., Gallenne, A., Gieren, W., Thompson, I. B., Pilecki, B., Karczmarek, P., Górski, M., Suchomska, K., Taormina, M., Zgirski, B., Wielgórski, P., Kołaczkowski, Z., Konorski, P., Villanova, S., Nardetto, N., Kervella, P., Bresolin, F., Kudritzki, R. P., Storm, J., Smolec, R., & Narloch, W.
Venue
Nature
Published
2019-03
Volume
567
Issue
7747
Pages
200-203
ISSN
  • 0028-0836 (ISSN-L)
  • 1476-4687
OpenAlex
W2922092944
Cited by
687
References
29
FWCI
38.15
Type
journal article
Language
en
Open access
green

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: A distance to the Large Magellanic Cloud that is precise to one per cent. https://app.cochat.ai/papers/10.1038/s41586-019-0999-4
The paper
Pietrzyński, G., Graczyk, D., Gallenne, A., Gieren, W., Thompson, I. B., Pilecki, B., Karczmarek, P., Górski, M., Suchomska, K., Taormina, M., Zgirski, B., Wielgórski, P., Kołaczkowski, Z., Konorski, P., Villanova, S., Nardetto, N., Kervella, P., Bresolin, F., Kudritzki, R. P., . . . Narloch, W. (2019). A distance to the Large Magellanic Cloud that is precise to one per cent. Nature. https://doi.org/10.1038/s41586-019-0999-4

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.