Towards including super-sample covariance in the unbinned likelihood for cluster abundance cosmology Article Swipe
Constantin Payerne
,
Catherine Murray
,
Céline Combet
,
Mariana Penna-Lima
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1093/mnras/stae1504
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1093/mnras/stae1504
The measurement of the abundance of galaxy clusters in the Universe is a sensitive probe of cosmology, which depends on both the expansion history of the Universe and the growth of structure. Density fluctuations across the finite survey volume add noise to this measurement, this is often referred to as super-sample covariance (SSC). For an unbinned cluster analysis, such noise has not been included in the cluster likelihood, since the effect of SSC was small compared to the Poisson shot-noise for samples of a few hundred clusters. For upcoming large cluster surveys such as the Rubin LSST, which will deliver catalogues of tens of thousands of clusters, this effect will no longer be negligible. In this paper, we propose a new hybrid likelihood based on the Gauss-Poisson Compound model (GPC), by using infinitesimal mass bins and standard redshift bins. This likelihood has the advantages of an unbinned Poisson likelihood while successfully incorporating the effects of SSC. Using a simulated dark matter halo catalogue, we find that the hybrid likelihood, accounting for both Poisson noise and SSC, increases the dispersion of the parameter posteriors by 20 per cent when using 100 000 clusters compared to the standard unbinned likelihood, based on Poisson statistics only.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1093/mnras/stae1504
- https://academic.oup.com/mnras/advance-article-pdf/doi/10.1093/mnras/stae1504/58257711/stae1504.pdf
- OA Status
- gold
- Cited By
- 2
- References
- 96
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4399793409
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4399793409Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1093/mnras/stae1504Digital Object Identifier
- Title
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Towards including super-sample covariance in the unbinned likelihood for cluster abundance cosmologyWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-06-17Full publication date if available
- Authors
-
Constantin Payerne, Catherine Murray, Céline Combet, Mariana Penna-LimaList of authors in order
- Landing page
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https://doi.org/10.1093/mnras/stae1504Publisher landing page
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https://academic.oup.com/mnras/advance-article-pdf/doi/10.1093/mnras/stae1504/58257711/stae1504.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
- OA URL
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https://academic.oup.com/mnras/advance-article-pdf/doi/10.1093/mnras/stae1504/58257711/stae1504.pdfDirect OA link when available
- Concepts
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Physics, Cosmology, Poisson distribution, Redshift, Astrophysics, Covariance, Galaxy, Dark matter, Cluster (spacecraft), Statistical physics, Statistics, Shot noise, Universe, Mathematics, Computer science, Programming language, Optics, DetectorTop concepts (fields/topics) attached by OpenAlex
- Cited by
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2Total citation count in OpenAlex
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2025: 1, 2024: 1Per-year citation counts (last 5 years)
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96Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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