Related papers: DRAGONS -- A Quick Overview
Classification is valuable and necessary in spectral analysis, especially for data-driven mining. Along with the rapid development of spectral surveys, a variety of classification techniques have been successfully applied to astronomical…
The next generation of wide-field deep astronomical surveys will deliver unprecedented amounts of images through the 2020s and beyond. As both the sensitivity and depth of observations increase, more blended sources will be detected. This…
The convergence between astronomy and data sonification represents a significant advancement in the approach and analysis of cosmic information. By surpassing the visual exclusivity in data analysis in astronomy, innovative projects have…
During the commissioning of the Gemini MCAO System (GeMS), we had the opportunity to obtain data with the Gemini Multi-Object Spectrograph (GMOS), the most utilised instrument at Gemini South Observatory, in March and May 2012. Several…
With the development of network and the World Wide Web (WWW), the Internet has been growing and changing dramatically. More and more on-line database systems and different kinds of services are available for astronomy research. How to help…
The Gaia mission started its regular observing program in the summer of 2014, and since then it is regularly obtaining observations of asteroids. This paper draws the outline of the data processing for Solar System objects, and in…
The implementation of fractional differential calculations can give new possibilities for image processing tools, in particular for those that are devoted to astronomical images analysis. As discussed in arxiv:0910.2381, the fractional…
We present the description of the project \texttt{SCORPIO}, a Python package for retrieving images and associated data of galaxy pairs based on their position, facilitating visual analysis and data collation of multiple archetypal systems.…
Modern astronomy relies on massive databases collected by robotic telescopes and digital sky surveys, acquiring data in a much faster pace than what manual analysis can support. Among other data, these sky surveys collect information about…
We present the first public data release of the GOGREEN and GCLASS surveys of galaxies in dense environments, spanning a redshift range $0.8<z<1.5$. The surveys consist of deep, multiwavelength photometry and extensive Gemini GMOS…
Diffractive optical neural networks (DONNs) have been emerging as a high-throughput and energy-efficient hardware platform to perform all-optical machine learning (ML) in machine vision systems. However, the current demonstrated…
This paper documents the sixteenth data release (DR16) from the Sloan Digital Sky Surveys; the fourth and penultimate from the fourth phase (SDSS-IV). This is the first release of data from the southern hemisphere survey of the Apache Point…
In time-domain astronomy, we need to use the relational database to manage star catalog data. With the development of sky survey technology, the size of star catalog data is larger, and the speed of data generation is faster. So, in this…
Over the past decade, astronomers have been using an increasingly larger number of web-based applications and archives to conduct their research. However, despite the early success in creating links across projects and data centers, the…
An efficient characterization of scientifically significant locations is essential prior to the return of humans to the Moon. The highest resolution imagery acquired from orbit of south-polar shadowed regions and other relevant locations…
The Gemini Planet Imager is a newly commissioned facility instrument designed to measure the near-infrared spectra of young extrasolar planets in the solar neighborhood and obtain imaging polarimetry of circumstellar disks. GPI's science…
Here, I present the community with exoTEDRF (EXOplanet Transit and Eclipse Data Reduction Framework; formerly known as supreme-SPOON), an end-to-end pipeline for data reduction and light curve analysis of time series observations (TSOs) of…
Deep astronomical images are often constructed by digitially stacking many individual sub-exposures. Each sub-exposure is expected to show small differences in the positions of stars and other objects in the field, due to the movement of…
Operational Neural Networks (ONNs) have recently been proposed as a special class of artificial neural networks for grid structured data. They enable heterogenous non-linear operations to generalize the widely adopted convolution-based…
Recent and forthcoming advances in instrumentation, and giant new surveys, are creating astronomical data sets that are not amenable to the methods of analysis familiar to astronomers. Traditional methods are often inadequate not merely…