Related papers: Hubble Tarantula Treasury Project - VI. Identifica…
The CFHTLS presents a unique data set for weak lensing studies, having high quality imaging and deep multi-band photometry. We have initiated an XMM-CFHTLS project to provide X-ray observations of the brightest X-ray selected clusters…
Despite the advances provided by large-scale photometric surveys, stellar features - such as metallicity - generally remain limited to spectroscopic observations often of bright, nearby low-extinction stars. To rectify this, we present a…
Background: Pleural Mesothelioma (PM) is an unusual, belligerent tumor that rapidly develops into cancer in the pleura of the lungs. Pleural Mesothelioma is a common type of Mesothelioma that accounts for about 75% of all Mesothelioma…
Proper motions (PMs) are crucial to fully understand the internal dynamics of globular clusters (GCs). To that end, the Hubble Space Telescope (HST) Proper Motion (HSTPROMO) collaboration has constructed large, high-quality PM catalogues…
We present the main-sequence binary (MSMS) Catalog derived from Gaia Data Release 3 BP/RP (XP) spectra. Leveraging the vast sample of low-resolution Gaia XP spectra, we develop a forward modeling approach that maps stellar mass and…
Decision Trees are prominent prediction models for interpretable Machine Learning. They have been thoroughly researched, mostly in the batch setting with a fixed labelled dataset, leading to popular algorithms such as C4.5, ID3 and CART.…
Accurate detection of pulmonary nodules with high sensitivity and specificity is essential for automatic lung cancer diagnosis from CT scans. Although many deep learning-based algorithms make great progress for improving the accuracy of…
We introduce new methods for robust high-precision photometry from well-sampled images of a non-crowded field with a strongly varying point-spread function. For this work, we used archival imaging data of the open cluster M37 taken by MMT…
We use the Panchromatic Hubble Andromeda Treasury (PHAT) survey dataset to perform spatially resolved measurements of star cluster formation efficiency ($\Gamma$), the fraction of stellar mass formed in long-lived star clusters. We use…
We develop a novel method based on machine learning principles to achieve optimal initiation of CPU-intensive computations for forward asteroseismic modeling in a multi-D parameter space. A deep neural network is trained on a precomputed…
Gravitational lensing is an important prediction of general relativity, providing both its test and a tool to detect faint but amplified sources and to measure masses of lenses. For some applications (e.g. testing the theory), a point…
One of the major goals of next-generation space-borne and ground-based telescopes is to detect and characterize the first galaxies that were in place in the first few hundred million years after the big bang. We study the spectral energy…
In order to better understand the role of high-mass stellar feedback in regulating star formation in giant molecular clouds, we carried out a Hubble Space Telescope (HST) Treasury Program "Measuring Young Stars in Space and Time" (MYSST)…
The "Advanced Spectral Library (ASTRAL)" Project (PI = T. Ayres) consists of two Treasury Programs: the Cycle 18 "Cool Stars" (GO-12278) Program and the Cycle 21 "Hot Stars" (GO-13346) Program. The primary goal of these programs is to…
We present a case study about the spatial indexing and regional classification of billions of geographic coordinates from geo-tagged social network data using Hierarchical Triangular Mesh (HTM) implemented for Microsoft SQL Server. Due to…
The HERMES-TP/SP (High Energy Rapid Modular Ensemble of Satellites -- Technologic and Scientific Pathfinder) is an in-orbit demonstration of the so-called distributed astronomy concept. Conceived as a mini-constellation of six 3U…
We measure the mass function for a sample of 840 young star clusters with ages between 10-300 Myr observed by the Panchromatic Hubble Andromeda Treasury (PHAT) survey in M31. The data show clear evidence of a high-mass truncation: only 15…
We present an automated statistical method that uses medium-resolution spectroscopic observations of a set of stars to select those that show evidence of possessing significant amounts of neutron-capture elements. Our tool was tested…
Machine learning is a powerful technique, becoming increasingly popular in astrophysics. In this paper, we apply machine learning to more than a thousand globular cluster (GC) models simulated as part of the 'MOCCA-Survey Database I'…
This paper presents a technique to search for supermassive black hole binaries (MBHBs) in the Sloan Digital Sky Survey (SDSS). The search is based on the peculiar properties of merging galaxies that are found in a mock galaxy catalog from…