Related papers: Infrastructure and Strategies for Time Domain and …
Exploration of time domain is now a vibrant area of research in astronomy, driven by the advent of digital synoptic sky surveys. While panoramic surveys can detect variable or transient events, typically some follow-up observations are…
We describe the development of a system for an automated, iterative, real-time classification of transient events discovered in synoptic sky surveys. The system under development incorporates a number of Machine Learning techniques, mostly…
Time-domain Astrophysics (TDA), a foundation of Astronomy, has become a major part of current and projected (2020s) astrophysics. While much has been derived from temporal measures of flux and color, the real physics comes from…
High-quality, usable, and effective software is essential for supporting astronomers in the discovery-focused tasks of data analysis and visualisation. As the volume, and perhaps more crucially, the velocity of astronomical data grows, the…
Astronomy is experiencing a rapid growth in data size and complexity. This change fosters the development of data-driven science as a useful companion to the common model-driven data analysis paradigm, where astronomers develop automatic…
Astronomy, as many other scientific disciplines, is facing a true data deluge which is bound to change both the praxis and the methodology of every day research work. The emerging field of astroinformatics, while on the one end appears…
Long-baseline interferometry at optical and near-infrared wavelengths is an emerging technology which is quickly becoming a useful tool to investigate stellar atmospheres and to compare observations with models. Stellar atmosphere models…
The NASA Exoplanet Archive and the Exoplanet Follow-up Observing Program service are two widely used resources for the exoplanet community. The NASA Exoplanet Archive provides a complete and accurate accounting of exoplanetary systems…
The next decade will feature a growing number of massive ground-based photometric, spectroscopic, and time-domain surveys, including those produced by DECam, DESI, and LSST. The NOAO Data Lab was launched in 2017 to enable efficient…
Since the next-generation satellite network consisting of various service function domains, such as communication, observation, navigation, etc., is moving towards large-scale, using single-domain resources is difficult to provide satisfied…
We report the outcomes of a survey that explores the current practices, needs and expectations of the astrophysics community, concerning four research aspects: open science practices, data access and management, data visualization, and data…
Broad efforts are underway to capture metadata about research software and retain it across services; notable in this regard is the CodeMeta project. What metadata are important to have about (research) software? What metadata are useful…
It remains challenging to automatically predict the multi-agent trajectory due to multiple interactions including agent to agent interaction and scene to agent interaction. Although recent methods have achieved promising performance, most…
The work of astronomers is getting more complex and advanced as the progress of computer development occurs. With improved computing capabilities and increased data flow, more sophisticated software is required in order to interpret, and…
The mining of Virtual Observatories (VOs) is becoming a powerful new method for discovery in astronomy. Here we report on the development of SkyDOT (Sky Database for Objects in the Time domain), a new Virtual Observatory, which is dedicated…
Mainstream visual object tracking frameworks predominantly rely on template matching paradigms. Their performance heavily depends on the quality of template features, which becomes increasingly challenging to maintain in complex scenarios…
Machine Learning methods will play a fundamental role in our ability to optimize the science output from the next generation of large scale surveys. Given the peculiarities of astronomical data, it is crucial that algorithms are adapted to…
We present a summary of the major contributions to the Special Session on Data Management held at the IAU General Assembly in Prague in 2006. While recent years have seen enormous improvements in access to astronomical data, and the Virtual…
In recent years, machine learning (ML) methods have remarkably improved how cosmologists can interpret data. The next decade will bring new opportunities for data-driven cosmological discovery, but will also present new challenges for…
Heliophysics theory and modeling build understanding from fundamental principles to motivate, interpret, and predict observations. Together with observational analysis, they constitute a comprehensive scientific program in heliophysics. As…