Related papers: CHEX-MATE: A non-parametric deep learning techniqu…
Different models of dark matter can alter the distribution of mass in galaxy clusters in a variety of ways. However, so can uncertain astrophysical feedback mechanisms. Here we present a Machine Learning method that ''learns'' how the…
We present the MAssive ClusterS and Intercluster Structures (MACSIS) project, a suite of 390 clusters simulated with baryonic physics that yields realistic massive galaxy clusters capable of matching a wide range of observed properties.…
The thermodynamical properties of the intracluster medium (ICM) are driven by scale-free gravitational collapse, but they also reflect the rich astrophysical processes at play in galaxy clusters. At low masses ($\sim 10^{14}$ M$_{\odot}$)…
Accurate knowledge of temperatures in power semiconductor modules is crucial for proper thermal management of such devices. Precise prediction of temperatures allows to operate the system at the physical limit of the device avoiding…
X-ray diffraction is ideal for probing sub-surface state during complex or rapid thermomechanical loading of crystalline materials. However, challenges arise as the size of diffraction volumes increases due to spatial broadening and…
We examine the systematics affecting the X-ray mass estimators applied to a set of five simulated galaxy clusters. They have been processed through the X-ray Map Simulator, X-MAS, to provide Chandra-like long exposures that are analyzed to…
We present a sample of 20 massive galaxy clusters with total virial masses in the range of 6 10^14 M_sol<M(vir)< 2 10^15M_sol, re-simulated with a customized version of the 1.5. ENZO code employing Adaptive Mesh Refinement. This technique…
We demonstrate that the configurational temperature formalism can be derived from the classical hypervirial theorem, and introduce a hierarchy of hyperconfigurational temperature definitions, which are particularly well suited for…
This project intends to study a cardiovascular disease risk early warning model based on one-dimensional convolutional neural networks. First, the missing values of 13 physiological and symptom indicators such as patient age, blood glucose,…
Results from a large sample of hydrodynamical/N-body simulations of galaxy clusters in a LCDM cosmology are used to simulate cluster X-ray observations as expected from Chandra observations. The physical modeling of the gas includes…
This is the third in a series of papers studying the astrophysics and cosmology of massive, dynamically relaxed galaxy clusters. Our sample comprises 40 clusters identified as being dynamically relaxed and hot (i.e., massive) in Papers I…
We present a spectroscopic deprojection analysis of a sample of ten relaxed galaxy clusters. We use an empirical F-test derived from a set of Markov Chain Monte Carlo simulations to determine if the core plasma in each cluster could contain…
Investigating X-ray luminous galaxy clusters at z>~1 provides a fundamental constraint on evolutionary studies of the largest virialized structures in the Universe, the baryonic matter in form of the hot ICM, their galaxy populations, and…
We report results from the analysis of 21 nearby galaxy clusters, 11 with cooling flow (CF) and 10 without cooling flow, observed with BeppoSAX. The temperature profiles of both CF and non-CF systems are characterized by an isothermal core…
We present results obtained from a set of cosmological hydrodynamic simulations of galaxy clusters, aimed at comparing predictions with observational data on the diversity between cool-core (CC) and non-cool-core (NCC) clusters. Our…
The diffuse plasma inside clusters of galaxies has X-ray emitting temperatures of a few keV. The physical mechanisms that heat this intracluster medium (ICM) to such temperatures include the accretion shock at the periphery of a galaxy…
We present results of N-body/gasdynamical simulations designed to investigate the evolution of X-ray clusters in a flat, low-density, cold dark matter (CDM) cosmogony. The density profile of the dark matter component can be fitted rather…
A new, three-dimensional, shock capturing, TVD hydrodynamic code is utilized to determine the distribution of hot gas in a CDM$+\Lambda$ model universe. This open model succeeds in matching local observations of clusters in contrast to the…
In this paper, we propose multi-stage and deformable deep convolutional neural networks for object detection. This new deep learning object detection diagram has innovations in multiple aspects. In the proposed new deep architecture, a new…
Melting is a high temperature process that requires extensive sampling of configuration space, thus making melting temperature prediction computationally very expensive and challenging. Over the past few years, I have built two methods to…