SUNBIRD: a simulation-based model for full-shape density-split clustering Article Swipe
Carolina Cuesta-Lazaro
,
E. Paillas
,
Sihan Yuan
,
Yan-Chuan Cai
,
S. Nadathur
,
W. J. Percival
,
Florian Beutler
,
Arnaud de Mattia
,
Daniel J. Eisenstein
,
D. Forero-Sánchez
,
Nelson Padilla
,
Mathilde Pinon
,
V. Ruhlmann-Kleider
,
Ariel G. Sánchez
,
Georgios Valogiannis
,
Pauline Zarrouk
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1093/mnras/stae1234
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1093/mnras/stae1234
Combining galaxy clustering information from regions of different environmental densities can help break cosmological parameter degeneracies and access non-Gaussian information from the density field that is not readily captured by the standard two-point correlation function (2PCF) analyses. However, modelling these density-dependent statistics down to the non-linear regime has so far remained challenging. We present a simulation-based model that is able to capture the cosmological dependence of the full shape of the density-split clustering (DSC) statistics down to intra-halo scales. Our models are based on neural-network emulators that are trained on high-fidelity mock galaxy catalogues within an extended-ΛCDM framework, incorporating the effects of redshift-space, Alcock–Paczynski distortions, and models of the halo–galaxy connection. Our models reach sub-per cent level accuracy down to $1 \, h^{-1}\text{Mpc}$ and are robust against different choices of galaxy–halo connection modelling. When combined with the galaxy 2PCF, DSC can tighten the constraints on ωcdm, σ8, and ns by factors of 2.9, 1.9, and 2.1, respectively, compared to a 2PCF-only analysis. DSC additionally puts strong constraints on environment-based assembly bias parameters.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1093/mnras/stae1234
- https://academic.oup.com/mnras/article-pdf/531/3/3336/58175676/stae1234.pdf
- OA Status
- gold
- Cited By
- 15
- References
- 104
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4399466819
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- OpenAlex ID
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https://openalex.org/W4399466819Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1093/mnras/stae1234Digital Object Identifier
- Title
-
SUNBIRD: a simulation-based model for full-shape density-split clusteringWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-06-05Full publication date if available
- Authors
-
Carolina Cuesta-Lazaro, E. Paillas, Sihan Yuan, Yan-Chuan Cai, S. Nadathur, W. J. Percival, Florian Beutler, Arnaud de Mattia, Daniel J. Eisenstein, D. Forero-Sánchez, Nelson Padilla, Mathilde Pinon, V. Ruhlmann-Kleider, Ariel G. Sánchez, Georgios Valogiannis, Pauline ZarroukList of authors in order
- Landing page
-
https://doi.org/10.1093/mnras/stae1234Publisher landing page
- PDF URL
-
https://academic.oup.com/mnras/article-pdf/531/3/3336/58175676/stae1234.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://academic.oup.com/mnras/article-pdf/531/3/3336/58175676/stae1234.pdfDirect OA link when available
- Concepts
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Physics, Halo, Galaxy, Astrophysics, Cluster analysis, Correlation function (quantum field theory), Redshift, Connection (principal bundle), Gaussian, Galaxy formation and evolution, Artificial intelligence, Computer science, Engineering, Dielectric, Quantum mechanics, Structural engineering, OptoelectronicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
15Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 11, 2024: 4Per-year citation counts (last 5 years)
- References (count)
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104Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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