2008/06/24 by G. P. Smith, Graham P. Smith, James E. Taylor
Physics and Astronomy · #Astronomy and Astrophysical Research #Astrophysics #Brightest cluster galaxy #Cluster (spacecraft) #Galaxies: Formation, Evolution, Phenomena #Galaxy #Galaxy cluster #Gravitational lens #Physics #Redshift #Stellar, planetary, and galactic studies #Structure formation #Substructure #Weak gravitational lensing #astro-ph
paper · pdf · doi:10.1086/591271
Accepted by ApJL, 4 pages, 2 figures
arxiv created 2008/06/24 · openalex publication_date 2008/07/08 · arxiv updated 2009/12/01 · openalex created_date 2016/06/24 · openalex updated_date 2026/08/05
We use semianalytic models of structure formation to interpret gravitational lensing measurements of substructure in galaxy cluster cores ( R ⩽ 250 h −1 kpc) at z = 0.2. The dynamic range of the lensing-based substructure fraction measurements is well matched to the theoretical predictions, both spanning f sub ∼ 0.05–0.65. The structure formation model predicts that f sub is correlated with cluster assembly history. We use simple fitting formulae to parameterize the predicted correlations: Δ 90 = τ 90 + α 90 log ( f sub ) and Δ 50 = τ 50 + α 50 log ( f sub ) , where Δ 90 and Δ 50 are the predicted lookback times from z = 0.2 to when each theoretical cluster had acquired 90% and 50%, respectively, of the mass it had at z = 0.2. The best-fit parameter values are α 90 = − 1.34 ± 0.79 Gyr , τ 90 = 0.31 ± 0.56 Gyr and α 50 = − 2.77 ± 1.66 Gyr , τ 50 = 0.99 ± 1.18 Gyr . Therefore, (1) observed clusters with f sub ≲ 0.1 (e.g., A383, A1835) are interpreted, on average, to have formed at z ≳ 0.8 and to have suffered ≤10% mass growth since z ≃ 0.4, and (2) observed clusters with f sub ≳ 0.4 (e.g., A68, A773) are interpreted as, on average, forming since z ≃ 0.4 and suffering >10% mass growth in the ~500 Myr preceding z = 0.2, i.e., since z = 0.25. In summary, observational measurements of f sub can be combined with structure formation models to estimate the age and assembly history of observed clusters. The ability to "age date" approximately clusters in this way has numerous applications to the large samples of clusters that are becoming available.