HOD-informed prior for EFT-based full-shape analyses of LSS

Abstract To improve the performance of full-shape analyses of large-scale structure, we consider using a halo occupation distribution (HOD)-informed prior for the effective field theory (EFT) nuisance parameters. We generate 320 000 mock galaxy catalogs using 10 000 sets of HOD parameters across 32 simulation boxes with different cosmologies. We measure and fit the redshift-space power spectra using a fast emulator of the EFT model, and the resulting best-fit EFT parameter distributions are used to create the prior. This prior effectively constrains the EFT nuisance parameter space, limiting it to the space of HOD-mocks that can be well fit by a EFT model. We have tested the stability of the prior under different configurations, including the effect of varying the HOD sample distribution and the inclusion of the hexadecapole moment. We find that our HOD-informed prior and the cosmological parameter constraints derived using it are robust. While cosmological fits using the standard EFT prior suffer from prior effects, sometimes failing to recover the true cosmology within Bayesian credible intervals, the HOD-informed prior mitigates these issues and significantly improves cosmological parameter recovery for ΛCDM and beyond. This work lays the foundation for better full-shape large-scale structure analyses in current and upcoming galaxy surveys, making it a valuable tool for addressing key questions in cosmology.

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Publication Details

Journal
Journal of Cosmology and Astroparticle Physics
Published
2025-04-01
DOI
https://doi.org/10.1088/1475-7516/2025/04/041
Citations
17
Primary Topic
Structural Health Monitoring Techniques
Type
article
Field-Weighted Citation Impact
16.20
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article

HOD-informed prior for EFT-based full-shape analyses of LSS

Will J. Percival, Marco Bonici, S. Paradiso, Hanyu Zhang et al.
17 citations
Journal of Cosmology and Astroparticle Physics
Structural Health Monitoring Techniques
16.20
article

HOD-informed prior for EFT-based full-shape analyses of LSS

Will J. Percival, Marco Bonici, S. Paradiso, Hanyu Zhang, Guido D’Amico
article en
17 citations

Abstract

Abstract To improve the performance of full-shape analyses of large-scale structure, we consider using a halo occupation distribution (HOD)-informed prior for the effective field theory (EFT) nuisance parameters. We generate 320 000 mock galaxy catalogs using 10 000 sets of HOD parameters across 32 simulation boxes with different cosmologies. We measure and fit the redshift-space power spectra using a fast emulator of the EFT model, and the resulting best-fit EFT parameter distributions are used to create the prior. This prior effectively constrains the EFT nuisance parameter space, limiting it to the space of HOD-mocks that can be well fit by a EFT model. We have tested the stability of the prior under different configurations, including the effect of varying the HOD sample distribution and the inclusion of the hexadecapole moment. We find that our HOD-informed prior and the cosmological parameter constraints derived using it are robust. While cosmological fits using the standard EFT prior suffer from prior effects, sometimes failing to recover the true cosmology within Bayesian credible intervals, the HOD-informed prior mitigates these issues and significantly improves cosmological parameter recovery for ΛCDM and beyond. This work lays the foundation for better full-shape large-scale structure analyses in current and upcoming galaxy surveys, making it a valuable tool for addressing key questions in cosmology.

Journal of Cosmology and Astroparticle PhysicsVol. 2025(04)
University of Parma (IT), University of Waterloo (CA), Perimeter Institute (CA), Istituto di Astrofisica Spaziale e Fisica Cosmica di Bologna (IT), Istituto Nazionale di Fisica Nucleare, Gruppo Collegato di Parma
Openalex Percentile: Top 1%
Structural Health Monitoring Techniques
16.20
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HOD-informed prior for EFT-based full-shape analyses of LSS — Will J. Percival, Marco Bonici, et al. · Journal of Cosmology and Astroparticle Physics (2025) | TGRS Research Map | TGRS