Related papers: CHEX-MATE: A non-parametric deep learning techniqu…
New X-ray observations with XMM-Newton show a lack of spectral evidence for large amounts of cooling and condensing gas in the centers of galaxy clusters believed to harbour strong cooling flows. The paper reexplores the cooling flow…
We present and compare three approaches for accurately retrieving depth-resolved temperature distributions within materials from their thermal-radiation spectra, based on: (1) a nonlinear equation solver implemented in commercial software,…
The density profile of a cool core of intracluster gas is investigated for a cluster of galaxies that is initially in the virial equilibrium state, and then undergoes radiative cooling. The initial gas profile is derived under the…
We present an XMM-Newton observation of A1413, a hot (kT = 6.5 keV) galaxy cluster at z=0.143. We construct gas and temperature profiles up to ~1700 kpc, equivalent to ~0.7 r_200. The gas distribution is well described by a beta model in…
At high redshift, due to both observational limitations and the variety of galaxy morphologies in the early universe, measuring galaxy structure can be challenging. Non-parametric measurements such as the CAS system have thus become an…
Extracting cosmological information from microwave sky observations requires accurate estimation of the underlying Cosmic Microwave Background (CMB) by removing foreground contamination, instrumental noise, and the effects of beam…
X-ray observations of galaxy clusters are routinely used to derive radial distributions of ICM thermdynamical properties such as density and temperature. However, observations allow us to access quantities projected on the celestial sphere…
In industrial inspection and component alignment tasks, template matching requires efficient estimation of a target's position and geometric state (rotation and scaling) under complex backgrounds to support precise downstream operations.…
Deep learning can accurately represent sub-grid-scale convective processes in climate models, learning from high resolution simulations. However, deep learning methods usually lack interpretability due to large internal dimensionality,…
This paper presents deep unfolding neural networks to handle inverse problems in photothermal radiometry enabling super resolution (SR) imaging. Photothermal imaging is a well-known technique in active thermography for nondestructive…
Accurate thermal analysis of composites and porous media requires detailed characterization of local thermal properties in small scale. For some important applications such as lithium-ion batteries, changes in the properties during the…
The XMM-Newton Distant Cluster Project (XDCP) aims at the identification of a well defined sample of X-ray selected clusters of galaxies at redshifts z>0.8. We present a catalogue of the extended sources in one the deepest ~250 ksec…
Clusters of galaxies are mainly formed by merging of smaller structures, according to the standard cosmological scenario. If the mass of a substructure is >10% of that of a galaxy cluster, the temperature distribution of the intracluster…
The use of galaxy clusters to constrain cosmology is limited in part due to uncertainties in derived cluster masses, which often depend on the gas temperature. Unfortunately, there exists a longstanding discrepancy in temperature…
(Abridged) X-ray clusters are conventionally divided into two classes: "cool core" (CC) clusters and "non-cool core" (NCC) clusters. Yet relatively little attention has been given to the origins of this dichotomy and, in particular, to the…
Temperature field reconstruction is essential for analyzing satellite heat reliability. As a representative machine learning model, the deep convolutional neural network (DCNN) is a powerful tool for reconstructing the satellite temperature…
Current cloud computing frameworks host millions of physical servers that utilize cloud computing resources in the form of different virtual machines (VM). Cloud Data Center (CDC) infrastructures require significant amounts of energy to…
The relativistic Sunyaev-Zel'dovich (SZ) effect offers a method, independent of X-ray, for measuring the temperature of the intracluster medium (ICM) in the hottest systems. Here, using N-body/hydrodynamic simulations of three galaxy…
Geometric feature learning for 3D surfaces is critical for many applications in computer graphics and 3D vision. However, deep learning currently lags in hierarchical modeling of 3D surfaces due to the lack of required operations and/or…
(Abridged) We present the results of an X-ray analysis of 80 galaxy clusters selected in the 2500 deg^2 South Pole Telescope survey and observed with the Chandra X-ray Observatory. We divide the full sample into subsamples of ~20 clusters…