Related papers: Cluster optical depth and pairwise velocity estima…
We adapt a non-linear filter proposed by Hu 2001 for detecting lensing of the CMB by large-scale structures to recover surface-density profiles of galaxy clusters from their localised, weak gravitational lensing effect on CMB fields.…
We present 13.9-18.2 GHz observations of the Sunyaev-Zel'dovich (SZ) effect towards Abell 2146 using the Arcminute Microkelvin Imager (AMI). The cluster is detected with a peak SNR ratio of 13 sigma in the radio source subtracted map.…
Galaxy cluster masses help to constrain cosmological parameters through the halo mass function. To get rid of major biases in the mass measurement, we directly probe the cluster gravitational potentials by observing their gravitational…
There are several supervised machine learning methods used for the application of automated morphological classification of galaxies; however, there has not yet been a clear comparison of these different methods using imaging data, or a…
We present a modern machine learning approach for cluster dynamical mass measurements that is a factor of two improvement over using a conventional scaling relation. Different methods are tested against a mock cluster catalog constructed…
Machine learning can accelerate cosmological inferences that involve many sequential evaluations of computationally expensive data vectors. Previous works in this series have examined how machine learning architectures impact emulator…
Galaxy-scale strong lenses in galaxy clusters provide a unique tool to investigate their inner mass distribution and the sub-halo density profiles in the low-mass regime, which can be compared with the predictions from cosmological…
We have developed a machine learning algorithm capable of detecting ``out-of-domain data'' for trustworthy cosmological inference. By using data from two separate suites of cosmological simulations, we show that our algorithm is able to…
Galaxy clusters can be used as powerful cosmological probes, provided one can obtain accurate mass estimates, which requires a precise knowledge of the underlying astrophysics of galaxy clusters. For these purposes, spatially resolved…
Future high-resolution microwave background measurements hold the promise of detecting galaxy clusters throughout our Hubble volume through their Sunyaev-Zel'dovich (SZ) signature, down to a given limiting flux. The number density of galaxy…
We outline our methods for obtaining high precision mass profiles, combining independent weak-lensing distortion, magnification, and strong-lensing measurements. For massive clusters the strong and weak lensing regimes contribute equal…
Making mock simulated catalogs is an important component of astrophysical data analysis. Selection criteria for observed astronomical objects are often too complicated to be derived from first principles. However the existence of an…
We examine the ability of the future Planck mission to provide a catalogue of galaxy clusters observed via their SZ distortion in the cosmic microwave background. For this purpose we produce full-sky SZ maps based on N-body simulations and…
The hot ionized gas of the intra-cluster medium emits thermal radiation in the X-ray band and also distorts the cosmic microwave radiation through the Sunyaev-Zel'dovich (SZ) effect. Combining these two complementary sources of information…
We develop a Maximum Likelihood estimator (MLE) to measure the masses of galaxy clusters through the impact of gravitational lensing on the temperature and polarization anisotropies of the cosmic microwave background (CMB). We show that, at…
Future multifrequency microwave background experiments with arcminute resolution and micro-Kelvin temperature sensitivity will be able to detect the kinetic Sunyaev-Zeldovich (kSZ) effect, providing a way to measure radial peculiar…
We discuss an implementation of a deep learning framework to gain insight into dark matter (DM) structure formation. We investigate the contribution of velocity and density field information to the construction of the halo mass function…
We develop a machine learning algorithm to infer the 3D cumulative radial profiles of total and gas mass in galaxy clusters from thermal Sunyaev-Zel'dovich effect maps. We generate around 73,000 mock images along various lines of sight…
The cosmological parameters prefered by the cosmic microwave background (CMB) primary anisotropies predict many more galaxy clusters than those that have been detected via the thermal Sunyaev-Zeldovich (tSZ) effect. This tension has…
The measurement of angular diameter distance to galaxy clusters, through combined Sunyaev-Zel'dovich (SZ) effect data with X-ray emission observations, is now a well-known probe of cosmology. Using a combination of SZ data and a map of the…