The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
Reconstruction of dark energy and expansion dynamics using Gaussian processes
Open accessAbstract
An important issue in cosmology is reconstructing the effective dark energy equation of state directly from observations. With few physically motivated models, future dark energy studies cannot only be based on constraining a dark energy parameter space, as the errors found depend strongly on the parametrisation considered. We present a new non-parametric approach to reconstructing the history of the expansion rate and dark energy using Gaussian Processes, which is a fully Bayesian approach for smoothing data. We present a pedagogical introduction to Gaussian Processes, and discuss how it can be used to robustly differentiate data in a suitable way. Using this method we show that the Dark Energy Survey - Supernova Survey (DES) can accurately recover a slowly evolving equation of state to σ w = ±0.05 (95% CL) at z = 0 and ±0.25 at z = 0.7, with a minimum error of ±0.025 at the sweet-spot at z ∼ 0.16, provided the other parameters of the model are known. Errors on the expansion history are an order of magnitude smaller, yet make no assumptions about dark energy whatsoever. A code for calculating functions and their first three derivatives using Gaussian processes has been developed and is available for download .
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
SEVEN-YEAR WILKINSON MICROWAVE ANISOTROPY PROBE(WMAP) OBSERVATIONS: COSMOLOGICAL INTERPRETATION
Komatsu, E., Smith, K. M., Dunkley, J., Bennett, C. L., Gold, B., Hinshaw, G., Jarosik, N., Larson, D., Nolta, M. R., Page, L., et al. (2011) · The Astrophysical Journal Supplement Series · doi:10.1088/0067-0049/192/2/18 · Cited by 8,802
COPELAND, E. J., SAMI, M., & TSUJIKAWA, S. (2006) · International Journal of Modern Physics D · doi:10.1142/s021827180600942x · Cited by 6,239
Suzuki, N., Rubin, D., Lidman, C., Aldering, G., Amanullah, R., Barbary, K., Barrientos, L. F., Botyanszki, J., Brodwin, M., Connolly, N., et al. (2012) · The Astrophysical Journal · doi:10.1088/0004-637x/746/1/85 · Cited by 1,699
Exploring the expanding Universe and dark energy using the statefinder diagnostic
Alam, U., Sahni, V., Deep Saini, T., & Starobinsky, A. A. (2003) · Monthly Notices of the Royal Astronomical Society · doi:10.1046/j.1365-8711.2003.06871.x · Cited by 921
IMPROVED DARK ENERGY CONSTRAINTS FROM ∼100 NEW CfA SUPERNOVA TYPE Ia LIGHT CURVES
Hicken, M., Wood-Vasey, W. M., Blondin, S., Challis, P., Jha, S., Kelly, P. L., Rest, A., & Kirshner, R. P. (2009) · The Astrophysical Journal · doi:10.1088/0004-637x/700/2/1097 · Cited by 894
SAHNI, V., & STAROBINSKY, A. (2006) · International Journal of Modern Physics D · doi:10.1142/s0218271806009704 · Cited by 734
Prospects for probing the dark energy via supernova distance measurements
Huterer, D., & Turner, M. S. (1999) · Physical Review D · doi:10.1103/physrevd.60.081301 · Cited by 462
Reconstructing the Cosmic Equation of State from Supernova Distances
Saini, T. D., Raychaudhury, S., Sahni, V., & Starobinsky, A. A. (2000) · Physical Review Letters · doi:10.1103/physrevlett.85.1162 · Cited by 395
The case for dynamical dark energy revisited
Alam, U., Sahni, V., & Starobinsky, A. A. (2004) · Journal of Cosmology and Astroparticle Physics · doi:10.1088/1475-7516/2004/06/008 · Cited by 381
Future supernovae observations as a probe of dark energy
Weller, J., & Albrecht, A. (2002) · Physical Review D · doi:10.1103/physrevd.65.103512 · Cited by 341
Cited by
Yu, H., Ratra, B., & Wang, F.-Y. (2018) · The Astrophysical Journal · doi:10.3847/1538-4357/aab0a2 · Cited by 319
PHOTOMETRIC SUPERNOVA CLASSIFICATION WITH MACHINE LEARNING
Lochner, M., McEwen, J. D., Peiris, H. V., Lahav, O., & Winter, M. K. (2016) · The Astrophysical Journal Supplement Series · doi:10.3847/0067-0049/225/2/31 · Cited by 200
Abdalla, E., Abellán, G. F., Aboubrahim, A., Agnello, A., Akarsu, Ö., Akrami, Y., Alestas, G., Aloni, D., Amendola, L., Anchordoqui, L. A., et al. (2022) · Journal of High Energy Astrophysics · doi:10.1016/j.jheap.2022.04.002 · Cited by 37
Melchiorri, A., & Ruchika (2026) · New Astronomy Reviews · doi:10.1016/j.newar.2026.101758
“The analysis was performed with the GaPP code (Seikel et al., 2012).”
Metadata
- Authors
- Seikel, M., Clarkson, C., & Smith, M.
- Venue
- Journal of Cosmology and Astroparticle Physics
- Publisher
- IOP Publishing
- Published
- 2012-06-25
- Volume
- 2012
- Issue
- 06
- Pages
- 036-036
- ISSN
- 1475-7508 (ISSN-L)
- 1475-7516
- OpenAlex
- W2082443206
- Cited by
- 441
- References
- 26
- FWCI
- 6.02
- 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: Reconstruction of dark energy and expansion dynamics using Gaussian processes. https://app.cochat.ai/papers/10.1088/1475-7516/2012/06/036
- The paper
- Seikel, M., Clarkson, C., & Smith, M. (2012). Reconstruction of dark energy and expansion dynamics using Gaussian processes. Journal of Cosmology and Astroparticle Physics. https://doi.org/10.1088/1475-7516/2012/06/036
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.
