Abstract
We present the first weak-lensing mass calibration and X-ray scaling relations of galaxy clusters and groups selected in the eROSITA Final Equatorial Depth Survey (eFEDS) observed by Spectrum Roentgen Gamma/eROSITA over a contiguous footprint with an area of ≈140 deg2, using the three-year (S19A) weak-lensing data from the Hyper Suprime-Cam (HSC) Subaru Strategic Program survey. In this work, we study a sample of 434 optically confirmed galaxy clusters (and groups) at redshift 0.01 ≲z ≲1.3 with a median of 0.35, of which 313 systems are uniformly covered by the HSC survey to enable the extraction of the weak-lensing shear observable. In a Bayesian population modeling, we perform a blind analysis for the weak-lensing mass calibration by simultaneously modeling the observed count rateηand the shear profileg+of individual clusters through the count-rate-to-mass-and-redshift (η-M500-z) relation and the weak-lensing-mass-to-mass-and-redshift (MWL-M500-z) relation, respectively, while accounting for the bias in these observables using simulation-based calibrations. As a result, the count-rate-inferred and lensing-calibrated cluster mass is obtained from the joint modeling of the scaling relations, as the ensemble mass spanning a range of 1013h-1M⊙≲M500≲ 1015h-1M⊙with a median of ≈1014h-1M⊙for the eFEDS sample. With the mass calibration, we further model the X-ray observable-to-mass-and-redshift relations, including the rest-frame soft-band and bolometric luminosity (LXandLb), the emission-weighted temperatureTX, the mass of intra-cluster mediumMg, and the mass proxyYX, which is the product ofTXandMg. Except forLXwith a steeper dependence on the cluster mass at a statistically significant level, we find that the other X-ray scaling relations all show a mass trend that is statistically consistent with the self-similar prediction at a level of ≲1.7σ. Meanwhile, all these scaling relations show no significant deviation from the self-similarity in their redshift scaling. Moreover, no significant redshift-dependent mass trend is present. This work demonstrates the synergy between the eROSITA and HSC surveys in preparation for the forthcoming first-year eROSITA cluster cosmology.
Highlights
If a cluster is not covered by the Hyper Suprime-Cam (HSC) survey, we evaluate the probability of observing this cluster with the X-ray observable
We show the comparison of LX with the literature in the upper-left panel of Fig. 16, in which we include the result of the simulated clusters from the C-Eagle cosmological hydrodynamical simulation (Barnes et al 2017) and the self-similar model with the normalization anchored to the best-fit value of the eROSITA Final Equatorial Depth Survey (eFEDS) sample
Detected clusters selected in the eFEDS survey using the threeyear weak-lensing shape catalog (S19A) from the HSC survey
Summary
The probe based on the abundance of galaxy clusters plays a crucial role in constraining cosmology by utilizing the sample of clusters selected in the optical (Costanzi et al 2019b, 2021; To et al 2021), X-rays (Mantz et al 2015; Schellenberger & Reiprich 2017; Pacaud et al 2018), and millimeter-wavelength bands (Planck Collaboration et al 2016; Bocquet et al 2015; de Haan et al 2016; Bocquet et al 2019) through the SunyaevZel’dovich (SZ; Sunyaev & Zel’dovich 1972) effect. A necessary ingredient in cluster cosmology is a large sample of galaxy clusters with a well-understood selection function. With recent wide and deep surveys in the optical, such as the Dark Energy Survey (The Dark Energy Survey Collaboration 2005), a large sample of galaxy clusters and groups has been constructed out to redshift z ≈ 0.6 and over a footprint with an area of more than a thousand square degrees. A sizable sample of optically selected clusters has largely improved cosmological constraints, modeling the selection function of the clusters is challenging, mainly because of the projection effect (Zu et al 2017; Costanzi et al 2019a; Sunayama et al 2020), and could result in a systematic bias in cosmological parameters (DES Collaboration et al 2020)
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