PostDoc, Harvard-Smithsonian Center for Astrophysics


First X-ray study that analyses galaxy clusters individually for a cosmological framework

Modern cosmology traces the history and predicts the fate of our Universe. Great achievements have been made by the discovery of the accelerated expansion, the claim for Dark Matter and Dark Energy which are both still highly unknown concepts. Today, the “dark” constituents of our Universe are of special interest; the former one as the additional matter component which does not behave like any other form of matter we know, and the latter a still mysterious force driving the expansion of the Universe. I investigate those by looking at the largest clearly defined structures in the Universe, called galaxy clusters. Galaxy clusters can contain thousands of galaxies and evolve from collapsed overdensities in the early Universe, and therefore witness its history. The X-ray regime takes a key role to observe galaxy clusters due to the visibility of the hot plasma between the galaxies, which is the most massive component that we can observe. The aim of this work is to analyze a complete sample of galaxy clusters in detail and constrain some of the most important cosmological parameters, the relative amount of matter in the Universe, and the amplitude of density fluctuations in the early Universe, which later collapsed to form structures like our Milky Way. High quality X-ray data of the brightest galaxy clusters enables me to set a new baseline for galaxy cluster cosmology in terms of statistic and by quantifying the various biases arising from such an analysis, which I describe in the following: The calibration of X-ray instruments is challenging, because of the absence of absolute calibration targets. In my cross calibration study of 5 X-ray detectors I find systematic differences, which cause temperature measurements of the galaxy cluster gas to be biased up to 23%. In this study I also introduce tests to estimate not only the relative difference of the instrumental calibrations, but point towards the absolute calibration, to ultimately find the best calibrated instrument. Other complications to estimate the galaxy cluster mass are connected to assumptions on the physical state of the hot gas, that have to be made: Especially clusters with lower mass are more affected by non-gravitational effects like very violent ouflows from supermassive black holes within the galaxies of these clusters. This study is of highest importance for the fundamental understanding of the largest objects in our Universe, and setting a baseline for future studies.


ICM cooling, AGN feedback and BCG properties of galaxy groups-Five properties where groups differ from clusters

Abstract: Using Chandra data for a sample of 26 galaxy groups, we constrained the central cooling times (CCTs) of the ICM and classified the groups as strong cool-core (SCC), weak cool-core (WCC) and non-cool-core (NCC) based on their CCTs. The total radio luminosity of the brightest cluster galaxy (BCG) was obtained using radio catalog data and literature, which was compared to the CCT to understand the link between gas cooling and radio output. We determined K-band luminosities of the BCG with 2MASS data, and used it to constrain the masses of the SMBH, which were then compared to the radio output. We also tested for correlations between the BCG luminosity and the overall X-ray luminosity and mass of the group. The observed cool-core/non-cool-core fractions for groups are comparable to those of clusters. However, notable differences are seen. For clusters, all SCCs have a central temperature drop, but for groups, this is not the case as some SCCs have centrally rising temperature profiles. While for the cluster sample, all SCC clusters have a central radio source as opposed to only 45% of the NCCs, for the group sample, all NCC groups have a central radio source as opposed to 77% of the SCC groups. For clusters, there are indications of an anticorrelation trend between radio luminosity and CCT which is absent for the groups. Indications of a trend of radio luminosity with black hole mass observed in SCC clusters is absent for groups. The strong correlation observed between the BCG luminosity and the cluster X-ray luminosity/cluster mass weakens significantly for groups. We conclude that there are important differences between clusters and groups within the ICM cooling/AGN feedback paradigm.

Pub.: 31 Mar '14, Pinned: 30 Jun '17

XMM-Newton and Chandra Cross Calibration Using HIFLUGCS Galaxy Clusters: Systematic Temperature Differences and Cosmological Impact

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.

Pub.: 05 Dec '14, Pinned: 30 Jun '17

Reconciling Planck cluster counts and cosmology? Chandra/XMM instrumental calibration and hydrostatic mass bias

Abstract: The mass of galaxy clusters can be inferred from the temperature of their X-ray emitting gas, $T_{\mathrm{X}}$. Their masses may be underestimated if it is assumed that the gas is in hydrostatic equilibrium, by an amount $b^{\mathrm{hyd}}\sim(20\pm10)$ % suggested by simulations. We have previously found consistency between a sample of observed \textit{Chandra} X-ray masses and independent weak lensing measurements. Unfortunately, uncertainties in the instrumental calibration of {\em Chandra} and {\em XMM-Newton} observatories mean that they measure different temperatures for the same gas. In this paper, we translate that relative instrumental bias into mass bias, and infer that \textit{XMM-Newton} masses of $\sim 10^{14}\,\mbox{M}_{\odot}$ ($> 5\cdot 10^{14} \mbox{M}_{\odot}$) clusters are unbiased ($\sim 35$ % lower) compared to WL masses. For massive clusters, \textit{Chandra}'s calibration may thus be more accurate. The opposite appears to be true at the low mass end. We observe the mass bias to increase with cluster mass, but presence of Eddington bias precludes firm conclusions at this stage. Nevertheless, the systematic \textit{Chandra} -- \textit{XMM-Newton} difference is important because {\em Planck}'s detections of massive clusters via the Sunyaev-Zeldovich (SZ) effect are calibrated via {\em XMM-Newton} observations. The number of detected SZ clusters are inconsistent with {\em Planck}'s cosmological measurements of the primary Cosmic Microwave Background (CMB). Given the \textit{Planck} cluster masses, if an (unlikely) uncorrected $\sim 20$ % calibration bias existed, this tension would be eased, but not resolved.

Pub.: 07 Jan '15, Pinned: 30 Jun '17

HICOSMO - Cosmology with a complete sample of galaxy clusters: II. Cosmological results

Abstract: The growth of structure in the Universe is tightly correlated with the cosmological parameters. Galaxy clusters as tracers of the large scale structure are the ideal objects to witness this evolution. The X-ray bright, hot gas in the potential well of a galaxy cluster enables systematic X-ray studies of samples of galaxy clusters to constrain cosmological parameters. HIFLUGCS consists of the 64 X-ray brightest clusters in the Universe, building up a local sample of galaxy clusters. Here we utilize this sample to determine, for the first time, individual hydrostatic mass estimates for all the clusters of the sample and, by making use of the completeness of the sample, we quantify constraints on the two interesting cosmological parameters, OmegaM and sigma8. In paper I we describe the data analysis procedure and compared the individual mass estimates with other references. Now we apply the total hydrostatic and gas mass estimates from the X-ray analysis to a Bayesian cosmological likelihood analysis and leave several parameters free to be constrained. We find OmegaM = 0.30+-0.01 and sigma8 = 0.79+-0.03 (statistical uncertainties, 68% credibility level) using our default analysis strategy combining both, a mass function analysis and the gas mass fraction results. The main sources of biases that we also correct here are (1) the influence of galaxy groups, (2) the hydrostatic mass bias, (3) the extrapolation of the total mass, (4) the theoretical halo mass function and (5) other physical effects. We find that galaxy groups introduce a strong bias, since their number density seems to be over predicted by the halo mass function. On the other hand, baryonic effects as incorporated by recent hydrodynamical simulations do not result in a significant change in the constraints. The total systematic uncertainties (20%) clearly dominate the statistical uncertainties on cosmological parameters.

Pub.: 16 May '17, Pinned: 30 Jun '17

HICOSMO - Cosmology with a complete sample of galaxy clusters: I. Data analysis, sample selection and luminosity-mass scaling-relation

Abstract: The X-ray regime, where the most massive visible component of galaxy clusters, the intra cluster medium (ICM), is visible, offers directly measured quantities, like the luminosity, and derived quantities, like the total mass, to characterize these objects. The aim of this project is to analyze a complete sample of galaxy clusters in detail and constrain cosmological parameters, like the matter density, OmegaM, or the amplitude of initial density fluctuations, sigma8. The purely X-ray flux-limited sample (HIFLUGCS) consists of the 64 X-ray brightest galaxy clusters, which are excellent targets to study the systematic effects, that can bias results. We analyzed in total 196 Chandra observations of the 64 HIFLUGCS clusters, with a total exposure time of 7.7 Ms. Here we present our data analysis procedure (including an automated substructure detection and an energy band optimization for surface brightness profile analysis) which gives individually determined, robust total mass estimates. These masses are tested against dynamical and Planck Sunyaev-Zeldovich (SZ) derived masses of the same clusters, where good overall agreement is found with the dynamical masses. The Planck SZ masses seem to show a mass dependent bias to our hydrostatic masses; possible biases in this mass-mass comparison are discussed including the Planck selection function. Furthermore, we show the results for the 0.1-2.4-keV-luminosity vs. mass scaling-relation. The overall slope of the sample (1.34) is in agreement with expectations and values from literature. Splitting the sample into galaxy groups and clusters reveals, even after a selection bias correction, that galaxy groups exhibit a significantly steeper slope (1.88) compared to clusters (1.06).

Pub.: 16 May '17, Pinned: 30 Jun '17