Constraints on the richness–mass relation and the optical-SZE positional offset distribution for SZE-selected clusters

Saro, A.; Bocquet, S.; Rozo, Eduardo; Benson, B. A.; Mohr, J. J.; Rykoff, E. S.; Soares-Santos, M.; Bleem, L. E.; Dodelson, Scott; Melchior, P.; Sobreira, F.; Upadhyay, V.; Weller, J.; Abbott, T. M. C.; Abdalla, F. B.; Allam, S.; Armstrong, R.; Banerji, M.; Bauer, A.; Bayliss, M.; Benoit-Lévy, A.; Bernstein, G. M.; Bertin, E.; Brodwin, M.; Brooks, D.; Buckley-Geer, E.; Burke, D. L.; Carlstrom, J. E.; Capasso, R.; Capozzi, D.; Rosell, A. Carnero; Kind, M. Carrasco; Chiu, I.; Covarrubias, R.; Crawford, T. M.; Crocce, M.; D’Andrea, C. B.; Costa, L. N. da; DePoy, D. L.; Desai, S.; Haan, T. de; Diehl, H. T.; Dietrich, J. P.; Doel, P.; Cunha, C. E.; Eifler, T. F.; Evrard, A. E.; Neto, A. Fausti; Fernández, E.; Flaugher, B.; Fosalba, P.; Frieman, J.; Gangkofner, C.; Gaztañaga, E.; Gerdes, D. W.; Gruen, D.; Gruendl, R. A.; Gupta, N.; Hennig, C.; Holzapfel, W. L.; Honscheid, K.; Jain, Bhuvnesh; James, D. J.; Kuêhn, K.; Kuropatkin, N.; Lahav, O.; Li, T. S.; Lin, Huan; Maia, M. A. G.; March, M.; Marshall, J. L.; Martini, Paul; McDonald, Michael; Miller, C. J.; Miquel, R.; Nord, B.; Ogando, R. L. C.; Plazas, A. A.; Reichardt, Christian; Romer, A. K.; Roodman, A.; Šako, M.; Sánchez, E.; Schubnell, M.; Sevilla-Noarbe, I.; Smith, R. C.; Stalder, B.; Stark, A. A.; Strazzullo, V.; Suchyta, E.; Swanson, M. E. C.; Tarlè, G.; Thaler, J. J.; Thomas, Daniel; Tucker, D. L.; Vikram, V.; Linden, Anja von der; Walker, A. R.; Wechsler, Risa H.; Wester, W. C.; Zenteno, A.; Ziegler, K. E.

doi:10.1093/mnras/stv2141

Cited by 118 publications

(172 citation statements)

References 68 publications

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“…Note that the results of this fit have been used to obtain the completeness and purity curves for different observable M * CL in §5.2. The M * CL |M h relation appears not to evolve with redshift, in agreement with other works (Lin et al 2006;Andreon & Congdon 2014;Saro et al 2015). In Fig.…”

Section: Observable-dark Matter Halo Mass Relationsupporting

confidence: 92%

“…While several efforts have been invested in probing that optical cluster mass tracers can achieve accuracies similar to SZ or X-ray tracers, so far it only has been probed up to moderate redshift (Andreon 2010) or massive clusters (Andreon 2012;Saro et al 2015).…”

Section: Observable-dark Matter Halo Mass Relationmentioning

confidence: 99%

“…Lin et al 2006;Andreon 2010;Andreon & Congdon 2014;Saro et al 2015), we have model the M * CL |M h relation with a log-log relation as follows:…”

Section: Observable-dark Matter Halo Mass Relationmentioning

confidence: 99%

“…The last redshift bin, 0.75 z < 1 is only shown to illustrate our our inability to measure correctly M * CL at this redshift range. While it becomes difficult to compare the values of p1 and p2 with different works due to the dependence of the definition of M * CL on the considered survey (Andreon 2010;Ascaso et al 2015a), or other observable used (Andreon 2012;Saro et al 2015), we can compare the scatter of the relation. The main scatter found for J-PAS is slightly smaller than this measured with the ALHAMBRA survey (Ascaso et al 2015a).…”

Section: Observable-dark Matter Halo Mass Relationmentioning

confidence: 99%

“…Other works have found slightly smaller scatter for a sample of clusters ranging a similar range of redshift but five times more massive that in this work. For instance, Saro et al (2015) find > 0.065 dex for very massive > 8 × 10…”

Section: Observable-dark Matter Halo Mass Relationmentioning

confidence: 99%

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An accurate cluster selection function for the J-PAS narrow-band wide-field survey

Ascaso

Benı́tez

Dupke

et al. 2016

Mon. Not. R. Astron. Soc.

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The impending Javalambre Physics of the accelerating universe Astrophysical Survey (J-PAS) will be the first wide-field survey of 8500 deg 2 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% 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% completeness and purity is M h ∼ 5 × 10 13 M ⊙ up to z ∼ 0.7. We also model the optical observable, M * CL -halo mass relation, finding a non-evolution with redshift and main scatter of σ M * CL |M h ∼ 0.14 dex down to a factor two lower in mass than other planned broad-band stage IV surveys, at least. For the M h ∼ 1 × 10 14 M ⊙ Planck mass limit, J-PAS will arrive up to z ∼ 0.85 with a σ M * CL |M h ∼ 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.

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Section: Observable-dark Matter Halo Mass Relationsupporting

confidence: 92%

Section: Observable-dark Matter Halo Mass Relationmentioning

confidence: 99%

“…Lin et al 2006;Andreon 2010;Andreon & Congdon 2014;Saro et al 2015), we have model the M * CL |M h relation with a log-log relation as follows:…”

Section: Observable-dark Matter Halo Mass Relationmentioning

confidence: 99%

Section: Observable-dark Matter Halo Mass Relationmentioning

confidence: 99%

Section: Observable-dark Matter Halo Mass Relationmentioning

confidence: 99%

See 3 more Smart Citations

An accurate cluster selection function for the J-PAS narrow-band wide-field survey

Ascaso

Benı́tez

Dupke

et al. 2016

Mon. Not. R. Astron. Soc.

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Cluster richness–mass calibration with cosmic microwave background lensing

Geach

Peacock

2017

Nat Astron

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Identifying galaxy clusters through overdensities of galaxies in photometric surveys is the oldest 1,2 and arguably the most economic and mass-sensitive detection method, 3,4 compared to X-ray [5][6][7] and SunyaevZel'dovich Effect 8 surveys that detect the hot intracluster medium. However, a perrennial problem has been the mapping of optical 'richness' measurements on to total cluster mass. 3,[9][10][11][12] Emitted at a conformal distance of 14 gigaparsecs, the cosmic microwave background acts as a backlight to all intervening mass in the Universe, and therefore has been gravitationally lensed. [13][14][15] Here we present a calibration of cluster optical richness at the 10 per cent level by measuring the average cosmic microwave background lensing convergence measured by Planck towards the positions of large numbers of optically-selected clusters, detecting the deflection of photons by haloes of total mass of the order 10 14 M . Although mainly aimed at the study of larger-scale structures, the Planck lensing reconstruction can yield nearly unbiased results for stacked clusters on arcminute scales. The lensing convergence only depends on the redshift integral of the fractional overdensity of matter, so this approach offers a clean measure of cluster mass over most of cosmic history, largely independent of baryon physics.Experiments such as the Atacama Cosmology Telescope (ACT), 16 South Pole Telescope (SPT) 17 and the Planck 18 satellite have now detected gravitational lensing of the cosmic microwave background (CMB) and produced large-area maps of lensing potential that detect features on 10-arcminute scales, effectively representing the projected mass density of the Universe back to the surface of last scattering. This offers a new method of understanding how visible matter traces the overall matter density field. 19,20 Clusters of galaxies are the rarest peaks in the matter density field and contain the most massive and oldest galaxies at any epoch; for this reason, they are simultaneously powerful cosmological probes 21 and unique environments for studying galaxy evolution. Naturally, clusters are expected to be strong deflectors of CMB photons, and therefore should be detectable, at least statistically, in maps of the CMB lensing field. This was first demonstrated with the 3.1σ detection of the lensing signal of 512 Sunyaev-Zel'dovich Effect (SZE) seleted clusters in SPT data, 22 where the lensing-and SZE-derived cluster masses were found to be in agreement. A 3.2σ statistical lensing signal was also detected in the ACT lensing map for 12,000 optically-selected galaxies, thought to reside on average in group-scale halos M ≈ 10 13 M , 23 demonstrating how the radial profile of the lensing convergence can be used to estimate the projected mass density around the target galaxies. 15,25 We now extend this to more massive systems over 1 /3 of the sky. The convergence of the lensing field caused by a foreground mass can be expressed in the classical lensing framework in terms of the projected mass density aswh...

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A new method to assign galaxy cluster membership using photometric redshifts

Castignani

Benoist

2016

A&A

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We introduce a new effective strategy to assign group and cluster membership probabilities Pmem to galaxies using photometric redshift information. Large dynamical ranges both in halo mass and cosmic time are considered. The method takes into account the magnitude distribution of both cluster and field galaxies as well as the radial distribution of galaxies in clusters using a non-parametric formalism, and relies on Bayesian inference to take photometric redshift uncertainties into account. We successfully test the method against 1, 208 galaxy clusters within redshifts z = 0.05−2.58 and masses 10 13.29−14.80 M drawn from wide field simulated galaxy mock catalogs mainly developed for the forthcoming Euclid mission. Median purity and completeness values of (55 +17 −15 )% and (95 +5 −10 )% are reached for galaxies brighter than 0.25L * within r200 of each simulated halo and for a statistical photometric redshift accuracy σ((zs −zp)/(1+zs)) = 0.03.The mean values p = 56% and c = 93% are consistent with the median and have negligible sub-percent uncertainties. Accurate photometric redshifts (σ((zs − zp)/(1 + zs)) 0.05) and robust estimates for the cluster redshift and cluster center coordinates are required. The dependence of the assignments on photometric redshift accuracy, galaxy magnitude and distance from the halo center, and halo properties such as mass, richness, and redshift are investigated. Variations in the mean values of both purity and completeness are globally limited to a few percent. The largest departures from the mean values are found for galaxies associated with distant z 1.5 halos, faint (∼ 0.25 L * ) galaxies, and those at the outskirts of the halo (at cluster-centric projected distances ∼ r200) for which the purity is decreased, ∆p 20% at most, with respect to the mean value. The proposed method is applied to derive accurate richness estimates. A statistical comparison between the true (Ntrue) vs. estimated richness (λ = Pmem) yields on average to unbiased results, Log(λ/Ntrue) = −0.0051 ± 0.15. The scatter around the mean of the logarithmic difference between λ and the halo mass is 0.10 dex for massive halos 10 14.5 M . Our estimates could therefore be useful to constrain the cluster mass function and to calibrate independent cluster mass estimates such as those obtained from weak lensing, Sunyaev-Zel'dovich, and X-ray studies. Our method can be applied to any list of galaxy clusters or groups in both present and forthcoming surveys such as SDSS, CFHTLS, Pan-STARRS, DES, LSST, and Euclid.

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Constraints on the richness–mass relation and the optical-SZE positional offset distribution for SZE-selected clusters

Cited by 118 publications

References 68 publications

An accurate cluster selection function for the J-PAS narrow-band wide-field survey

An accurate cluster selection function for the J-PAS narrow-band wide-field survey

Cluster richness–mass calibration with cosmic microwave background lensing

A new method to assign galaxy cluster membership using photometric redshifts

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