Fit looks good but parameters are odd.
LydiaMak opened this issue · 15 comments
I am fitting an SED and although my fit looks good the parameters are oddly distributed (especially tage) and MCMC results look odd. I keep in general the initial parameters and priors as default except
model_params["lumdist"] = {"N": 1, "isfree": False, "init": ldist, "units":"Mpc"}
# Let's make some changes to initial values appropriate for our objects and data
#model_params["zred"]["init"] = 0.0
#model_params["dust2"]["init"] = 0.05
#model_params["logzsol"]["init"] = -0.5
model_params["tage"]["init"] = 13.
model_params["mass"]["init"] = 1e9
# These are dwarf galaxies, so lets also adjust the metallicity prior,
# the tau parameter upward, and the mass prior downward
#model_params["dust2"]["prior"] = priors.TopHat(mini=0.0, maxi=2.0)
#model_params["tau"]["prior"] = priors.LogUniform(mini=1e-1, maxi=1e2)
model_params["mass"]["prior"] = priors.LogUniform(mini=1e8, maxi=1e12)
That chain does not look converged. You could try running it for longer, or try the dynesty sampler.
The example before was also setting both ldist and redshift in run_params. If I set only the ldist and also give the prior of mass like that
model_params["mass"]["prior"] = priors.LogUniform(mini=1e8, maxi=1e12)
I got the attached results. Is it wrong to set both?
However, what really bothers me is the tage which doesn't make sense at all. Is it necessary to give a
model_params["tage"]["disp_floor"]?
There is something odd happening with the initial parameters after running optimization or emcee and instead of initial tage = 13 the initial tage is 1.1 for example. Not sure why this is happening.
The chain for mass does not look converged, and is taking a long time to diffuse in the parameter space. I suspect this is to do with the initial width of the set of walkers in this parameter. I suggest increasing disp_floor dramatically, and/or cross-checking using dynesty.
Re lumdist and zred, if you set both then the distance modulus will come from lumdit but the spectrum will be shifted in wavelength by 1+zred before projecting the filters. Sometimes this is the right thing to do (e.g. if you have narrow filters and the object is decoupled from the hubble flow, such that the luminosity distance is not directly related to the redshift)
Why do you think the tage value does not make sense? Is this a very red, quiescent galaxy? For parametric (tau, delay tau) SFHs the value of tage need not actually have anything to do with the actual age of the universe, it just describes the last significant SF event. See e.g. Leja et al 2019 or Carnall et al 2019
Ok, I will try the thing about mass.
The galaxy is probably a post-starburst galaxy from spectrum. g-r ~ 0.68. From the interactive demo notebook I thought tage is the age of the galaxy but I guess it's more in the sense of stellar populations?
For dynesty using these
model_params = TemplateLibrary["parametric_sfh"]
model_params["dust2"]["init"] = 0.1
model_params["logzsol"]["init"] = -0.3
model_params["tage"]["init"] = 13.
model_params["mass"]["init"] = 1e8
model_params["dust2"]["prior"] = priors.TopHat(mini=0.0, maxi=2.0)
model_params["tau"]["prior"] = priors.LogUniform(mini=1e-1, maxi=10)
model_params["mass"]["prior"] = priors.LogUniform(mini=1e6, maxi=1e10)
I get the attached.
That seems largely consistent with the emcee results (though I still suggest increasing disp_floor for stellar mass). Noticing that dust2 is hitting the upper prior edge, do you expect this to be a very dusty galaxy?
oh wait, if it's a post-starburst I'm not sure you're going to get good/believable fits with a parametric SFH.....
It has been used before in such cases but I have seen non-parametric used as well. Should I try a non-parametric one better (but there are many options)?
Also, no, I don't think it should be that dusty. And metallicity result seems strange.
Ok. I think I figured the main issue. It was on the photometry I was using mostly for SDSS where I was not using the CModel photometry as I should. I will get back with the results once I confirm that everything is correct for 2MASS and WISE.
Ok, I think the results make much more sense now.
great, though it does seem like you are bmping up against an upper prior limit for stellar mass, you may want to increase the prior range.
Yes, I will close the issue for now and if something comes up I will re-open it! Thank you for all your help!
Reopening the issue as something strange is happening. Just by changing the prior limits for the mass from 10^6-10^10 to 10^6-10^11 gives me this very strange result
Same happens for Dynesty.
you have a few stuck walkers, you can reinitialize with starting parameters closer the bulk of the walkers, or you can run longer till they become unstuck. It's stochastic though, so it might not always happen. You can also try dynesty again.