Quick Look for Observers

The difficulty with high-dispersion spectral analysis is that it takes a lot of work to make a small example spectrum. In my personal experience, it is surprisingly annoying to quickly find out if, for example, the water line was here or not during an observation. AutoRT was made for that purpose. Here is an example to quickly make the spectrum assuming water, CO, and CIA.

import numpy as np
import matplotlib.pyplot as plt
from exojax.spec import AutoRT
from exojax.utils.grids import wavenumber_grid

nus,wav,res=nugrid(23200,23300,1000,"AA") #compute a spectrum in 23200-23300 AA
Parr=np.logspace(-8,2,100)
Tarr = 1270.*(Parr/1.0)**0.1 #T-P profile

autort=AutoRT(nus,1.e5,2.33,Tarr,Parr) #g=1.e5 cm/s2, mmw=2.33
autort.addcia("H2-H2",0.74,0.74)       #CIA, mmr(H)=0.74
autort.addmol("ExoMol","CO",0.01,crit=1.e-45)  #CO line, mmr(CO)=0.01
autort.addmol("ExoMol","H2O",0.004,crit=1.e-40)  #H2O line, mmr(H2O)=0.004

F=autort.rtrun()
F=autort.spectrum(nus,100000.0,18.0,0.0) #R=100,000 and Vsini=18km/s
plt.plot(wav[::-1],F,label="CO+H2O emission")
plt.legend()
plt.show()

AutoXS was made for quick analysis of the cross section of molecules.

import numpy as np
import matplotlib.pyplot as plt
from exojax.spec import AutoXS, AutoRT
from exojax.utils.grids import wavenumber_grid

nus,wav,res=nugrid(23200,23300,1000,"AA")
autoxs=AutoXS(nus,"ExoMol","CO",memory_size=30)
xsv=autoxs.xsection(1000.0,1.0)
plt.plot(wav[::-1],xsv,label="CO")
plt.yscale("log")
plt.show()