| Summary: | 碩士 === 國立臺灣大學 === 天文物理研究所 === 105 === The galaxy cluster sciences have been flourishing in modern times due
to the successful wide field surveys, such as the Sloan Digital Sky Survey
(SDSS), the Hyper Suprime-Cam Subaru Strategic Program (HSC) and the
Dark Energy Survey (DES). To study physical properties of these massive
gravitational systems statistically, mock catalogs are an useful tool for evaluating
statistical uncertainties in measurements and quantifying the observational
selection bias. We present two types of mock catalogs designed for
different purposes in the HSC cluster survey. One is for quantitatively studying
the completeness and purity of the cluster sample, and the other is for
statistical analysis.
1. To validate cross correlation methods, we construct a general photometric
mock galaxy catalog based on the MICE-Grand Challenge Galaxy
Catalog generated by combining Halo Occupation Distribution (HOD)
method with Sub-halo Abundance Matching (SHAM). For the original
MICE galaxy catalog, it covers an area over 5000 deg2 out to redshift
z < 1.4 and is complete down to an intrinsic magnitude Mr < −18.9.
We extract a patch of a 200 deg2
area and derive physical properties
of galaxies, such as stellar mass and photometric redshift, from the DES
and the Vista Hemisphere Survey (VHS) photometry originally provided
by the MICE catalog. We also include observational artifacts, like bright
star masks and irregular survey boundary.
2. For second type of mocks, we present a set of mock galaxy catalogs designed for cluster detection in the HSC survey. The catalogs are generated
using real galaxies identified in the S16A release of HSC survey
and a halo catalog from an N-body simulation. Our mock clusters span
the redshift range from 0.3 to 1.2 with the mass range 1013M⊙ < M200 <
2 × 1014M⊙. To mimic realistic observation conditions, we make use
of the HSC galaxy catalog in the COSMOS field as the field population
and combine it with our mock cluster galaxies, adopting masked regions
where no galaxies are in them. The CAMIRA algorithm is run on 90
such sets of mock catalogs. By cross-matching the result with halo catalogs,
we investigate the purity and completeness of CAMIRA detected
mock clusters, and find that the purity of the CAMIRA mock clusters
is greater than 0.95, which indicates that most of the clusters detected
by CAMIRA are true clusters in mocks. For the completeness, we find
that it is correlated with the halo mass and redshift. The completeness is
high at the high mass end and starts to drop once halo masses are lower
than 1.4 × 1014M⊙. Given a halo mass, the completeness is higher at
lower redshift and becomes lower at higher redshift.
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