Everything we'd like to do with LSST data, but we don't know (yet) how

TL;DR

The paper discusses the capabilities of LSST, its potential for groundbreaking astronomical discoveries, and the statistical challenges involved in analyzing its vast dataset to maximize scientific outcomes.

Contribution

It highlights the scientific potential of LSST and emphasizes the astro-statistical challenges that must be addressed to fully utilize its data.

Findings

LSST will generate an unprecedented volume of astronomical data.

Rapid reporting of transient events will enable timely follow-up observations.

Addressing astro-statistical challenges is crucial for extracting maximum science from LSST.

Abstract

The Large Synoptic Survey Telescope (LSST), the next-generation optical imaging survey sited at Cerro Pachon in Chile, will provide an unprecedented database of astronomical measurements. The LSST design, with an 8.4m (6.7m effective) primary mirror, a 9.6 sq. deg. field of view, and a 3.2 Gigapixel camera, will allow about 10,000 sq. deg. of sky to be covered twice per night, every three to four nights on average, with typical 5-sigma depth for point sources of $r$=24.5 (AB). With over 800 observations in $ugrizy$ bands over a 10-year period, these data will enable a deep stack reaching $r$=27.5 (about 5 magnitudes deeper than SDSS) and faint time-domain astronomy. The measured properties of newly discovered and known astrometric and photometric transients will be publicly reported within 60 sec after observation. The vast database of about 30 trillion observations of 40 billion objects will be mined for the unexpected and used for precision experiments in astrophysics. In addition to a brief introduction to LSST, we discuss a number of astro-statistical challenges that need to be overcome to extract maximum information and science results from LSST dataset.