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 Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

We introduce the Automatic Learning for the Rapid Classification of Events(ALeRCE) broker, an astronomical alert broker designed to provide a rapid andself--consistent classification of large etendue telescope alert streams, suchas that provided by the Zwicky Transient Facility (ZTF) and, in the future, theVera C. Rubin Observatory Legacy Survey of Space and Time (LSST). ALeRCE is aChilean--led broker run by an interdisciplinary team of astronomers andengineers, working to become intermediaries between survey and follow--upfacilities. ALeRCE uses a pipeline which includes the real--time ingestion,aggregation, cross--matching, machine learning (ML) classification, andvisualization of the ZTF alert stream. We use two classifiers: a stamp--basedclassifier, designed for rapid classification, and a light--curve--basedclassifier, which uses the multi--band flux evolution to achieve a more refinedclassification. We describe in detail our pipeline, data products, tools andservices, which are made public for the community (see\url{https://alerce.science}). Since we began operating our real--time MLclassification of the ZTF alert stream in early 2019, we have grown a largecommunity of active users around the globe. We describe our results to date,including the real--time processing of $9.7\times10^7$ alerts, the stampclassification of $1.9\times10^7$ objects, the light curve classification of$8.5\times10^5$ objects, the report of 3088 supernova candidates, and differentexperiments using LSST-like alert streams. Finally, we discuss the challengesahead to go from a single-stream of alerts such as ZTF to a multi--streamecosystem dominated by LSST.

The Automatic Learning for the Rapid Classification of Events (ALeRCE) Alert Broker