Spitzer death; nearest neighbors

Today was spent at the Spitzer Science Center for the 39th meeting of the Oversight Committee, on which I have served since 2008. This meeting was just like every other: I learned a huge amount! This time about how the mission comes to a final end, with the exercise of various un-exercised mechanisms, and then the expenditure of all propellants and batteries. We discussed also the plans for the final proposal call, and the fitness of the observatory to observe way beyond its final day. On that latter note: We learned that NASA will transfer operations of Spitzer to a third party, for about a million USD per month. That's an interesting opportunity for someone. Or some consortium.

In unrelated news, Christina Eilers (MPIA) executed a very simple (but unprecedented) idea today: She asked what would happen with a data-driven model of stellar spectra (APOGEE data) if the model is simply nearest neighbor: That is, if each test-set object is given the labels of its nearest (in a chi-squared sense) training-set object. The answer is impressive: the nearest-neighbor method is only slightly worse than the quadratic data-driven model known as The Cannon. This all relates to the point that most machine-learning methods are—in some sense—nearest-neighbor methods!

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