The miniJPAS survey: cluster and galaxy group detections with AMICO - Maturi, Matteo; Finoguenov, A.; Lopes, P. A. A.; González Delgado, R. M.; Dupke, R. A.; Cypriano, E. S.; Carrasco, E. R.; Diego, J. M.; Penna-Lima, M.; Doubrawa, L.; Vílchez, J. M.; Moscardini, L.; et al. (Astronomy and astrophysics, 2023)
Methods. We used the Adaptive Matched Identiﬁer of Clustered Objects (AMICO) algorithm to detect and characterize groups and clusters of galaxies down to S /N = 2.5 in the redshift range 0.05 < z < 0.8. - Results. We detected 80, 30, and 11 systems with signal-to-noise ratios higher than 2.5, 3.0, and 3.5, respectively, down to ∼1013 M h−1. We derive mass-proxy scaling relations based on Chandra and XMM-Newton X-ray data for the signal amplitude returned by AMICO, the intrinsic richness, and a new proxy that incorporates the galaxies’ stellar masses. This proxy is made possible thanks to the J-PAS ﬁlters and shows a smaller scatter with respect to the richness. We fully characterize the sample and use AMICO to derive a probabilistic membership association of galaxies with the detected groups that we test against spectroscopy. We further show how the narrow-band ﬁlters of J-PAS provide a gain of up to 100% in signal-to-noise ratio in detection and an uncertainty on the redshift of clusters of only σz = 0.0037(1 + z), placing J-PAS between broad-band photometric and spectroscopic surveys. - Conclusions. The performance of AMICO and J-PAS with respect to mass sensitivity, mass-proxies quality, and redshift accuracy will allow us to derive cosmological constraints not only based on cluster counts, but also based on clustering of galaxy clusters.
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