2020-01-09

non-parametric and hierarchical

On the flight home from #AAS235, I did some writing in a paper by Lily Zhao (Yale) about spectrograph (wavelength) calibration. I'm very excited about this project; we removed all dependence on polynomials and other kinds of strict functional forms. We went non-parametric. But of course this greatly increases the degrees of freedom of the fitting or interpolation of the calibration data. So when we do this, we also have to go hierarchical; we have to restrict the calibration freedom using the data. That is, we don't have any strict functional form for the calibration of the spectrograph, but we require that the calibration solution we find lives in the space of solutions that we have seen before. That is, if you increase the freedom by going non-parametric, you need to restrict the freedom by going non-parametric. (The results look incredible.)

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