Evaluating tests of virialization and substructure using galaxy clusters in the ORELSE survey

Abstract

We evaluated the effectiveness of different indicators of cluster virialization using 12 large-scale structures in the ORELSE survey spanning from 0.7 < z < 1.3. We located diffuse X-ray emission from 16 galaxy clusters using Chandra observations. We studied the properties of these clusters and their members, using Chandra data in conjunction with optical and near-IR imaging and spectroscopy. We measured X-ray luminosities and gas temperatures of each cluster, as well as velocity dispersions of their member galaxies. We compared these results to scaling relations derived from virialized clusters, finding significant offsets of up to 3-4σ for some clusters, which could indicate they are disturbed or still forming. We explored if other properties of the clusters correlated with these offsets by performing a set of tests of virialization and substructure on our sample, including Dressler-Schectman tests, power ratios, analyses of the velocity distributions of galaxy populations, and centroiding differences. For comparison to a wide range of studies, we used two sets of tests: ones that did and did not use spectral energy distribution fitting to obtain rest-frame colours, stellar masses, and photometric redshifts of galaxies. Our results indicated that the difference between the stellar mass or light mean-weighted center and the X-ray center, as well as the projected offset of the most-massive/brightest cluster galaxy from other cluster centroids had the strongest correlations with scaling relation offsets, implying they are the most robust indicators of cluster virialization and can be used for this purpose when X-ray data is insufficiently deep for reliable L X and T X measurements.

Persistence of the colour–density relation and efficient environmental quenching to z ∼ 1.4

“…Alternatively, if the conditions in groups and clusters change by z ∼ 1.4 to reduce the efficacy of ram pressure stripping or harassment, i.e., the differential velocity of galaxies relative to one another or the density of the IGM/ICM decreases, this change would possibly provide some possibility of explaining the observed behavior. However, such a change in conditions is extremely unlikely for the sample of ORELSE clusters as they are observed to contain a well-developed ICM and a galaxy population with a high σ v to the highest redshifts studied here (Blanton et al 2003;Maughan et al 2006;Mehrtens et al 2012;Clerc et al 2014;Rumbaugh et al 2013Rumbaugh et al , 2018. In addition, the average virial mass of the detected clusters and groups in the ORELSE sample does not change appreciably with redshift but rather holds steady in the range log( M vir ) = 14.2 − 14.5 (though see discussion at the end of §3.3).…”

“…The photometric cali-bration of the mosaics output by both pipelines was done selecting bright (m < 15), non-saturated objects with existing Two Micron All Sky Survey (2MASS; Skrutskie et al 2006) photometry, with appropriate k-corrections made using stars drawn from the Infrared Telescope Facility (IRTF) spectral library (Rayner et al 2009). Additional imaging in the NIR was taken from the Spitzer (Werner et al 2004) space observatory using the InfraRed Array Camera (IRAC; Fazio et al 2004) in the two non-cryogenic channels ([3.6]/[4.5]) for all 15 ORELSE fields and additionally in the two cryogenic channels ([5.8]/[8.0]) for four of the ORELSE fields (SC1604, RXJ1716, RXJ1053, and XLSS005 following the naming convention of Rumbaugh et al 2018;Tomczak et al 2019) to an average depth of 24.0, 23.8, 22.4 and 22.3 magnitudes, respectively. The basic calibrated data (cBCD) images provided by the Spitzer Heritage Archive were reduced using the MOsaicker and Point source EXtractor (MOPEX; Makovoz & Marleau 2005) package in conjunction with several custom Interactive Data Language (IDL) scripts written by J. Surace.…”

“…see,Tomczak et al 2017;Rumbaugh et al 2018 and §2.3 for details on detection bands for each ORELSE field.MNRAS 000, 1-27(2019)…”

Establishing a new technique for discovering large-scale structure using the ORELSE survey

“…Finally, to approximate the true number of members, N, for each group/cluster, the above numbers are aperture corrected in an attempt to include those real members that lie at R > R vir . This aperture correction is estimated by multiplying the number of members calculated above by the average ratio of z spec members at R vir to those at 1.5R vir for all of the ORELSE clusters presented in Rumbaugh et al (2018), where the definition of z spec members is the same as that stated earlier in the section. This ratio is computed to be 1/0.68.…”

Extended Radio AGN at z ∼ 1 in the ORELSE Survey: The Confining Effect of Dense Environments

“…It is known that the ICM is plausibly more developed in more massive clusters and at lower redshift at fixed mass, and their ICM density profile is more regular (Newman et al 2013;Rumbaugh et al 2018). As a consequence, the effect of a more developed cluster environment on the size might show a better correlation with the clustocentric radius.…”