Related papers: CHEX-MATE: A non-parametric deep learning techniqu…
Precise determination of galaxy cluster masses is crucial for establishing reliable mass-observable scaling relations in cluster cosmology. We employ graph neural networks (GNNs) to estimate galaxy cluster masses from radially sampled…
We report on spectroscopic imaging observations of the nearby (z=0.022) galaxy cluster 3C 129 performed with the ACIS detector on board of the Chandra X-ray observatory. Applying a deprojection analysis which fully takes into account the…
Atmospheric simulations for urban cities can be computationally intensive because of the need for high spatial resolution, such as a few meters, to accurately represent buildings and streets. Deep learning has recently gained attention…
The information content of crystalline materials becomes astronomical when collective electronic behavior and their fluctuations are taken into account. In the past decade, improvements in source brightness and detector technology at modern…
Using the PV observation of A1795, we illustrate the capability of XMM-EPIC to measure cluster temperature profiles, a key ingredient for the determination of cluster mass profiles through the equation of hydrostatic equilibrium. We develop…
We develop and present the Descriptive Parametric Model (DPM), a tool for generating profiles of gaseous halos (pressure, electron density, and metallicity) as functions of radius, halo mass, and redshift. The model assumes single-phase,…
The circum-galactic medium (CGM) can feasibly be mapped by multiwavelength surveys covering broad swaths of the sky. With multiple large datasets becoming available in the near future, we develop a likelihood-free Deep Learning technique…
In the realm of X-ray spectral analysis, the true nature of spectra has remained elusive, as observed spectra have long been the outcome of convolution between instrumental response functions and intrinsic spectra. In this study, we employ…
Modern hydrodynamical simulations offer nowadays a powerful means to trace the evolution of the X-ray properties of the intra-cluster medium (ICM) during the cosmological history of the hierarchical build up of galaxy clusters. In this…
We present a systematic analysis of the intracluster medium (ICM) in an X-ray flux limited sample of 45 galaxy clusters. Using archival ROSAT PSPC data and published ICM temperatures, we present best fit double and single beta model…
We measure the evolution of the X-ray luminosity-temperature (L_X-T) relation since z~1.5 using a sample of 211 serendipitously detected galaxy clusters with spectroscopic redshifts drawn from the XMM Cluster Survey first data release…
This paper addresses the challenges of designing mesh convolution neural networks for 3D mesh dense prediction. While deep learning has achieved remarkable success in image dense prediction tasks, directly applying or extending these…
We introduce a technique based on infrared thermal emission, termed depth thermography, that can remotely measure the temperature distribution beneath the surface of certain objects. Depth thermography utilizes the thermal-emission spectrum…
Deconvolution of large survey images with millions of galaxies requires to develop a new generation of methods which can take into account a space variant Point Spread Function (PSF) and have to be at the same time accurate and fast. We…
The redshift evolution of the galaxy cluster temperature function is a powerful probe of cosmology. However, its determination requires the measurement of redshifts for all clusters in a catalogue, which is likely to prove challenging for…
To better constrain models of cool core galaxy cluster formation, we have used X-ray observations taken from the Chandra and ROSAT archives to examine the properties of cool core and non-cool core clusters, especially beyond the cluster…
We present the results of a joint analysis of $Chandra$ X-ray and South Pole Telescope (SPT) SZ observations targeting the first sample of galaxy clusters at $0.3 < z < 1.3$, selected to be the progenitors of well-studied nearby clusters…
We consider the non-radial motions, originating in the outskirts of clusters of galaxies and we show how it may reduce the discrepancy between Cold Dark Matter (CDM) predicted X-ray temperature distribution function of clusters of galaxies…
We analysed XMM-{\it Newton} EPIC data for 53 galaxy clusters. Through 2D spectral maps, we provide the most detailed and extended view of the spatial distribution of temperature (kT), pressure (P), entropy (S) and metallicity (Z) of galaxy…
A promising approach to improve cloud parameterizations within climate models and thus climate projections is to use deep learning in combination with training data from storm-resolving model (SRM) simulations. The ICOsahedral…