Create the reference solar abundance file

Here we join the Asplund+ (2009) data with other sources of information to create our output solar_abundances.fits file.



In [1]:

    
output_file = 'solarabundances.fits'



In [2]:

    
import matplotlib.pyplot as plt
import numpy as np
from astropy.io import fits
from astropy.table import Table,Column,join

Read in the Asplund+ (2009) data

For convenience, cull to Z < 75.



In [3]:

    
fl = 'asplund2009_abundances.txt'
asplund = Table.read(fl,format='ascii',comment=';')
asplund.remove_column('DIFF_PH_MET')

#Excise Z>75 data
gd = (asplund['Z'] <= 75)
solar = asplund[gd]

Add column for references:



In [4]:

    
reference_column = Column(['Asplund+ (2009)']*np.size(solar), name='Reference', dtype='U30')
solar.add_column(reference_column)

Simple text list of element names:



In [5]:

    
element_names=np.chararray.strip(solar['ELEMENT'])

Oxygen...issues.



In [6]:

    
o_indx = np.where((element_names.lower() == 'O'.lower()))
solar[o_indx]









    Out[6]:




Table length=1

Z ELEMENT PHOTO PHOTO_ERR METEOR METEOR_ERR BEST ERR Reference
int64 str2 float64 float64 float64 float64 float64 float64 str30
8 O 8.69 0.05 8.4 0.04 8.69 0.05 Asplund+ (2009)

Adopt the Steffen+ (2015) oxygen abundance



In [7]:

    
steffen = [8.76, 0.02]

solar['BEST'][o_indx] = steffen[0] # Steffen abundance
solar['ERR'][o_indx] = steffen[1]

solar['PHOTO'][o_indx] = steffen[0] # Steffen abundance
solar['PHOTO_ERR'][o_indx] = steffen[1]

solar['Reference'][o_indx] = 'Steffen+ (2015)'

#Total mass:
mmm = (10.**(solar['PHOTO'][0]-12.)/0.7381)
#Old oxygen mass:
print("Old O mass fraction: {0:0.5f}".format((10.**(asplund['PHOTO'][o_indx]-12.)*16./mmm)[0]))
#New oxygen mass:
print("New O mass fraction: {0:0.5f}".format((10.**(solar['BEST'][o_indx]-12.)*16./mmm)[0]))









    



Old O mass fraction: 0.00578
New O mass fraction: 0.00680



In [8]:

    
solar[o_indx]









    Out[8]:




Table length=1

Z ELEMENT PHOTO PHOTO_ERR METEOR METEOR_ERR BEST ERR Reference
int64 str2 float64 float64 float64 float64 float64 float64 str30
8 O 8.76 0.02 8.4 0.04 8.76 0.02 Steffen+ (2015)

Adopt the Amarsi+ (2018) oxygen abundance

Amarsi+ (2018) have questioned the results of Steffen+ (2015). Their derived abundance is equivalent to the original Asplund version. It appears the solar oxygen abundance is still in question.



In [9]:

    
amarsi = [8.69, 0.03]

solar['BEST'][o_indx] = amarsi[0] # Steffen abundance
solar['ERR'][o_indx] = amarsi[1]

solar['PHOTO'][o_indx] = amarsi[0] # Steffen abundance
solar['PHOTO_ERR'][o_indx] = amarsi[1]

solar['Reference'][o_indx] = 'Amarsi+ (2018);Asplund+ (2009)'

#Total mass:
mmm = (10.**(solar['PHOTO'][0]-12.)/0.7381)
#Old oxygen mass:
print("Old O mass fraction: {0:0.5f}".format((10.**(asplund['PHOTO'][o_indx]-12.)*16./mmm)[0]))
#New oxygen mass:
print("New O mass fraction: {0:0.5f}".format((10.**(solar['BEST'][o_indx]-12.)*16./mmm)[0]))









    



Old O mass fraction: 0.00578
New O mass fraction: 0.00578



In [10]:

    
solar[o_indx]









    Out[10]:




Table length=1

Z ELEMENT PHOTO PHOTO_ERR METEOR METEOR_ERR BEST ERR Reference
int64 str2 float64 float64 float64 float64 float64 float64 str30
8 O 8.69 0.03 8.4 0.04 8.69 0.03 Amarsi+ (2018);Asplund+ (2009)

Add mean atomic mass



In [11]:

    
iso = Table.read('isotopes.dat',format='ascii',comment=';;')
iso.keep_columns(['Z','AtomicWeight'])
atoms = join(solar,iso,keys='Z')

Now we have all the information we want in the combined table atoms.



In [12]:

    
atoms[0:5]









    Out[12]:




Table length=5

Z ELEMENT PHOTO PHOTO_ERR METEOR METEOR_ERR BEST ERR Reference AtomicWeight
int64 str2 float64 float64 float64 float64 float64 float64 str30 float64
1 H 12.0 30.0 8.22 0.04 12.0 0.0 Asplund+ (2009) 1.0079
2 He 10.93 0.01 1.29 30.0 10.93 0.01 Asplund+ (2009) 4.002602
3 Li 1.05 0.1 3.26 0.05 3.26 0.05 Asplund+ (2009) 6.968
4 Be 1.38 0.09 1.3 0.03 1.31 0.03 Asplund+ (2009) 9.01218
5 B 2.7 0.2 2.79 0.04 2.79 0.04 Asplund+ (2009) 10.813

Write to output file



In [13]:

    
atoms.write(output_file,overwrite=True)

Mean metal abundances by mass



In [156]:

    
# The abundance by mass:
eps = (10.**(atoms['BEST']-12.)*atoms['AtomicWeight']).data
total_mass = eps.sum()



In [157]:

    
plt.plot(atoms['Z'],np.log10(eps/total_mass),'ro-',markersize=4,lw=1);

Calculate X, Y, Z



In [158]:

    
X = eps[0]/total_mass
Y = eps[1]/total_mass



In [159]:

    
zzz = (atoms['Z'] > 2)
Z = eps[zzz].sum()/total_mass



In [160]:

    
print("\nMean abundances by mass: X=H, Y=He, Z=metals; mean mass per H atom, µ.\n")
print("\tX = {0:0.4f}".format(X))
print("\tY = {0:0.4f}".format(Y))
print("\tZ = {0:0.4f}".format(Z))
print("\tµ = {0:0.4f}".format(1./X))









    



Mean abundances by mass: X=H, Y=He, Z=metals; mean mass per H atom, µ.

	X = 0.7376
	Y = 0.2493
	Z = 0.0131
	µ = 1.3558

Thus the metal mass fraction in the solar system is Z = 0.0131.

The mean mass per H is µ = 1.36.

Z	ELEMENT	PHOTO	PHOTO_ERR	METEOR	METEOR_ERR	BEST	ERR	Reference
int64	str2	float64	float64	float64	float64	float64	float64	str30
8	O	8.69	0.05	8.4	0.04	8.69	0.05	Asplund+ (2009)