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

The Large Synoptic Survey Telescope (LSST) will be a large, wide-fieldground-based system designed to obtain, starting in 2015, multiple images ofthe sky that is visible from Cerro Pachon in Northern Chile. About 90% of theobserving time will be devoted to a deep-wide-fast survey mode which willobserve a 20,000 deg$^2$ region about 1000 times during the anticipated 10years of operations (distributed over six bands, $ugrizy$). Each 30-second longvisit will deliver 5$\sigma$ depth for point sources of $r\sim24.5$ on average.The co-added map will be about 3 magnitudes deeper, and will include 10 billiongalaxies and a similar number of stars. We discuss various measurements thatwill be automatically performed for these 20 billion sources, and how they canbe used for classification and determination of source physical and otherproperties. We provide a few classification examples based on SDSS data, suchas color classification of stars, color-spatial proximity search for wide-anglebinary stars, orbital-color classification of asteroid families, and therecognition of main Galaxy components based on the distribution of stars in theposition-metallicity-kinematics space. Guided by these examples, we anticipatethat two grand classification challenges for LSST will be 1) rapid and robustclassification of sources detected in difference images, and 2) {\itsimultaneous} treatment of diverse astrometric and photometric time seriesmeasurements for an unprecedentedly large number of objects.

Parametrization and Classification of 20 Billion LSST Objects: Lessons from SDSS