相关论文: A speedy pixon image reconstruction algorithm
The Zeldovich approximation, 1st order Lagrangian perturbation theory, provides a good description of the clustering of matter and galaxies on large scales. The acoustic feature in the large-scale correlation function of galaxies imprinted…
The masses of galaxy clusters are a key tool to constrain cosmology through the physics of large-scale structure formation and accretion. Mass estimates based on X-ray and Sunyaev--Zel'dovich measurements have been found to be affected by…
We develop a machine learning algorithm that generates high-resolution thermal Sunyaev-Zeldovich (SZ) maps of novel galaxy clusters given only halo mass and mass accretion rate. The algorithm uses a conditional variational autoencoder…
We present a self consistent method to perfom a joint analysis of Sunyaev-Zel'dovich and weak gravitational lensing observation of galaxy clusters. The spatial distribution of the cluster main constituents is described by a perturbative…
We present a novel approach for reconstructing the projected mass distribution of clusters of galaxies from sparse and noisy weak gravitational lensing shear data. The reconstructions are regularised using knowledge gained from numerical…
We study the ability of three-frequency, arcminute-resolution microwave measurements to detect galaxy clusters via their Sunyaev-Zel'dovich (SZ) distortion of the microwave background. For this purpose, we have constructed large-area…
Using high-resolution microwave sky maps made by the Atacama Cosmology Telescope, we for the first time present strong evidence for motions of galaxy clusters and groups via microwave background temperature distortions due to the kinematic…
We develop a method for reconstructing the two-dimensional, projected gravitational potential of galaxy clusters from observed line-of-sight velocity dispersions of cluster galaxies. It is the third of an intended series of papers aiming at…
We present a method to estimate the lensing potential from massive galaxy clusters for given observational X-ray data. The concepts developed and applied in this work can easily be combined with other techniques to infer the lensing…
We present a novel approach to reconstruct gas and dark matter projected density maps of galaxy clusters using score-based generative modeling. Our diffusion model takes in mock SZ and X-ray images as conditional inputs, and generates…
The detection of compact sources embedded in a background is a very common problem in many fields of Astronomy. In these lecture notes we present a review of different techniques developed for the detection and extraction of compact…
Galaxy clusters provide a multitude of observational data across wavelengths and their structure and morphology are of considerable interest in cosmology as well as astrophysics. We develop a framework that allows the combination of lensing…
We present a new statistical method for constructing background subtracted measurements from event list data gathered by X-ray and gamma ray observatories. This method was initially developed specifically to construct images that account…
A unified method for three-dimensional reconstruction of objects from transmission images collected at multiple illumination directions is described. The method may be applicable to experimental conditions relevant to absorption-based,…
We propose and test a new method based on Richardson-Lucy deconvolution to reconstruct three-dimensional gas density and temperature distributions in galaxy clusters from combined X-ray and thermal Sunyaev-Zel'dovich observations. Clusters…
We examine the ability of the Sunyaev-Zel'dovich effect (SZE) statistics proposed by Lee (2002) using numerical simulations. The statistics describe the distribution of the peak heights in the noise-contaminated SZE sky maps, and provide an…
We present a fast algorithm to produce light curves of distant stars undergoing microlensing near critical curves. The need of these type of algorithms is motivated by recent observations of microlensing events of distant stars at high…
We present a new application of deep learning to reconstruct the cosmic microwave background (CMB) temperature maps from the images of microwave sky, and to use these reconstructed maps to estimate the masses of galaxy clusters. We use a…
Lemaitre-Tolman-Bondi inhomogeneous spacetimes can be used as a cosmological model to account for the type Ia supernova data. However, such models also give rise to large velocities of galaxy clusters with respect to the cosmic microwave…
Galaxy clusters are considered as excellent probes for cosmology. For that purpose, their mass needs to be measured and their structural properties needs to be understood. We propose a method for galaxy cluster mass reconstruction which…