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Stars exhibit a bewildering variety of variable behaviors ranging fromexplosive magnetic flares to stochastically changing accretion to periodicpulsations or rotations. The principal LSST surveys will have cadences toosparse and irregular to capture most of these phenomena. A novel idea isproposed here to observe a single Galactic field, rich in unobscured stars, ina continuous sequence of $\sim 15$ second exposures for one long winter nightin a single photometric band. The result will be a unique dataset of $\sim 1$million regularly spaced stellar lightcurves. The lightcurves will gives aparticularly comprehensive collection of dM star variability. A powerful arrayof statistical procedures can be applied to the ensemble of lightcurves fromthe long-standing fields of time series analysis, signal processing andeconometrics. Dozens of `features' describing the variability can be extractedand subject to machine learning classification, giving a unique authoritativeobjective classification of rapidly variable stars. The most effective featurescan then inform the wider LSST community on the best approaches to variablestar identification and classification from the sparse, irregular cadences thatdominate the LSST project.

Characterizing Variable Stars in a Single Night with LSST