Astronomy and Astrophysics – Astrophysics – High Energy Astrophysical Phenomena
Scientific paper
2009-12-21
Astronomy and Astrophysics
Astrophysics
High Energy Astrophysical Phenomena
14 pages, 3 figures, Accepted for publication in the Astrophysical Journal Letters
Scientific paper
We present the mass-X-ray observable scaling relationships for clusters of galaxies using the XMM-Newton cluster catalog of Snowden et al. Our results are roughly consistent with previous observational and theoretical work, with one major exception. We find 2-3 times the scatter around the best fit mass scaling relationships as expected from cluster simulations or seen in other observational studies. We suggest that this is a consequence of using hydrostatic mass, as opposed to virial mass, and is due to the explicit dependence of the hydrostatic mass on the gradients of the temperature and gas density profiles. We find a larger range of slope in the cluster temperature profiles at r_{500} than previous observational studies. Additionally, we find only a weak dependence of the gas mass fraction on cluster mass, consistent with a constant. Our average gas mass fraction results argue for a closer study of the systematic errors due to instrumental calibration and analysis method variations. We suggest that a more careful study of the differences between various observational results and with cluster simulations is needed to understand sources of bias and scatter in cosmological studies of galaxy clusters.
Davis David S.
Juett Adrienne M.
Mushotzky Richard
No associations
LandOfFree
Testing the Reliability of Cluster Mass Indicators with a Systematics Limited Dataset does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Testing the Reliability of Cluster Mass Indicators with a Systematics Limited Dataset, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Testing the Reliability of Cluster Mass Indicators with a Systematics Limited Dataset will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-301765