If you go to the blue side of Lyman alpha, at reasonable redshifts (say 2), the continuum is not clearly visible, since the forest is dense and has a range of equivalent widths. Any study of IGM physics or radiation or clustering or ionization depends on an accurate continuum determination. What to do? Obviously, you should fit your continuum simultaneously with whatever else you are measuring, and marginalize out the posterior uncertainties on the continuum. Duh!
That said, few have attempted this. Today I had a long conversation with Hennawi, Eilers, Rorai, and KG Lee (all MPIA) about this; they are trying to constrain IGM physics with the transmission pdf, marginalizing out the continuum. We discussed the problem of sampling each quasar's continuum separately but having a universal set of IGM parameters. I advocated a limited case of Foreman-Mackey and my endless applications of importance sampling. Gibbs sampling would work too. We discussed how to deal with the fact that different quasars might disagree mightily about the IGM parameters. Failure of support can ruin your whole day. We came up with a clever hack that extends a histogram of samples to complete support in the parameters space.
In Milky Way group meeting, Ness (MPIA) showed that there appears to be an over-density of metal-poor stars in the inner one degree (projected) at the center of the Milky Way. She is using APOGEE data and her home-built metallicity indicators. We discussed whether the effect could be caused by issues with selection (either because of dust or a different explicit selection program in this center-Galaxy field). If the effect is real, it is extremely interesting. For example, even if the stars were formed there, why would they stay there?
Well, first I would argue that you have to agree on what 'IGM' is before trying to set its parameters....don't get me started.
ReplyDeleteIn my experiments with this method ( http://arxiv.org/abs/1403.2660 ) it has proven very useful for combining posteriors from subsets of the available data into a median of probability measures; and if you apply the suggested cut at 1/(2*m) then it can reject outliers from this median estimate.
ReplyDelete