An Evenly-Spaced LSST Cadence for Rapidly Variable Stars

TL;DR

This paper proposes a continuous 30-second cadence LSST micro-survey of a Galactic field to produce a comprehensive, regularly spaced dataset of stellar light curves, enabling detailed analysis of rapidly variable stars and transient phenomena.

Contribution

It introduces a novel LSST micro-survey strategy with uniform cadence to capture diverse rapid stellar variability, facilitating advanced analysis and classification methods.

Findings

Creates a dataset of ~1 million regularly spaced stellar light curves.

Enables detailed statistical and machine learning analysis of rapid variability.

Provides a foundation for improved variable star classification methods.

Abstract

Stars exhibit a bewildering variety of rapidly variable behaviors ranging from explosive magnetic flares to stochastically changing accretion to periodic pulsations or rotation. The principal Rubin Observatory Legacy Survey of Space and Time (LSST) surveys will have cadences too sparse and irregular to capture many of these phenomena. We propose here a LSST micro-survey to observe a single Galactic field, rich in unobscured stars, in a continuous sequence of 30 second exposures for one long winter night in a single photometric band. The result will be a unique dataset of $\sim 1$ million regularly spaced stellar light curves (LCs). The LCs will constitute a comprehensive collection of late-type stellar flaring, but also other classes like short-period binary systems and cataclysmic variables, young stellar objects and ultra-short period exoplanets. An unknown variety of anomalous Solar System, Galactic and extragalactic variables and transients may also be present. A powerful array of statistical procedures can be applied to individual LCs from the long-standing fields of time series analysis, signal processing and econometrics. Dozens of `features' describing the variability can be extracted and the ensemble of light curves can be subject to advanced machine learning clustering procedures. This will give a unique, authoritative, objective taxonomy of the rapidly variable sky derived from identically cadenced LCs. This micro-survey is best performed early in the Rubin Observatory program, and the results can inform the wider community on the best approaches to variable star identification and classification from the sparse, irregular cadences that dominate the planned surveys.