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Project information
Project information
Project leads: Hung-Yu Jian (ASIAA), Yen-Ting Lin (ASIAA), and Keiichi Umetsu (ASIAA), Lihwai Lin (ASIAA), Bau-Ching Hsieh (ASIAA)
Point of contact: Hung-Yu Jian (hyjian@asiaa.sinica.edu.tw)
Rubin project code: TAI-ASI-S4
Relevant working groups:
Project status: Active
Rationale
Rationale
Galaxy clusters are the largest gravitationally bound structures in the Universe, containing hundreds to thousands of galaxies embedded within massive halos of dark matter and hot intracluster gas. As such, they serve as powerful laboratories for studying a wide range of astrophysical and cosmological phenomena, including the nature of dark matter and dark energy through gravitational lensing, galaxy evolution through environmentally driven star-formation quenching, and the properties of the intracluster medium (ICM).
Galaxy clusters can be identified using a variety of observational techniques, including their X-ray emission, the thermal Sunyaev–Zel'dovich effect produced by the inverse Compton scattering of cosmic microwave background photons by the hot intracluster plasma, the gravitational lensing distortions they induce in background galaxies, and the optical distribution of their member galaxies.
Various methods have been developed to identify galaxy groups and clusters in photometric galaxy catalogs. Among them, the Probability Friends-of-Friends (pFOF) algorithm (see also here) is specifically designed to identify galaxy groups in datasets with photometric-redshift uncertainties. The algorithm requires only the sky positions (right ascension and declination), photometric and/or spectral redshifts, and their associated redshift probability distribution functions (PDFs). Consequently, pFOF provides an objective group-finding approach that is independent of assumptions about galaxy colors or requiring a red sequence, setting it apart from traditional red-sequence cluster detection algorithms.
Developed as part of the LSST in-kind contributions, this project provides both group/cluster catalogs and their associated member-galaxy catalogs for the LSST Galaxy Science Collaboration.
Results
Results
(1) Performance of the pFOF on DC2 Catalog
The pFOF algorithm was evaluated on DEmP DC2 data products, using photometric redshifts (photo-z) and their associated redshift probability distribution functions (PDFs) as input features.
For a detected pFOF group with N_pFOF member galaxies, purity (p) is defined as:
p = N1/N_pFOF,
where N1 represents the number of member galaxies common to both the detected pFOF group and its corresponding true DC2 group.
For a true DC2 group with N_true member galaxies, completeness (c) is defined as:
c = N2/N_true,
where N2 is the number of shared member galaxies between the true DC2 group and the detected pFOF group.
To quantify the group-finding performance, we adopt the one-way purity (p1) and one-way completeness (c1). An identified pFOF group is considered a successful one-way detection if its purity satisfies p >=0.5, in which case p1 = 1; otherwise, p1 = 0. Likewise, a true DC2 group is regarded as successfully recovered if its completeness satisfies c >= 0.5, in which case c1 = 1; otherwise, c1 = 0.
For this analysis, we require each detected pFOF group to contain at least 10 member galaxies and restrict the sample to the redshift range 0.02 < z < 1.4. Under these criteria, the optimal average one-way purity and completeness are found to be p1 = 0.42 and c1 = 0.485, respectively.
The pFOF grouping performance is summarized as follows.
(i) Purity and Completeness as a function of the richness λ:
(ii) Purity and Completeness as a function of the redshift:
Furthermore, following the evaluation framework from AMICO (Bellagamba et al. 2018), matching between detected and mock clusters required a projected spatial separation dr <= 1 Mpc/h and a redshift offset dz <= 0.1. Under these constraints, pFOF achieves an average purity of 0.51 and a completeness of 0.86. The full performance trends are detailed below.
(i) Purity and Completeness as a function of the redshift:
(ii) Purity and Completeness as a function of the richness λ:
Moreover, we evaluate the pFOF performance by adopting the redMapper cosmoDC2 catalog as the reference catalog within a sub-area. We find that p1 = 0.999 and c1 = 0.338, indicating that pFOF successfully identifies the redMapper clusters it detects, but recovers only approximately 34% of the redMapper clusters in the reference sample. For comparison, when evaluating the performance of redMapper using the true DC2 clusters as the reference catalog within the same sub-area, we obtain p1 = 0.496 and c1 = 0.309.
Talks and presentations
Talks and presentations
Outputs
Outputs
Connections to other projects
Connections to other projects
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