Related papers: Challenges for LSST scale data sets

Radio-astronomy is about to embark on a new way of doing science. The revolution that is about to take place is not due to the enormous sensitivity of the Square Kilometre Array, which is still a decade away, but due to its pathfinders,…

The unprecedented volume and rate of transient events that will be discovered by the Large Synoptic Survey Telescope (LSST) demands that the astronomical community update its followup paradigm. Alert-brokers -- automated software system to…

Spatiotemporal data mining (STDM) discovers useful patterns from the dynamic interplay between space and time. Several available surveys capture STDM advances and report a wealth of important progress in this field. However, STDM challenges…

The sheer size of high-accuracy, multi-band photometry, spectroscopy, astrometry and seismic data that space missions like Kepler, Gaia, PLATO, TESS, JWST and ground-based facilities under development such as MOONS, WEAVE and the LSST will…

Synthetic data are becoming a critical tool for building artificially intelligent systems. Simulators provide a way of generating data systematically and at scale. These data can then be used either exclusively, or in conjunction with real…

The Large Synoptic Survey Telescope (LSST) will use an active optics system (AOS) to maintain alignment and surface figure on its three large mirrors. Corrective actions fed to the LSST AOS are determined from information derived from 4…

Although huge progress has been made on scene analysis in recent years, most existing works assume the input images to be in day-time with good lighting conditions. In this work, we aim to address the night-time scene parsing (NTSP)…

We present a data-driven technique to analyze multifrequency images from upcoming cosmological surveys mapping large sky area. Using full information from the data at the two-point level, our method can simultaneously constrain the…

Imbalanced classification and spurious correlation are common challenges in data science and machine learning. Both issues are linked to data imbalance, with certain groups of data samples significantly underrepresented, which in turn would…

The Sloan Digital Sky Survey (SDSS) will carry out a digital photometric and spectroscopic survey over pi steradians in the northern Galactic cap. An array of CCD detectors used in drift-scan mode will image the sky in five passbands to a…

LSST will open new vistas for cosmology in the next decade, but it cannot reach its full potential without data from other telescopes. Cosmological constraints can be greatly enhanced using wide-field ($>20$ deg$^2$ total survey area),…

The days of the lone astronomer with his optical telescope and photographic plates are long gone: Astronomy in 2025 will not only be multi-wavelength, but multi-messenger, and dominated by huge data sets and matching data rates. Catalogues…

Large Language Models are being used in conversational agents that simulate human conversations and generate social studies data. While concerns about the models' biases have been raised and discussed in the literature, much about the data…

Temporal data, notably time series and spatio-temporal data, are prevalent in real-world applications. They capture dynamic system measurements and are produced in vast quantities by both physical and virtual sensors. Analyzing these data…

For centuries, the rich nocturnal environment of the starry sky could be modelled only by analogue tools such as paper planispheres, atlases, globes and numerical tables. The immersive sky simulator of the twentieth century, the…

The Large Synoptic Survey Telescope (LSST) Dark Energy Science Collaboration (DESC) will use five cosmological probes: galaxy clusters, large scale structure, supernovae, strong lensing, and weak lensing. This Science Requirements Document…

The contemporary astronomical instruments have been producing the unprecedented amount of data. The largest part of this "data avalanche" is being produced by deep all-sky surveys yielding terabytes of raw data per night. Such a great data…

Much of the science case for the next generation of deep, wide-field optical/infrared surveys has been driven by the further study of dark energy. This is a laudable goal (and the subject of a companion white paper by Zhan et al.). However,…

This paper studies the large-scale subspace clustering (LSSC) problem with million data points. Many popular subspace clustering methods cannot directly handle the LSSC problem although they have been considered as state-of-the-art methods…

Astrophysical light curves are particularly challenging data objects due to the intensity and variety of noise contaminating them. Yet, despite the astronomical volumes of light curves available, the majority of algorithms used to process…