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

The Vera C. Rubin Observatory, through its Legacy Survey of Space and Time, will soon start producing 10 million alerts on transient astronomical objects per night. Due to logistics and bandwidth, alerts will not be dispatched directly to…

We introduce a novel approach to detecting microlensing events and other transients in light curves, utilising the isolation forest (iForest) algorithm for anomaly detection. Focusing on the Legacy Survey of Space and Time by the Vera C.…

The recent advances in Gravitational-wave astronomy have greatly accelerated the study of Multimessenger astrophysics. There is a need for the development of fast and efficient algorithms to detect non-astrophysical transients and noises…

A community meeting on the topic of "Radio Astronomy in the LSST Era" was hosted by the National Radio Astronomy Observatory in Charlottesville, VA (2013 May 6--8). The focus of the workshop was on time domain radio astronomy and sky…

The Sloan Digital Sky Survey-II Supernova Survey has identified a large number of new transient sources in a 300 sq. deg. region along the celestial equator during its first two seasons of a three-season campaign. Multi-band (ugriz) light…

We used four-year baseline HST/WFC3 IR observations of the Galactic Centre in the F153M band (1.53 micron) to identify variable stars in the central ~2.3'x2.3' field. We classified 3845 long-term (periods from months to years) and 76…

In the upcoming decade large astronomical surveys will discover millions of transients raising unprecedented data challenges in the process. Only the use of the machine learning algorithms can process such large data volumes. Most of the…

Dense subgraph discovery methods are routinely used in a variety of applications including the identification of a team of skilled individuals for collaboration from a social network. However, when the network's node set is associated with…

Wide-field imaging surveys such as the Dark Energy Survey (DES) rely on coarse measurements of spectral energy distributions in a few filters to estimate the redshift distribution of source galaxies. In this regime, sample variance, shot…

The observational era of gravitational-wave astronomy began in the Fall of 2015 with the detection of GW150914. One potential type of detectable gravitational wave is short-duration gravitational-wave bursts, whose waveforms can be…

This work presents a new approach for detection and exclusion (or de-weighting) of pseudo-range measurements from the Global Navigation Satellite System (GNSS) in order to improve the accuracy of single-epoch positioning, which is an…

We present the methods and results from the discovery and photometric measurement of 26 bright (VR $>$ 24 trans-Neptunian objects (TNOs) during the first year (2019-20) of the DECam Ecliptic Exploration Project (DEEP). The DEEP survey is an…

This paper presents a new optical imaging survey of four deep drilling fields (DDFs), two Galactic and two extragalactic, with the Dark Energy Camera (DECam) on the 4 meter Blanco telescope at the Cerro Tololo Inter-American Observatory…

We describe the application of data mining algorithms to research problems in astronomy. We posit that data mining has always been fundamental to astronomical research, since data mining is the basis of evidence-based discovery, including…

We address the problem of sequentially selecting and observing processes from a given set to find the anomalies among them. The decision-maker observes a subset of the processes at any given time instant and obtains a noisy binary indicator…

We present DELIGHT, or Deep Learning Identification of Galaxy Hosts of Transients, a new algorithm designed to automatically and in real-time identify the host galaxies of extragalactic transients. The proposed algorithm receives as input…

This paper introduces a novel variability report generator developed for the Large Array Survey Telescope (LAST), a cost-effective multi-purpose telescope array conducting a wide survey of the variable sky in the visible-light spectrum.…

We propose a new hierarchy of semidefinite programming relaxations for inference problems. As test cases, we consider the problem of community detection in block models. The vertices are partitioned into $k$ communities, and a graph is…

Machine-learning (ML) algorithms will play a crucial role in studying the large datasets delivered by new facilities over the next decade and beyond. Here, we investigate the capabilities and limits of such methods in finding galaxies with…

Upcoming deep optical surveys, such as the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), will scan the sky to unprecedented depths, detecting billions of galaxies. However, this amount of detections will lead to the…