XMM-Newton and Chandra Cross Calibration Using HIFLUGCS Galaxy Clusters: Systematic Temperature Differences and Cosmological Impact
arXiv:1404.7130 · doi:10.1051/0004-6361/201424085
Abstract
Cosmological constraints from clusters rely on accurate gravitational mass estimates, which strongly depend on cluster gas temperature measurements. Therefore, systematic calibration differences may result in biased, instrument-dependent cosmological constraints. This is of special interest in the light of the tension between the Planck results of the primary temperature anisotropies of the CMB and Sunyaev-Zel'dovich plus X-ray cluster counts analyses. We quantify in detail the systematics and uncertainties of the cross-calibration of the effective area between five X-ray instruments, EPIC-MOS1/MOS2/PN onboard XMM-Newton and ACIS-I/S onboard Chandra, and the influence on temperature measurements. Furthermore, we assess the impact of the cross calibration uncertainties on cosmology. Using the HIFLUGCS sample, consisting of the 64 X-ray brightest galaxy clusters, we constrain the ICM temperatures through spectral fitting in the same, mostly isothermal, regions and compare them. Our work is an extension to a previous one using X-ray clusters by the IACHEC. Performing spectral fitting in the full energy band we find that best-fit temperatures determined with XMM-Newton/EPIC are significantly lower than Chandra/ACIS temperatures. We demonstrate that effects like multitemperature structure and different relative sensitivities of the instruments at certain energy bands cannot explain the observed differences. We conclude that using XMM-Newton/EPIC, instead of Chandra/ACIS to derive full energy band temperature profiles for cluster mass determination results in an 8% shift towards lower OmegaM values and <1% shift towards higher sigma8 values in a cosmological analysis of a complete sample of galaxy clusters. Such a shift is insufficient to significantly alleviate the tension between Planck CMB anisotropies and SZ plus XMM-Newton cosmological constraints.
Accepted by A&A; Python-Script for modification of XMM-Newton/EPIC and Chandra/ACIS effective areas according to the stacked residual ratios: https://wikis.mit.edu/confluence/display/iachec/Data3
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