At the end of the day I had a wide-ranging conversation with Andy Casey (Monash) about all things spectroscopic. I mentioned to him my new interest in domain adaptation, and whether it could be used to build data-driven models. The SDSS-V project has two spectrographs, at two different telescopes, each of which observes stars down different fibers (which have their own idiosyncracies). Could we build a data-driven model to see what any star observed down one fiber of one spectrograph would look like if it had been observed down any other fiber or any fiber of the other spectrograph? That would permit us to see what systematics are spectrograph-specific, and whether we would have got the same answers with the other spectrograph, and other questions like that.
There are some stars observed multiple times and by both observatories, but I'm kind-of interested in whether we could do better using the huge number of stars that haven't been observed twice instead. Indeed, it isn't clear which contains more information about the transformations. Another fun thing: The northern sky and the southern sky are different! We would have to re-build domain adaptation to be sensitive to those differences, which might get into causal-inference territory.
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