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Título: | An accurate cluster selection function for the J-PAS narrow-band wide-field survey |
Autor: | Ascaso, Begoña CSIC ORCID; Benítez, Narciso CSIC ORCID; Marín-Franch, Antonio | Palabras clave: | Miscellaneous - cosmology Observations - dark matter - large-scale structure of Universe General - cosmology Clusters Surveys - galaxies |
Fecha de publicación: | 2016 | Editor: | Blackwell Publishing | Citación: | Monthly Notices of the Royal Astronomical Society 456: 4291- 4304 (2016) | Resumen: | The impending Javalambre Physics of the accelerating Universe Astrophysical Survey (J-PAS) will be the first wide-field survey of ≳ 8500 deg2 to reach the 'stage IV' category. Because of the redshift resolution afforded by 54 narrow-band filters, J-PAS is particularly suitable for cluster detection in the range z<1. The photometric redshift dispersion is estimated to be only ~0.003 with few outliers ≁4 per cent for galaxies brighter than i ~ 23 AB, because of the sensitivity of narrow band imaging to absorption and emission lines. Here, we evaluate the cluster selection function for J-PAS using N-body+semi-analytical realistic mock catalogues. We optimally detect clusters from this simulation with the Bayesian Cluster Finder, and we assess the completeness and purity of cluster detection against the mock data. The minimum halo mass threshold we find for detections of galaxy clusters and groups with both>80 per cent completeness and purity is M ~ 5 × 10M⊙ up to z ~ 0.7. We also model the optical observable, M-halo mass relation, finding a non-evolution with redshift and main scatter of σM|M ~ 0.14 dex down to a factor 2 lower in mass than other planned broad-band stage IV surveys, at least. For the M ~ 1 × 10M⊙ Planck mass limit, J-PAS will arrive up to z ~ 0.85 with a σM|M ~ 0.12 dex. Therefore, J-PAS will provide the largest sample of clusters and groups up to z ~ 0.8 with a mass calibration accuracy comparable to X-ray data. © 2016 The Authors. | URI: | http://hdl.handle.net/10261/150260 | DOI: | 10.1093/mnras/stv2988 | Identificadores: | doi: 10.1093/mnras/stv2988 issn: 1365-2966 |
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IAA_2016_MNRASstv2988.pdf | 1,71 MB | Adobe PDF | Visualizar/Abrir |
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