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Sherlock: what it does, how it works (Dave Young)
Cross-match against NED-D is throttled and cached to avoid Sherlock being black-listed by NED-D.
Aim to reduce cross-match to integer-based search fields to speed up queries.
Roy noted that, by end of first year, depth of LSST survey will make most other surveys less relevant. How does this impact role of Sherlock?
Dave Y noted that, for SNe, NED was critical for classification. LSST would help to eliminate ‘background fog'. For QUB, this will be a critical use case.
Roy W noted that Lasair will likely serve other applications, as well as SNe.
Stephen S noted that LSST catalogue (inc. photometric redshift) will be huge help for objects with redshift less than mag. 22, though will not help astronomers to identify those objects for which spectroscopy is interesting.
Gareth F noted conflict of tuning for particular applications vs. different use cases. Would it worthwhile to produce confidence information for classification results?
Dave Y noted that Sherlock produces a list of all sources that the transient has probably been associated list. The top-level result, from Sherlock, is the ‘tip of the iceberg’. Also, agrees that providing one-off confidence value would be useful.
Visualisation of Sherlock classification would make it more immediate for users to identify source that has been crossmatched and algorithm that has been most successful.