相关论文: Predicting the Age of Astronomical Transients from…
Astronomical transients are stellar objects that become temporarily brighter on various timescales and have led to some of the most significant discoveries in cosmology and astronomy. Some of these transients are the explosive deaths of…
I provide an incomplete inventory of the astronomical variability that will be found by next-generation time-domain astronomical surveys. These phenomena span the distance range from near-Earth satellites to the farthest Gamma Ray Bursts.…
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…
Temporal sampling does more than add another axis to the vector of observables. Instead, under the recognition that how objects change (and move) in time speaks directly to the physics underlying astronomical phenomena, next-generation…
The ongoing optical time-domain astronomy surveys are routinely reporting fifty transient candidates per night. Here, I investigate the demographics of astronomical transients and supernova classifications reported to the Transient Name…
In the last years, the need for automated real-time detection and classification of astronomical transients began to be more impelling. Better technologies involve a higher number of detected candidates and an automated classification will…
To search for optical counterparts to gravitational waves, it is crucial to develop an efficient follow-up method that allows for both a quick telescopic scan of the event localization region and search through the resulting image data for…
New time-domain surveys, such as the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), will observe millions of transient alerts each night, making standard approaches of visually identifying new and interesting transients…
There is an increasing number of large, digital, synoptic sky surveys, in which repeated observations are obtained over large areas of the sky in multiple epochs. Likewise, there is a growth in the number of (often automated or robotic)…
Large modern surveys require efficient review of data in order to find transient sources such as supernovae, and to distinguish such sources from artefacts and noise. Much effort has been put into the development of automatic algorithms,…
Exploration of the transient Universe is an exciting and fast-emerging area within radio astronomy. Known transient phenomena range in time scales from sub-nanoseconds to years or longer, thus spanning a huge range in time domain and…
The next generation of observatories will facilitate the discovery of new types of astrophysical transients. The detection of such phenomena, whose characteristics are presently poorly constrained, will hinge on the ability to perform blind…
Transient phenomena are interesting and potentially highly revealing of details about the processes under observation and study that could otherwise go unnoticed. It is therefore important to maximize the sensitivity of the method used to…
We are at the dawn of a new golden age for radio astronomy, with a new generation of facilities under construction and the global community focussed on the Square Kilometre Array as its goal for the next decade. These new facilities offer…
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…
Future surveys such as the Legacy Survey of Space and Time (LSST) of the Vera C. Rubin Observatory will observe an order of magnitude more astrophysical transient events than any previous survey before. With this deluge of photometric data,…
Astrophysical transients have been observed for millennia and have shaped our most basic assumptions about the Universe. In the last century, systematic searches have grown from detecting handfuls of transients per year to over 7000 in 2018…
Supervised classification of temporal sequences of astronomical images into meaningful transient astrophysical phenomena has been considered a hard problem because it requires the intervention of human experts. The classifier uses the…
The primary challenge in the study of explosive astrophysical transients is their detection and characterisation using multiple messengers. For this purpose, we have developed a new data-driven discovery framework, based on deep learning.…
Astronomy has entered the multi-messenger data era and Machine Learning has found widespread use in a large variety of applications. The exploitation of synoptic (multi-band and multi-epoch) surveys, like LSST (Legacy Survey of Space and…