SPT clusters with DES and HST weak lensing. I. Cluster lensing and Bayesian population modeling of multi-wavelength cluster datasets
SPT clusters with DES and HST weak lensing. I. Cluster lensing and Bayesian population modeling of multi-wavelength cluster datasets
We present a Bayesian population modeling method to analyze the abundance of galaxy clusters identified by the South Pole Telescope (SPT) with a simultaneous mass calibration using weak gravitational lensing data from the Dark Energy Survey (DES) and the Hubble Space Telescope (HST). We discuss and validate the modeling choices with a particular focus on a robust, weak-lensing-based mass calibration using DES data. For the DES Year 3 data, we report a systematic uncertainty in weak-lensing mass calibration that increases from 1\% at z=0.25 to 10\% at z=0.95, to which we add 2\% in quadrature to account for uncertainties in the impact of baryonic effects. We implement an analysis pipeline that joins the cluster abundance likelihood with a multi-observable likelihood for the SZ, optical richness, and weak-lensing measurements for each individual cluster. We validate that our analysis pipeline can recover unbiased cosmological constraints by analyzing mocks that closely resemble the cluster sample extracted from the SPT-SZ, SPTpol~ECS, and SPTpol~500d surveys and the DES Year~3 and HST-39 weak-lensing datasets. This work represents a crucial prerequisite for the subsequent cosmological analysis of the real dataset.
astro-ph.CO
Bocquet, S.
8a92384f-6e1b-47ac-ba89-a843b73d434b
Grandis, S.
d6bad66d-2e23-4865-97c4-557c2ccc3a0a
Bleem, L.E.
7a132706-7602-468a-85d1-dd81085cc5bf
Smith, M.
8bdc74e1-a37b-434d-ae75-82763109bf7a
Wiseman, P.
865f95f8-2200-46a8-bd5e-3ee30bb44072
The Dark Energy Survey Collaboration
The South Pole Telescope Collaboration
Bocquet, S.
8a92384f-6e1b-47ac-ba89-a843b73d434b
Grandis, S.
d6bad66d-2e23-4865-97c4-557c2ccc3a0a
Bleem, L.E.
7a132706-7602-468a-85d1-dd81085cc5bf
Smith, M.
8bdc74e1-a37b-434d-ae75-82763109bf7a
Wiseman, P.
865f95f8-2200-46a8-bd5e-3ee30bb44072
[Unknown type: UNSPECIFIED]
Abstract
We present a Bayesian population modeling method to analyze the abundance of galaxy clusters identified by the South Pole Telescope (SPT) with a simultaneous mass calibration using weak gravitational lensing data from the Dark Energy Survey (DES) and the Hubble Space Telescope (HST). We discuss and validate the modeling choices with a particular focus on a robust, weak-lensing-based mass calibration using DES data. For the DES Year 3 data, we report a systematic uncertainty in weak-lensing mass calibration that increases from 1\% at z=0.25 to 10\% at z=0.95, to which we add 2\% in quadrature to account for uncertainties in the impact of baryonic effects. We implement an analysis pipeline that joins the cluster abundance likelihood with a multi-observable likelihood for the SZ, optical richness, and weak-lensing measurements for each individual cluster. We validate that our analysis pipeline can recover unbiased cosmological constraints by analyzing mocks that closely resemble the cluster sample extracted from the SPT-SZ, SPTpol~ECS, and SPTpol~500d surveys and the DES Year~3 and HST-39 weak-lensing datasets. This work represents a crucial prerequisite for the subsequent cosmological analysis of the real dataset.
Text
2310.12213v1
- Author's Original
Available under License Other.
More information
e-pub ahead of print date: 18 October 2023
Additional Information:
submitted to PRD
Keywords:
astro-ph.CO
Identifiers
Local EPrints ID: 484630
URI: http://eprints.soton.ac.uk/id/eprint/484630
PURE UUID: b7542c20-0f92-4c73-a6b5-414133bc52c5
Catalogue record
Date deposited: 17 Nov 2023 18:10
Last modified: 18 Mar 2024 03:43
Export record
Contributors
Author:
S. Bocquet
Author:
S. Grandis
Author:
L.E. Bleem
Corporate Author: The Dark Energy Survey Collaboration
Corporate Author: The South Pole Telescope Collaboration
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics