Weisz and I pair-coded, with some help from Fouesneau and Foreman-Mackey, an extension to Weisz's spectral fitting program that will simultaneously fit spectroscopic and photometric data on stellar clusters. The idea is that a spectrum contains far more information about the stellar population than a few photometric points, but a typically taken, calibrated, and reduced spectrum has serious systematics in the spectrophotometric calibration. How to use these data responsibly?
Our generative model (or maybe causal model?) is that the spectroscopic data are good, but multiplied by an unknown smooth function of wavelength representing spectrophotometric wrongness. We put in a flexible (cubic spline) model for this function, and fit (with emcee) the cluster spectrum and the spline function (which enters multiplicatively). We got something working and now Weisz is running it overnight. In the end, if this model has the right flexibility, the overall spectral shape information will come from the photometry, while the line information will come from the spectroscopy.
The SOP in this business is to fit and divide out a continuum, from the spectrum and the spectrum models. That's a good idea, but it isn't the Right Thing To Do (tm) if you think your models might have certain kinds of problems. It also performs badly when no part of your spectrum is clearly continuum and you might have small resolution differences between model and data.
"Our generative model (or maybe causal model?) is that the spectroscopic data are good, but multiplied by an unknown smooth function of wavelength representing spectrophotometric wrongness. We put in a flexible (cubic spline) model for this function, and fit (with emcee) the cluster spectrum and the spline function (which enters multiplicatively)."
ReplyDeleteOh cool. Pancoast (UCSB) and I should think about something like this for the next version of our RM fitting code. I have tried something similar but it didn't work that well.
The supernova folks have been doing things like this for a while, to build spectrophotometric templates for SN Ia cosmology. There are those who argue that you need real spectrophotometry to do this properly, but you can probably get 90% of the way there with a technique like this, and that may be good enough for what you're doing. In the end it depends on how sensitive your conclusions are to this "warping" function and how accurately you can predict the warp for a given exposure.
ReplyDeleteI am a bit surprised that the errors in the specphot calibration are an issue. There are other bigger problems too, in the interpretation of the photometry as defining any sort of SED. Are you allowing the effective wavelengths of the photometric bandpasses to be a function of color? How do you convert a magnitude into a flux? This too is a function of the SED. As stated by Richard, we have been puzzling over this for 2 decades in supernova work. The photometric systems are defined using stellar SEDs but the observed objects do not have stellar SEDs. I am not at all convinced that the photometry gives you a better idea of the SED than does the specphot (with its systematic errors).
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