Forecasts for Galaxy Cluster Observations and Cosmological Implications from the eROSITA All-Sky Survey
Forecasts for Galaxy Cluster Observations and Cosmological Implications from the eROSITA All-Sky Survey
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DissertationDate of Exam
17.03.2016Date of Publication
19.04.2016Advisor
Reiprich, Thomas H.Co-Referee
Porciani, CristianoMetadata
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Abstract
One of the most commonly asked questions in astrophysics today refers to the nature of dark energy. The characteristics of this parameter are imprinted in the large-scale structure of matter and accordingly also in the distribution of galaxy clusters as tracers of this structure. The up-coming X-ray instrument eROSITA, which is scheduled for launch in 2017, will detect a sample of ~100,000 clusters of galaxies in a total of eight all-sky surveys. These observations are expected to significantly support the study of dark energy. Before the launch of the instrument, it is essential to forecast the expected observations, as well as to prepare the required data analysis strategies. The projects within this thesis support these aims, while focusing on the observations of galaxy clusters and on the cosmological implications from the expected cluster catalogue.
In a first project, I perform predictions on how well eROSITA will be able to detect cluster gas temperatures and redshifts, while simulating realistic spectra for a variety of different clusters. Applying a spectral fit, the cluster properties are re-obtained and subsequently analysed in comparison to the input parameter. Convolving these results with the halo mass function and an assumed instrumental selection function, yields the number of eROSITA clusters with precise characteristics. Accordingly, the instrument will obtain precise temperatures with relative uncertainties of <10% for clusters up to distances of z~0.15. This relates to observations of ~1,700 new clusters with precise properties. Also, redshifts will be accessible from the X-ray data alone up to distances of z~0.45.
For a sub-sample of the above clusters, I additionally test the influence of the pre-analysis to extract the cluster spectra from the observed raw data. This is achieved by generating event files of cluster observations and by reducing them based on the currently developed eROSITA software, eSASS. While the parameter precisions are only minorly influenced by the pre-analysis, the parameter accuracy now shows a bias of >10%. The identification of this and other systematics already initiated an advanced development of the data reduction software.
To quantify the cosmological potential of eROSITA, I convert the halo mass function into a more general abundance function, which is based on the number of observed cluster photons. This function allows the computation of a mockcatalogue of the expected eROSITA clusters, which is highly dependent on cosmology. Implementing this catalogue and the corresponding abundance model into Markov-Chain Monte Carlo simulations yields the credibilities of the cosmological parameters, including the nature of dark energy. These forecasts present the instrument as powerful probe for precision cosmology, where the credibilities from the cluster abundances alone show comparable results to the Planck data with external priors. Combining both data sets allows for relative precisions of 7.7% for w_0 and for an uncertainty on w_a of 0.276. This results in a figure of merit of FoM=53 for the nature of dark energy on the 2-sigma uncertainty level.
In conclusion, eROSITA will allow for precise studies of galaxy cluster properties, while increasing the current sample of clusters with precise temperatures by a factor of 5-10. The on-going development of the data reduction tools will support these expectations. These cluster studies and the resulting large catalogue of objects, will allow for strong and unprecedented cosmological constraints. Based on these results, eROSITA will be classified as the first Stage IV instrument for studying the nature of dark energy.
In a first project, I perform predictions on how well eROSITA will be able to detect cluster gas temperatures and redshifts, while simulating realistic spectra for a variety of different clusters. Applying a spectral fit, the cluster properties are re-obtained and subsequently analysed in comparison to the input parameter. Convolving these results with the halo mass function and an assumed instrumental selection function, yields the number of eROSITA clusters with precise characteristics. Accordingly, the instrument will obtain precise temperatures with relative uncertainties of <10% for clusters up to distances of z~0.15. This relates to observations of ~1,700 new clusters with precise properties. Also, redshifts will be accessible from the X-ray data alone up to distances of z~0.45.
For a sub-sample of the above clusters, I additionally test the influence of the pre-analysis to extract the cluster spectra from the observed raw data. This is achieved by generating event files of cluster observations and by reducing them based on the currently developed eROSITA software, eSASS. While the parameter precisions are only minorly influenced by the pre-analysis, the parameter accuracy now shows a bias of >10%. The identification of this and other systematics already initiated an advanced development of the data reduction software.
To quantify the cosmological potential of eROSITA, I convert the halo mass function into a more general abundance function, which is based on the number of observed cluster photons. This function allows the computation of a mockcatalogue of the expected eROSITA clusters, which is highly dependent on cosmology. Implementing this catalogue and the corresponding abundance model into Markov-Chain Monte Carlo simulations yields the credibilities of the cosmological parameters, including the nature of dark energy. These forecasts present the instrument as powerful probe for precision cosmology, where the credibilities from the cluster abundances alone show comparable results to the Planck data with external priors. Combining both data sets allows for relative precisions of 7.7% for w_0 and for an uncertainty on w_a of 0.276. This results in a figure of merit of FoM=53 for the nature of dark energy on the 2-sigma uncertainty level.
In conclusion, eROSITA will allow for precise studies of galaxy cluster properties, while increasing the current sample of clusters with precise temperatures by a factor of 5-10. The on-going development of the data reduction tools will support these expectations. These cluster studies and the resulting large catalogue of objects, will allow for strong and unprecedented cosmological constraints. Based on these results, eROSITA will be classified as the first Stage IV instrument for studying the nature of dark energy.
Subjects
Kosmologie, Strukturentwicklung, Dunkle Energie, Galaxienhaufen, Spektralanalyse, Röntgenbeobachtungen, Cosmology, Large Scale Structure, Dark Energy, Galaxy Clusters, spectral analysis, X-rays
Classification (DDC)
520 Astronomie, KartografieBorm, Katharina: Forecasts for Galaxy Cluster Observations and Cosmological Implications from the eROSITA All-Sky Survey. - Bonn, 2016. - Dissertation, Rheinische Friedrich-Wilhelms-Universität Bonn.
Online-Ausgabe in bonndoc: https://nbn-resolving.org/urn:nbn:de:hbz:5n-43294
Online-Ausgabe in bonndoc: https://nbn-resolving.org/urn:nbn:de:hbz:5n-43294
@phdthesis{handle:20.500.11811/6747,
urn: https://nbn-resolving.org/urn:nbn:de:hbz:5n-43294,
author = {{Katharina Borm}},
title = {Forecasts for Galaxy Cluster Observations and Cosmological Implications from the eROSITA All-Sky Survey},
school = {Rheinische Friedrich-Wilhelms-Universität Bonn},
year = 2016,
month = apr,
note = {One of the most commonly asked questions in astrophysics today refers to the nature of dark energy. The characteristics of this parameter are imprinted in the large-scale structure of matter and accordingly also in the distribution of galaxy clusters as tracers of this structure. The up-coming X-ray instrument eROSITA, which is scheduled for launch in 2017, will detect a sample of ~100,000 clusters of galaxies in a total of eight all-sky surveys. These observations are expected to significantly support the study of dark energy. Before the launch of the instrument, it is essential to forecast the expected observations, as well as to prepare the required data analysis strategies. The projects within this thesis support these aims, while focusing on the observations of galaxy clusters and on the cosmological implications from the expected cluster catalogue.
In a first project, I perform predictions on how well eROSITA will be able to detect cluster gas temperatures and redshifts, while simulating realistic spectra for a variety of different clusters. Applying a spectral fit, the cluster properties are re-obtained and subsequently analysed in comparison to the input parameter. Convolving these results with the halo mass function and an assumed instrumental selection function, yields the number of eROSITA clusters with precise characteristics. Accordingly, the instrument will obtain precise temperatures with relative uncertainties of <10% for clusters up to distances of z~0.15. This relates to observations of ~1,700 new clusters with precise properties. Also, redshifts will be accessible from the X-ray data alone up to distances of z~0.45.
For a sub-sample of the above clusters, I additionally test the influence of the pre-analysis to extract the cluster spectra from the observed raw data. This is achieved by generating event files of cluster observations and by reducing them based on the currently developed eROSITA software, eSASS. While the parameter precisions are only minorly influenced by the pre-analysis, the parameter accuracy now shows a bias of >10%. The identification of this and other systematics already initiated an advanced development of the data reduction software.
To quantify the cosmological potential of eROSITA, I convert the halo mass function into a more general abundance function, which is based on the number of observed cluster photons. This function allows the computation of a mockcatalogue of the expected eROSITA clusters, which is highly dependent on cosmology. Implementing this catalogue and the corresponding abundance model into Markov-Chain Monte Carlo simulations yields the credibilities of the cosmological parameters, including the nature of dark energy. These forecasts present the instrument as powerful probe for precision cosmology, where the credibilities from the cluster abundances alone show comparable results to the Planck data with external priors. Combining both data sets allows for relative precisions of 7.7% for w_0 and for an uncertainty on w_a of 0.276. This results in a figure of merit of FoM=53 for the nature of dark energy on the 2-sigma uncertainty level.
In conclusion, eROSITA will allow for precise studies of galaxy cluster properties, while increasing the current sample of clusters with precise temperatures by a factor of 5-10. The on-going development of the data reduction tools will support these expectations. These cluster studies and the resulting large catalogue of objects, will allow for strong and unprecedented cosmological constraints. Based on these results, eROSITA will be classified as the first Stage IV instrument for studying the nature of dark energy.},
url = {https://hdl.handle.net/20.500.11811/6747}
}
urn: https://nbn-resolving.org/urn:nbn:de:hbz:5n-43294,
author = {{Katharina Borm}},
title = {Forecasts for Galaxy Cluster Observations and Cosmological Implications from the eROSITA All-Sky Survey},
school = {Rheinische Friedrich-Wilhelms-Universität Bonn},
year = 2016,
month = apr,
note = {One of the most commonly asked questions in astrophysics today refers to the nature of dark energy. The characteristics of this parameter are imprinted in the large-scale structure of matter and accordingly also in the distribution of galaxy clusters as tracers of this structure. The up-coming X-ray instrument eROSITA, which is scheduled for launch in 2017, will detect a sample of ~100,000 clusters of galaxies in a total of eight all-sky surveys. These observations are expected to significantly support the study of dark energy. Before the launch of the instrument, it is essential to forecast the expected observations, as well as to prepare the required data analysis strategies. The projects within this thesis support these aims, while focusing on the observations of galaxy clusters and on the cosmological implications from the expected cluster catalogue.
In a first project, I perform predictions on how well eROSITA will be able to detect cluster gas temperatures and redshifts, while simulating realistic spectra for a variety of different clusters. Applying a spectral fit, the cluster properties are re-obtained and subsequently analysed in comparison to the input parameter. Convolving these results with the halo mass function and an assumed instrumental selection function, yields the number of eROSITA clusters with precise characteristics. Accordingly, the instrument will obtain precise temperatures with relative uncertainties of <10% for clusters up to distances of z~0.15. This relates to observations of ~1,700 new clusters with precise properties. Also, redshifts will be accessible from the X-ray data alone up to distances of z~0.45.
For a sub-sample of the above clusters, I additionally test the influence of the pre-analysis to extract the cluster spectra from the observed raw data. This is achieved by generating event files of cluster observations and by reducing them based on the currently developed eROSITA software, eSASS. While the parameter precisions are only minorly influenced by the pre-analysis, the parameter accuracy now shows a bias of >10%. The identification of this and other systematics already initiated an advanced development of the data reduction software.
To quantify the cosmological potential of eROSITA, I convert the halo mass function into a more general abundance function, which is based on the number of observed cluster photons. This function allows the computation of a mockcatalogue of the expected eROSITA clusters, which is highly dependent on cosmology. Implementing this catalogue and the corresponding abundance model into Markov-Chain Monte Carlo simulations yields the credibilities of the cosmological parameters, including the nature of dark energy. These forecasts present the instrument as powerful probe for precision cosmology, where the credibilities from the cluster abundances alone show comparable results to the Planck data with external priors. Combining both data sets allows for relative precisions of 7.7% for w_0 and for an uncertainty on w_a of 0.276. This results in a figure of merit of FoM=53 for the nature of dark energy on the 2-sigma uncertainty level.
In conclusion, eROSITA will allow for precise studies of galaxy cluster properties, while increasing the current sample of clusters with precise temperatures by a factor of 5-10. The on-going development of the data reduction tools will support these expectations. These cluster studies and the resulting large catalogue of objects, will allow for strong and unprecedented cosmological constraints. Based on these results, eROSITA will be classified as the first Stage IV instrument for studying the nature of dark energy.},
url = {https://hdl.handle.net/20.500.11811/6747}
}
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