English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

With the advent of the Large Synoptic Survey Telescope (LSST), time-domainastronomy will be faced with an unprecedented volume and rate of data.Real-time processing of variables and transients detected by such large-scalesurveys is critical to identifying the more unusual events and allocatingscarce follow-up resources efficiently. We develop an algorithm to identifythese novel events within a given population of variable sources. We determinethe distributions of magnitude changes (dm) over time intervals (dt) for agiven passband f, pf(dm|dt), and use these distributions to compute thelikelihood of a test source being consistent with the population, or anoutlier. We demonstrate our algorithm by applying it to the DECam multi-bandtime-series data of more than 2000 variable stars identified by Saha et al.(2019) in the Galactic Bulge that are largely dominated by long-periodvariables and pulsating stars. Our algorithm discovers 18 outlier sources inthe sample, including a microlensing event, a dwarf nova, and twochromospherically active RS CVn stars, as well as sources in the BlueHorizontal Branch region of the color-magnitude diagram without any knowncounterparts. We compare the performance of our algorithm for novelty detectionwith multivariate KDE and Isolation Forest on the simulated PLAsTiCC dataset.We find that our algorithm yields comparable results despite its simplicity.Our method provides an efficient way for flagging the most unusual events in areal-time alert-broker system.

astrophysical journal/the astrophysical journal

A classification algorithm for time-domain novelties in preparation for  LSST alerts: Application to variable stars and transients detected with DECam  in the Galactic Bulge