論文の公開元へStatistical analyses of optically selected galaxy clusters from Subaru Hyper Suprime-Cam
概要
Cosmological observations in the last twenty years have established the standard Λdominated Cold Dark Matter (ΛCDM) cosmological model based on General Relativity for the gravity theory thanks to the increasing amount of observational data. It is essential to validate the consistency of this model with other independent cosmological probes or to constrain extensions of the standard model such as self-interacting dark matter, time-evolving dark energy, and modified gravity with observational data.
Galaxy clusters are the most massive gravitationally bound structure in the Universe, which form in dark matter halos after interactions between gravitational dynamics and baryonic process related to galaxy formation. Observations of galaxy clusters in the literature have revealed and constrained the existence and nature of dark matter, dark energy, baryonic matter, and galaxy evolution and formation with other cosmological and observational probes.
Given the smaller number of such massive dark matter halos in which galaxy clusters reside, we require deep imaging data from wide field-of-view surveys to investigate the statistical properties of galaxy clusters over a wide redshift range. The recent development of wide-field optical imaging surveys such as the Hyper SuprimeCam Subaru Strategic Program (HSC-SSP) makes an optical selection of galaxy clusters based on red member galaxies in such cluster regions particularly powerful, typically with a larger number of galaxy clusters than those selected by X-ray or radio wavelengths at present.
With the same imaging data, such wide-field optical imaging surveys also enable us to calibrate the relation of galaxy cluster mass (M) and the number of red member galaxies above some luminosity threshold for each cluster (N), called optical richness, through weak gravitational lensing effects around galaxy clusters by statistically averaging over a large number of weakly and systematically deformed shapes of distant galaxies to reveal their mass profiles with equal sensitivity to the dark and baryonic matter. Constraining this mass-richness relation via weak gravitational lensing is fundamentally important to connect theories or simulations with observations on galaxy clusters, since the halo mass determine the physical properties dominantly such as density profiles of dark matter halo and galaxy evolution and formation physics. Also, constraining the mass distribution function of dark matter halos at galaxy cluster mass scales leads to cosmological parameter estimations.
Among the physical properties of galaxy clusters, the splashback radius has been recently proposed as a physical boundary of dark matter halos at the outskirts from a suite of high-resolution N-body simulations, which separates orbiting from accreting materials (e.g., dark matter and galaxies) as a sharp density edge. At the splashback radius, the logarithmic derivative of density profiles is predicted to drop significantly over a narrow range of radius due to piling up of materials with small radial velocities at their first orbital apocenter after infall into halos. Importantly, recent observational constraints from different survey data in the literature on the splashback radius around optically selected galaxy clusters from an optical cluster-finding algorithm, called redMaPPer, have shown that the observed splashback radius is ~20% smaller than that predicted by N-body simulations under the ΛCDM model at a high significance (~4σ), with the help of the mass-richness relation from weak gravitational lensing effects. These observations with high signal-to-noise ratios are based on statistical measurements of projected photometric galaxy densities around galaxy clusters, since dynamics of galaxies are expected to follow dark matter distribution in the outskirts based on gravitational potentials dominantly determined by the larger amount of dark matter. The dependence of the splashback radius on new physics such as self-interacting dark matter, time-evolving dark energy, and modified gravity have been investigated in the literature over the last five years to try to explain the deviation in the observed splashback radius from the standard model. The features of the splashback radius have also been known as probes of galaxy formation and evolution with galaxy color or magnitude cuts.
In this thesis, we present observational and statistical studies of optically selected galaxy clusters on the mass-richness relation and the splashback radius with mock simulation analyses. We employ the data catalogs from the ongoing HSC-SSP with the Subaru telescope for optically selected galaxy clusters, weak lensing analyses, and photometric galaxies. We use ~2000 optically selected galaxy clusters from the independent cluster-finding algorithm, called CAMIRA, at a wide cluster redshift range of 0.1
First, we measure stacked weak lensing profiles around the HSC CAMIRA clusters over the wide redshift range. We detect lensing signals around high-redshift clusters at 0.7
Second, we present analyses on the splashback radius of the HSC CAMIRA clusters with the results of the analysis for the mass-richness relation. We detect the splashback feature from the projected cross-correlation measurements between the clusters and photometric galaxies over the wide redshift range, including for high redshift clusters at 0.7
Hence, for the first time, we conclude that the observed splashback radii are consistent with the theoretical predictions based on the ΛCDM model and our massrichness relation from weak lensing effects for the HSC CAMIRA clusters at our precisions over the wide redshift range (~15% for each bin of 0.1
We can improve precisions on measurements of the mass-richness relation and the splashback radius by employing the upcoming full HSC survey data or other future survey data in various wavelengths, including X-ray and radio, in order to study cosmological and astrophysical aspects of galaxy clusters and the Universe itself in more detail. Our observational results with the CAMIRA clusters and our analysis frameworks and methodology for the observational data and mock observations are informative to conduct such analyses with properly accounting for the selection effects in the near future.
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