Finding and Classifying Variables and Transients in the LSST Data Stream

Mathematics – Logic

Scientific paper

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Scientific paper

LSST's all-sky coverage, consistent long-term monitoring, and flexible criteria for event identification will revolutionize studies of a wide variety of astrophysical phenomena. LSST will open new a window onto objects both familiar and exotic, from known types of variables in the local universe, to rare and faint transients at cosmological distances. Increased sample sizes of known-but-rare observational phenomena will quantify their distributions for the first time, thus challenging existing theory. LSST will also sample regions of parameter space where transient events are expected on theoretical grounds, but have not yet been observed. These scientific opportunities necessarily come with new challenges: in the vast LSST data stream, how does one identify events of interest, and marshal precious observational resources to study these events in detail? In this talk, I discuss both the opportunities LSST will provide, as well as the challenges we face and opportunities for community involvement.

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