The eROSITA Final Equatorial-Depth Survey (eFEDS)

Context. We present the results of a systematic X-ray analysis of optically rich galaxy clusters detected by the Subaru Hyper Suprime-Cam (HSC) survey in the eROSITA Final Equatorial-Depth Survey (eFEDS) field. Aims. Through a joint analysis of the SRG (Spectrum Roentgen Gamma)/eROSITA and Subaru/HSC surveys, we aim to investigate the dynamical status of the optically selected clusters and to derive the cluster scaling relations. Methods. The sample consists of 43 optically selected galaxy clusters with a richness >40 in the redshift range of 0.16–0.89. We systematically analyzed the X-ray images and emission spectra using the eROSITA data. We identified the brightest cluster galaxy (BCG) using the optical and far-infrared databases. We evaluated the cluster’s dynamical status by measuring three quantities: offset between the X-ray peak and BCG position, the gas concentration parameter, and the number of galaxy-density peaks. We investigated the luminosity–temperature and mass–luminosity relations based on eROSITA X-ray spectra and HSC weak-lensing data analyses. Results. Based on these three measurements, we estimated the fraction of relaxed clusters to be 2(< 39)%, which is smaller than that of the X-ray-selected cluster samples. After correcting for a selection bias due to the richness cut, we obtained a shallow L − T slope of 2.1 ± 0.5, which is consistent with the predictions of the self-similar model and the baseline model incorporating a mass–concentration relation. The L − M slope of 1.5 ± 0.3 is in agreement with the above-cited theoretical models as well as the data on the shear-selected clusters in the eFEDs field. Conclusions. Our analysis of high-richness optical clusters yields a small fraction of relaxed clusters and a shallow slope for the luminosity–temperature relation. This suggests that the average X-ray properties of the optical clusters are likely to be different from those observed in the X-ray samples. Thus, the joint eROSITA and HSC observations are a powerful tool in extending the analysis to a larger sample and understanding the selection effect with a view to establish cluster scaling relations.