相关论文: Deep learning of quasar lightcurves in the LSST er…

We introduce a deep machine learning approach to studying quasar microlensing light curves for the first time by analyzing hundreds of thousands of simulated light curves with respect to the accretion disc size and temperature profile. Our…

Astronomy light curves are sparse, gappy, and heteroscedastic. As a result standard time series methods regularly used for financial and similar datasets are of little help and astronomers are usually left to their own instruments and…

We apply machine learning techniques in an attempt to predict and classify stellar properties from noisy and sparse time series data. We preprocessed over 94 GB of Kepler light curves from MAST to classify according to ten distinct physical…

Quasars experiencing strong lensing offer unique viewpoints on subjects related to the cosmic expansion rate, the dark matter profile within the foreground deflectors, and the quasar host galaxies. Unfortunately, identifying them in…

We present variability and multi-wavelength photometric information for the 933 known quasars in the QUEST Variability Survey. These quasars are grouped into variable and non-variable populations based on measured variability confidence…

In the upcoming synoptic all--sky survey era of astronomy, thousands of new multiply imaged quasars are expected to be discovered and monitored regularly. Light curves from the images of gravitationally lensed quasars are further affected…

The consequences of complex disturbed environments in the vicinity of a supermassive black hole are not well represented by standard statistical models of optical variability in active galactic nuclei (AGN). Thus, developing new…

We apply a convolutional neural network (CNN) to classify and detect quasars in the Sloan Digital Sky Survey Stripe 82 and also to predict the photometric redshifts of quasars. The network takes the variability of objects into account by…

Time-domain astronomy is progressing rapidly with the ongoing and upcoming large-scale photometric sky surveys led by the Vera C. Rubin Observatory project (LSST). Billions of variable sources call for better automatic classification…

Stellar light curves contain valuable information about oscillations and granulation, offering insights into stars' internal structures and evolutionary states. Traditional asteroseismic techniques, primarily focused on power spectral…

Gravitationally lensed sources may have unresolved or blended multiple images, and for time varying sources the lightcurves from individual images can overlap. We use convolutional neural nets to both classify the lightcurves as due to…

The microlensing signal in the light curves of gravitationally lensed quasars can shed light on the dark matter (DM) composition in their lensing galaxies. Here, we investigate a sample of six lensed quasars from the most recent and best…

Photometric data-driven classification of supernovae becomes a challenge due to the appearance of real-time processing of big data in astronomy. Recent studies have demonstrated the superior quality of solutions based on various machine…

Strongly lensed quadruply imaged quasars (quads) are extraordinary objects. They are very rare in the sky -- only a few tens are known to date -- and yet they provide unique information about a wide range of topics, including the expansion…

In this work, we propose a novel ensemble of recurrent neural networks (RNNs) that considers the multiband and non-uniform cadence without having to compute complex features. Our proposed model consists of an ensemble of RNNs, which do not…

During the last decade, a considerable amount of effort has been made to classify variable stars using different machine learning techniques. Typically, light curves are represented as vectors of statistical descriptors or features that are…

Forthcoming imaging surveys will potentially increase the number of known galaxy-scale strong lenses by several orders of magnitude. For this to happen, images of tens of millions of galaxies will have to be inspected to identify potential…

Archives of long photometric surveys, like the Kepler database, are a gold mine for studying flares. However, identifying them is a complex task; while in the case of single-target observations it can be easily done manually by visual…

We describe the construction of a highly reliable sample of approximately 7,000 optically faint periodic variable stars with light curves obtained by the asteroid survey LINEAR across 10,000 sq.deg of northern sky. Majority of these…

We devise an optimal method to measure the temporal power spectrum of the lensing and intrinsic fluctuations of multiply-imaged strongly lensed quasar light curves, along with the associated time delays. The method is based on a Monte-Carlo…