Volume 409, Number 2, October II 2003
|Page(s)||449 - 457|
|Section||Cosmology (including clusters of galaxies)|
|Published online||17 November 2003|
Arc statistics in cosmological models with dark energy
Max-Planck-Institut für Astrophysik, PO Box 1317, 85741 Garching, Germany
2 Dipartimento di Astronomia, Università di Padova, vicolo dell'Osservatorio 2, 35122 Padova, Italy
3 Osservatorio Astronomico di Padova, Vicolo dell'Osservatorio 5, 35122 Padova, Italy
4 Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA
5 SISSA/ISAS, via Beirut 4, 34014 Trieste, Italy
6 Dipartimento di Astronomia, via Ranzani 1, 40127 Bologna, Italy
Corresponding author: M. Bartelmann, firstname.lastname@example.org
Accepted: 18 July 2003
We investigate how the probability of the formation of giant arcs in galaxy clusters is expected to change in cosmological models dominated by dark energy with an equation of state compared to cosmological-constant or open models. To do so, we use a simple analytic model for arc cross sections based on the Navarro-Frenk-White density profile which we demonstrate reproduces essential features of numerically determined arc cross sections. Since analytic lens models are known to be inadequate for accurate absolute quantifications of arc probabilities, we use them only for studying changes relative to cosmological-constant models. Our main results are (1) the order of magnitude difference between the arc probabilities in low density, spatially flat and open CDM models found numerically is reproduced by our analytic model, and (2) dark-energy cosmologies with increase the arc optical depth by at most a factor of two and are thus unlikely to reconcile arc statistics with spatially flat cosmological models with low matter density.
Key words: galaxies: clusters: general / cosmology: theory / cosmology: dark matter / cosmology: gravitational lensing
© ESO, 2003
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.