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Gaia data and stellar surveys open the way to the construction of detailed 3D maps of the Galactic interstellar (IS) dust based on the synthesis of star distances and extinctions. Reliable extinction measurements require very accurate…

Astrophysics of Galaxies · Physics 2018-09-05 R. Lallement , L. Capitanio , L. Ruiz-Dern , C. Danielski , C. Babusiaux , J. L. Vergely , M. Elyajouri , F. Arenou , N. Leclerc

Parametrized measures (or Young measures) enable to reformulate non-convex variational problems as convex problems at the cost of enlarging the search space from space of functions to space of measures. To benefit from such machinery, we…

Numerical Analysis · Mathematics 2025-11-04 Rayehe Karimi Mahabadi , Jianfeng Lu , Hossein Salahshoor

Context: this paper describes the detection of wide binary and multiple central stars (CSs) of Galactic planetary nebulae (PNe) using the most up-to-date data available from the Gaia Data Release 3 (Gaia DR3). Aims: the objective of this…

Solar and Stellar Astrophysics · Physics 2023-05-10 A. Ali , J. M. Khalil , A. Mindil

We have derived accurate distances to Galactic globular clusters by combining data from the Gaia Early Data Release 3 with distances based on Hubble Space telescope HST data and literature based distances. We determine distances either…

Astrophysics of Galaxies · Physics 2021-07-14 Holger Baumgardt , Eugene Vasiliev

We explore how information in images of nearby galaxies can be used to estimate their distance. We train a convolutional Neural Network (NN) to do this, using galaxy images from the Illustris simulation. We show that if the NN is trained on…

Cosmology and Nongalactic Astrophysics · Physics 2022-04-21 Kevin M. Quigley , Samuel Hori , Rupert A. C. Croft

A serious limitation in the study of many globular clusters -- especially those located near the Galactic Center -- has been the existence of large and differential extinction by foreground dust. In a series of papers we intend to map the…

Astrophysics of Galaxies · Physics 2015-05-27 Javier Alonso-García , Mario Mateo , Bodhisattva Sen , Moulinath Banerjee , Kaspar von Braun

Observations of high-redshift Type Ia supernovae (SNe~Ia) are used to study the cosmic transparency at optical wavelengths. Assuming a flat $\Lambda$CDM cosmological model based on BAO and CMB results, redshift dependent deviations of SN~Ia…

Cosmology and Nongalactic Astrophysics · Physics 2018-05-16 Ariel Goobar , Suhail Dhawan , Daniel Scolnic

One field containing WISE J154151.65-225024.9 was observed by Hubble Space Telescope at three different epochs taken in ~5 yrs. We measured positions of sources in all images and successfully linked these positions to the Gaia DR2 absolute…

Solar and Stellar Astrophysics · Physics 2018-10-17 L. R. Bedin , C. Fontanive

Despite years of high accuracy observations, none of the available theoretical techniques has yet allowed the confirmation of a moon beyond the solar system. Methods are currently limited to masses about an order of magnitude higher than…

Earth and Planetary Astrophysics · Physics 2014-05-02 René Heller

Three-dimensional (3D) maps of Galactic interstellar dust are a tool for a wide range of uses. We aim to construct 3D maps of dust extinction in the Local Arm and surrounding regions. Gaia EDR3 photometric data were combined with 2MASS…

Astrophysics of Galaxies · Physics 2022-05-25 R. Lallement , J. -L. Vergely , C. Babusiaux , N. L. J. Cox

In `A Bayesian Approach to Locating the Red Giant Branch Tip Magnitude (PART I),' a new technique was introduced for obtaining distances using the TRGB standard candle. Here we describe a useful complement to the technique with the…

We present a table of 215 SNRs with distances. New distances are found to SNR G$51.26+0.11$ of $6.6 \pm 1.7$ kpc using HI absorption spectra, and to 5 other SNRs using maser/molecular cloud associations. We recalculate the distances and…

High Energy Astrophysical Phenomena · Physics 2022-11-30 S. Ranasinghe , D. Leahy

We demonstrate an algorithm for learning a flexible color-magnitude diagram from noisy parallax and photometry measurements using a normalizing flow, a deep neural network capable of learning an arbitrary multi-dimensional probability…

Instrumentation and Methods for Astrophysics · Physics 2019-08-23 Miles D. Cranmer , Richard Galvez , Lauren Anderson , David N. Spergel , Shirley Ho

A novel fusion python application of data mining techniques (DMT) was designed and implemented to locate, identify, and delineate the subsurface structural pattern (SSP) of source rocks for the features of interest underlain the study area.…

Signal Processing · Electrical Eng. & Systems 2020-06-15 John Stephen Kayode , Yusri Yusup

Galactic planetary nebula (PN) distances are derived, except in a small number of cases, through the calibration of statistical properties of PNe. Such calibrations are limited by the accuracy of individual PN distances which are obtained…

Astrophysics · Physics 2009-11-13 Letizia Stanghellini , Richard A. Shaw , Eva Villaver

We present an empirical method which measures the distance to a Type Ia supernova (SN Ia) with a precision of ~ 10% from a single night's data. This method measures the supernova's age and luminosity/light-curve parameter from a spectrum,…

We report on the discovery of Cepheids in the field spiral galaxy NGC 3621, based on observations made with the Wide Field and Planetary Camera 2 on board the Hubble Space Telescope (HST). NGC 3621 is one of 18 galaxies observed as a part…

Determining reliable distances to classical novae is a challenging but crucial step in deriving their ejected masses and explosion energetics. Here we combine radio expansion measurements from the Karl G. Jansky Very Large Array with…

High Energy Astrophysical Phenomena · Physics 2015-06-03 J. D. Linford , V. A. R. M. Ribeiro , L. Chomiuk , T. Nelson , J. L. Sokoloski , M. P. Rupen , K. Mukai , T. J. O'Brien , A. J. Mioduszewski , J. Weston

Distance metric learning (DML) has been studied extensively in the past decades for its superior performance with distance-based algorithms. Most of the existing methods propose to learn a distance metric with pairwise or triplet…

Machine Learning · Computer Science 2019-05-23 Qi Qian , Jiasheng Tang , Hao Li , Shenghuo Zhu , Rong Jin