Poor optically thin N2H+(1-0) fit #125
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this is the code to reproduce the problem: import pyspeckit
from pyspeckit.spectrum.models import n2hp
import numpy as np
import astropy.units as u
cube = pyspeckit.Spectrum('73-core2_N2Hp.fits')
rms=0.046
cube.error[:] = rms
cube.xarr.refX = 93173.772e6*u.Hz
cube.xarr.velocity_convention = 'radio'
cube.xarr.convert_to_unit('km/s')
F=False
T=True
import matplotlib.pyplot as plt
plt.ion()
cube.Registry.add_fitter('n2hp_vtau', pyspeckit.models.n2hp.n2hp_vtau_fitter,4)
cube.specfit(fittype='n2hp_vtau', guesses=[3.94, 0.1, 0, 0.309],
verbose_level=4, signal_cut=3, limitedmax=[F,T,T,T], limitedmin=[T,T,T,T],
minpars=[0, 0, -1, 0.05], maxpars=[30.,50.,1,1.0], fixed=[F,T,F,F])
cube.plotter(errstyle='fill')
cube.specfit.plot_fit()
plt.savefig('N2Hp_pyspeckit_fit.png')Only to complement the information, usually the optically thin model is used when |
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OK, that's pretty strange. I will investigate. |
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This is a very serious issue that will trigger a new bugfix release today (after having released only a few hours ago...): when @jpinedaf was here last, we corrected the RJ-assumption RT equation to use the full Planck function, but there was a typo. |
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sorry that I didn't see that one! |
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This change does fix the issue! Thanks a lot @keflavich
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Great! Thank you @keflavich! |
keflavich
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Dec 10, 2015
Poor optically thin N2H+(1-0) fit
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Optically thin fit does not reproduce N2H+(1-0) hyperfine structure and returns too high T_ex (e+11) and sigma, two times bigger than a real value (calculated with CLASS or optically thick approach).
The criterion we use to decide which fit results to use, optically thin or thick, is tau/delta_tau>=3. Most of N2H+(1-0) spectra will pass this criterion, however there are points on the edges of the cores where N2H+ line is not strong enough so we need optically thin approach.
I've checked some of such points and optically thin fit does not give good result, please see the thin and thick fits of the same spectrum in the attached figures. The spectrum used to produce the figures is here https://github.com/Punanova/thick_vs_thin/blob/master/73-core2_N2Hp.fits
.