相关论文: A classification algorithm for time-domain novelti…

The Vera C. Rubin Observatory recently released Data Preview 1 (DP1) in advance of the upcoming Legacy Survey of Space and Time (LSST), which will enable boundless discoveries in time-domain astronomy over the next ten years. DP1 provides…

Fast moving celestial objects are characterized by velocities across the celestial sphere that significantly differ from the motions of background stars. In observational images, these objects exhibit distinct shapes, contrasting with the…

A sample of Cataclysmic Variables (CVs) is presented including spectroscopically identified 380 spectra of 245 objects, of which 58 CV candidates are new discoveries. The BaggingTopPush and the Random Forest algorithms are applied to the…

Tidal features provide signatures of recent mergers and offer a unique insight into the assembly history of galaxies. The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) will enable an unprecedentedly large survey of…

Upcoming LSST survey gives an unprecedented opportunity for studying populations of intrinsically faint objects using microlensing technique. Large field of view and aperture allow effective time-series observations of many stars in…

We propose a novel Bayesian framework for changepoint detection in large-scale spherical spatiotemporal data, with broad applicability in environmental and climate sciences. Our approach models changepoints as spatially dependent…

The rates and properties of tidal disruption events (TDEs) provide valuable insights into their host galaxy central stellar densities and the demographics of their central supermassive black holes (SMBHs). TDEs have been observed only at…

Among the many challenges posed by the huge data volumes produced by the new generation of astronomical instruments there is also the search for rare and peculiar objects. Unsupervised outlier detection algorithms may provide a viable…

Ly$\alpha$ blobs (LABs) are large, spatially extended Ly$\alpha$-emitting objects whose nature remains unclear. Their statistical properties such as number densities and luminosity functions are still uncertain because of small sample sizes…

This paper introduces a new methodology for detecting anomalies in time series data, with a primary application to monitoring the health of (micro-) services and cloud resources. The main novelty in our approach is that instead of modeling…

Distinguishing active galaxies from star-forming galaxies is essential for understanding galaxy evolution. Diagnostic methods like the BPT (Baldwin, Phillips, and Terlevich) diagram use optical emission-line ratios to separate galaxies.…

By pursuing the goal to find new variables in the COROT field-of-view we characterised a sample of stars located in the lower part of the instability strip. Our sample is composed of stars belonging to the disk population in the solar…

Community detection is a fundamental task in graph analysis, with methods often relying on fitting models like the Stochastic Block Model (SBM) to observed networks. While many algorithms can accurately estimate SBM parameters when the…

In the context of cybersecurity, tracking the activities of coordinated hosts over time is a daunting task because both participants and their behaviours evolve at a fast pace. We address this scenario by solving a dynamic novelty discovery…

Strong gravitational lensing enables a wide range of science: probing cosmography; testing dark matter models; understanding galaxy evolution; and magnifying the faint, small and distant Universe. However to date exploiting strong lensing…

This study presents a bidirectional Long Short-Term Memory (LSTM) neural network for classifying transient astronomical object light curves from the Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC) dataset. The…

The Large Synoptic Survey Telescope (LSST) surveys have initially been optimized to omit the inner part of the Milky Way disk/bar from deep and cadence observations. However it is now clear that the LSST will be powerful for Galactic…

We present the discovery and statistical analysis of $12\;660$ spotted variable stars toward and inside the Galactic bulge from over two-decade-long Optical Gravitational Lensing Experiment (OGLE) data. We devise a new method of dereddening…

Tidal disruption events (TDEs) are multi-messenger transients in which a star is tidally destroyed by a supermassive black hole at the center of galaxies. The Rubin Observatory Legacy Survey of Space and Time (LSST) is anticipated to…

The exponential growth of astronomical datasets provides an unprecedented opportunity for humans to gain insight into the Universe. However, effectively analyzing this vast amount of data poses a significant challenge. Astronomers are…