相关论文: Supernova search with active learning in ZTF DR3

Active galactic nuclei (AGNs) are known to exhibit stochastic variability across a wide range of timescales and wavelengths. AGN flares are extreme outbursts that deviate from this typical behavior and may trace a range of energetic…

We present a public catalog of transients from the Zwicky Transient Facility (ZTF) Bright Transient Survey (BTS), a magnitude-limited (m<19 mag in either the g or r filter) survey for extragalactic transients in the ZTF public stream. We…

We describe an algorithm for identifying point-source transients and moving objects on reference-subtracted optical images containing artifacts of processing and instrumentation. The algorithm makes use of the supervised machine learning…

The SuperNovae Analysis aPplication (SNAP) is a new tool for the analysis of SN observations and validation of SN models. SNAP consists of an open source relational database with (a) observational light curve, (b) theoretical light curve,…

Over the past decade wide-field optical time-domain surveys have increased the discovery rate of transients to the point that $\lesssim 10\%$ are being spectroscopically classified. Despite this, these surveys have enabled the discovery of…

Deep convolutional neural networks (CNNs) have been widely used in surface defect detection. However, no CNN architecture is suitable for all detection tasks and designing effective task-specific requires considerable effort. The neural…

Understanding and quantifying the contribution of known classes of transient and variable sources is an important lesson to be learned from the manifold of pre-cursors programs of the near-future large synoptic sky survey programs like…

This paper presents the first major data release and survey description for the ANU WiFeS SuperNovA Program (AWSNAP). AWSNAP is an ongoing supernova spectroscopy campaign utilising the Wide Field Spectrograph (WiFeS) on the Australian…

The development of synoptic sky surveys has led to a massive amount of data for which resources needed for analysis are beyond human capabilities. To process this information and to extract all possible knowledge, machine learning…

With a rapidly rising number of transients detected in astronomy, classification methods based on machine learning are increasingly being employed. Their goals are typically to obtain a definitive classification of transients, and for good…

Future time-domain surveys for transient events in the near- and mid-infrared bands will significantly extend our understanding about the physics of the early Universe. In this paper we study the implications of a deep (~27 mag), long-term…

We apply deep recurrent neural networks, which are capable of learning complex sequential information, to classify supernovae\footnote{Code available at \href{https://github.com/adammoss/supernovae}{https://github.com/adammoss/supernovae}}.…

With large-scale surveys such as the Zwicky Transient Facility (ZTF), it has become possible to obtain a well-sampled light curve spanning the full length of the survey for any discovery within the survey footprint. Similarly, any transient…

Thermally Activated Delayed Fluorescence (TADF) emitters must satisfy two competing requirements: small singlet-triplet energy gaps for thermal upconversion and sufficient spin-orbit coupling for fast reverse intersystem crossing.…

Here we present a catalog of 12,993 photometrically-classified supernova-like light curves from the Zwicky Transient Facility, along with candidate host galaxy associations. By training a random forest classifier on spectroscopically…

Anomaly detection techniques enable effective anomaly detection and diagnosis in multi-variate time series data, which are of major significance for today's industrial applications. However, establishing an anomaly detection system that can…

[abridged] In large-scale time-domain surveys, the processing of data, from procurement up to the detection of sources, is generally automated. One of the main challenges is contamination by artifacts, especially in regions of strong…

Determining the frequency and duration of changing--look (CL) active galactic nuclei (AGNs) phenomena, where the optical broad emission lines appear or disappear, is crucial to understand the evolution of the accretion flow around…

In this work, six convolutional neural networks (CNNs) have been trained based on %different feature images and arrays from the database including 15,638 superflare candidates on solar-type stars, which are collected from the three-years…

The first few hours of a supernova (SN) contain significant information about the progenitor system. The most modern wide-field surveys that scan the sky repeatedly every few days can discover all kinds of transients in those early epochs.…