Pith. sign in

REVIEW 1 cited by

Constraining cosmological parameters using the splashback radius of galaxy clusters

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2406.17849 v1 pith:YYHDBQIK submitted 2024-06-25 astro-ph.CO astro-ph.GA

classification astro-ph.COastro-ph.GA
keywords cosmologicalomegasigmaclusterparametersradiussplashbackgalaxy
verification ladder T0 review T1 audit T2 compute T3 formal

Signed reviews

No signed human review yet.

0 comments
abstract

Cosmological parameters such as $\Omega_{\rm{M}}$ and $\sigma_{8}$ can be measured indirectly using various methods, including galaxy cluster abundance and cosmic shear. These measurements constrain the composite parameter $S_{8}$, leading to degeneracy between $\Omega_{\rm{M}}$ and $\sigma_{8}$. However, some structural properties of galaxy clusters also correlate with cosmological parameters, due to their dependence on a cluster's accretion history. In this work, we focus on the splashback radius, an observable cluster feature that represents a boundary between a cluster and the surrounding Universe. Using a suite of cosmological simulations with a range of values for $\Omega_{\rm{M}}$ and $\sigma_{8}$, we show that the position of the splashback radius around cluster-mass halos is greater in cosmologies with smaller values of $\Omega_{\rm{M}}$ or larger values of $\sigma_{8}$. This variation breaks the degeneracy between $\Omega_{\rm{M}}$ and $\sigma_{8}$ that comes from measurements of the $S_{8}$ parameter. We also show that this variation is, in principle, measurable in observations. As the splashback radius can be determined from the same weak lensing analysis already used to estimate $S_{8}$, this new approach can tighten low-redshift constraints on cosmological parameters, either using existing data, or using upcoming data such as that from Euclid and LSST.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Identifying backsplash galaxies using machine learning

    astro-ph.GA 2026-07 conditional novelty 6.0 of 10

    Machine learning trained on The Three Hundred simulations identifies backsplash galaxies in cluster outskirts with ~75% purity/completeness, and has been applied to HI-tail galaxies in Virgo.

Pith tools