Flexible model creation and molecule formation investigation
This notebook will explore how to create and explore a custom model, and use that to compare the stardis molecular solver to the molecular solver implemented in Korg.
[1]:
#Basic needed imports
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from stardis.io.base import parse_config_to_model
from stardis.plasma import create_stellar_plasma
from astropy import units as u
/home/runner/micromamba/envs/stardis/lib/python3.12/site-packages/setuptools_scm/git.py:167: UserWarning: "/home/runner/work/stardis/stardis" is shallow and may cause errors
warnings.warn(f'"{wd.path}" is shallow and may cause errors')
[2]:
config, adata, stellar_model = parse_config_to_model('basic_config.yml')
WARNING: UnitsWarning: 'erg/cm2/s' contains multiple slashes, which is discouraged by the FITS standard [astropy.units.format.generic]
[3]:
stellar_model.temperatures
[3]:
$[9934.3,~9678.4,~9424.6,~9168.5,~8903.8,~8620.2,~8462.6,~8290.4,~8097.7,~7876.9,~7618.2,~7314.8,~6983.3,~6694.8,~6451.9,~6235.2,~6044.3,~5875.7,~5727.4,~5597.1,~5483.1,~5382.5,~5294.4,~5216.8,~5148.5,~5088.6,~5034.4,~4988.1,~4944.1,~4905.9,~4870.5,~4838.3,~4808.6,~4780.9,~4754.7,~4729.9,~4706,~4682.9,~4660.2,~4637.8,~4615.6,~4593.5,~4571.5,~4549.5,~4527.4,~4504.9,~4461,~4416.3,~4371.3,~4326.1,~4280.8,~4235.5,~4190.4,~4145.9,~4102.6,~4066.8] \; \mathrm{K}$
These temperatures come from the model we read in, which represent the sun. However, for demonstration purposes, let’s overwrite these temperatures to go from 3,000 to 10,000 K. This can be done by simply overwriting the object’s temperatures attribute. For ease of use, let’s match the same number of depth points as the existing one, so we don’t have to worry about shape mismatches for other parts of the model. We’ll also overwrite the density so we can examine how molecular formation changes purely as a function of temperature.
[4]:
stellar_model.temperatures = np.linspace(3000, 10000, len(stellar_model.temperatures)) * u.K
stellar_model.composition.density = np.ones_like(stellar_model.composition.density) * 3e-7 #This is a reasonable density above the solar photosphere
[5]:
stellar_plasma = create_stellar_plasma(stellar_model, adata, config) #Then we go ahead and create the stellar plasma. This will solve the ionization and molecular balance equations.
Negative ionic molecules not currently supported. Assuming no H2-.
Negative ionic molecules not currently supported. Assuming no C2-.
Negative ionic molecules not currently supported. Assuming no CH-.
Negative ionic molecules not currently supported. Assuming no OH-.
Negative ionic molecules not currently supported. Assuming no SiH-.
Negative ionic molecules not currently supported. Assuming no HS-.
Negative ionic molecules not currently supported. Assuming no CN-.
Negative ionic molecules not currently supported. Assuming no CS-.
Negative ionic molecules not currently supported. Assuming no FeO-.
Negative ionic molecules not currently supported. Assuming no H2-.
Negative ionic molecules not currently supported. Assuming no C2-.
Negative ionic molecules not currently supported. Assuming no CH-.
Negative ionic molecules not currently supported. Assuming no OH-.
Negative ionic molecules not currently supported. Assuming no SiH-.
Negative ionic molecules not currently supported. Assuming no HS-.
Negative ionic molecules not currently supported. Assuming no CN-.
Negative ionic molecules not currently supported. Assuming no CS-.
Negative ionic molecules not currently supported. Assuming no FeO-.
Now we can investigate each of the molecular densities in the plasma.
[6]:
stellar_plasma.molecule_number_density
[6]:
| 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | ... | 46 | 47 | 48 | 49 | 50 | 51 | 52 | 53 | 54 | 55 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Molecule | |||||||||||||||||||||
| H2 | 4.173526e+16 | 3.524205e+16 | 2.836289e+16 | 2.166660e+16 | 1.573569e+16 | 1.096084e+16 | 7.430232e+15 | 4.985077e+15 | 3.362091e+15 | 2.305035e+15 | ... | 4.149437e+12 | 3.827602e+12 | 3.536749e+12 | 3.273035e+12 | 3.033149e+12 | 2.814238e+12 | 2.613836e+12 | 2.429808e+12 | 2.260302e+12 | 2.103711e+12 |
| Li2 | 1.083895e+04 | 2.556534e+03 | 0.000000e+00 | 1.736232e+04 | 1.703398e+04 | 1.801338e+03 | 1.225000e+03 | 1.076660e+04 | 0.000000e+00 | 1.439098e+04 | ... | 4.810851e+03 | 4.919161e+03 | 5.027418e+03 | 5.135517e+03 | 5.243352e+03 | 5.350815e+03 | 5.457791e+03 | 5.564162e+03 | 5.669803e+03 | 5.774583e+03 |
| B2 | 2.001489e+02 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 7.175067e+02 | 0.000000e+00 | 5.503644e+03 | 0.000000e+00 | 0.000000e+00 | 2.124297e+03 | ... | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 1.826164e+05 | 3.438785e+04 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 5.516299e+05 | 0.000000e+00 |
| C2 | 6.308218e+12 | 3.764890e+12 | 1.997027e+12 | 9.841823e+11 | 4.723712e+11 | 2.282457e+11 | 1.132013e+11 | 5.827353e+10 | 3.135724e+10 | 1.769409e+10 | ... | 1.067086e+06 | 9.004944e+05 | 7.623889e+05 | 6.446457e+05 | 5.484334e+05 | 4.625608e+05 | 4.130229e+05 | 3.298226e+05 | 2.813122e+05 | 2.418078e+05 |
| N2 | 4.483557e+12 | 4.460950e+12 | 4.418194e+12 | 4.339952e+12 | 4.202556e+12 | 3.973703e+12 | 3.618028e+12 | 3.113891e+12 | 2.481482e+12 | 1.800708e+12 | ... | 2.491493e+06 | 2.056682e+06 | 1.706652e+06 | 1.420066e+06 | 1.185691e+06 | 9.944353e+05 | 8.355199e+05 | 7.034911e+05 | 5.936564e+05 | 5.033554e+05 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| GeSe | 1.797603e+01 | 8.097244e+00 | 4.711990e+00 | 3.587088e+00 | 1.691207e+00 | 9.164035e-01 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | ... | 0.000000e+00 | 0.000000e+00 | 6.131447e+03 | 0.000000e+00 | 2.134916e+05 | 6.881388e+04 | 1.310527e+04 | 4.099053e+04 | 1.473623e+05 | 3.273818e+05 |
| KBr | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 4.237644e-01 | 1.012536e+01 | 0.000000e+00 | 1.210853e+01 | 0.000000e+00 | 4.715811e+01 | 0.000000e+00 | ... | 2.219070e+04 | 9.215178e+04 | 0.000000e+00 | 2.960028e+04 | 3.399918e+04 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 |
| SiTe | 3.280525e+02 | 1.982031e+02 | 7.249512e+01 | 5.465405e+01 | 0.000000e+00 | 1.329663e+01 | 0.000000e+00 | 4.557781e+02 | 6.401628e+02 | 0.000000e+00 | ... | 6.349098e+04 | 0.000000e+00 | 2.342839e+05 | 0.000000e+00 | 3.321557e+05 | 3.750577e+05 | 0.000000e+00 | 1.656807e+05 | 3.604702e+05 | 4.431267e+05 |
| GeTe | 2.118515e+00 | 0.000000e+00 | 0.000000e+00 | 5.061211e+01 | 9.543540e+01 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | ... | 0.000000e+00 | 2.200635e+05 | 0.000000e+00 | 1.848813e+05 | 0.000000e+00 | 2.012299e+05 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 3.588300e+05 |
| KI | 0.000000e+00 | 3.575574e+00 | 3.159040e+01 | 0.000000e+00 | 1.041164e+02 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 1.562940e+02 | 0.000000e+00 | ... | 0.000000e+00 | 2.678832e+04 | 0.000000e+00 | 4.142413e+04 | 2.435976e+04 | 3.496347e+04 | 7.330461e+04 | 1.393621e+05 | 0.000000e+00 | 0.000000e+00 |
291 rows × 56 columns
[7]:
korg_densities = pd.read_csv('korg_comparison_number_densities.csv') #This is a file with output number densities gathered from Korg, using the same densities and temperatures defined here.
[8]:
korg_densities
[8]:
| T | C2 | H2 | O2 | HHplus | |
|---|---|---|---|---|---|
| 0 | 3000.0000 | 2.530050e+01 | 4.175859e+16 | 4.990826e+08 | 7.781635e+00 |
| 1 | 3127.2727 | 9.400628e+01 | 3.444805e+16 | 7.489777e+08 | 5.935924e+01 |
| 2 | 3254.5454 | 3.963682e+02 | 2.709785e+16 | 8.674742e+08 | 3.633406e+02 |
| 3 | 3381.8181 | 1.835227e+03 | 2.035246e+16 | 8.131400e+08 | 1.807372e+03 |
| 4 | 3509.0908 | 8.830996e+03 | 1.469220e+16 | 6.600394e+08 | 7.386049e+03 |
| 5 | 3636.3635 | 4.247642e+04 | 1.030661e+16 | 4.875497e+08 | 2.523339e+04 |
| 6 | 3763.6362 | 1.990776e+05 | 7.115632e+15 | 3.391470e+08 | 7.402898e+04 |
| 7 | 3890.9089 | 8.859317e+05 | 4.890974e+15 | 2.294073e+08 | 1.923825e+05 |
| 8 | 4018.1816 | 3.639707e+06 | 3.376555e+15 | 1.555365e+08 | 4.558531e+05 |
| 9 | 4145.4543 | 1.334790e+07 | 2.354848e+15 | 1.088003e+08 | 1.008459e+06 |
| 10 | 4272.7270 | 4.179838e+07 | 1.664657e+15 | 8.089770e+07 | 2.120734e+06 |
| 11 | 4399.9997 | 1.066539e+08 | 1.194737e+15 | 6.542193e+07 | 4.295063e+06 |
| 12 | 4527.2724 | 2.161158e+08 | 8.710359e+14 | 5.748114e+07 | 8.452567e+06 |
| 13 | 4654.5451 | 3.498605e+08 | 6.449981e+14 | 5.329004e+07 | 1.625382e+07 |
| 14 | 4781.8178 | 4.637127e+08 | 4.848620e+14 | 5.005032e+07 | 3.062428e+07 |
| 15 | 4909.0905 | 5.182725e+08 | 3.697505e+14 | 4.604665e+07 | 5.656093e+07 |
| 16 | 5036.3632 | 5.043794e+08 | 2.858153e+14 | 4.078431e+07 | 1.022459e+08 |
| 17 | 5163.6359 | 4.427584e+08 | 2.237668e+14 | 3.475198e+07 | 1.802601e+08 |
| 18 | 5290.9086 | 3.630244e+08 | 1.772946e+14 | 2.876599e+07 | 3.080865e+08 |
| 19 | 5418.1813 | 2.861592e+08 | 1.420541e+14 | 2.341764e+07 | 5.064037e+08 |
| 20 | 5545.4540 | 2.212943e+08 | 1.150152e+14 | 1.893879e+07 | 7.945201e+08 |
| 21 | 5672.7267 | 1.700065e+08 | 9.403810e+13 | 1.531782e+07 | 1.185694e+09 |
| 22 | 5799.9994 | 1.306757e+08 | 7.759292e+13 | 1.243801e+07 | 1.686568e+09 |
| 23 | 5927.2721 | 1.008814e+08 | 6.457310e+13 | 1.015987e+07 | 2.300636e+09 |
| 24 | 6054.5448 | 7.836478e+07 | 5.416917e+13 | 8.356222e+06 | 3.031979e+09 |
| 25 | 6181.8175 | 6.129999e+07 | 4.578299e+13 | 6.922415e+06 | 3.887110e+09 |
| 26 | 6309.0902 | 4.829544e+07 | 3.896796e+13 | 5.776106e+06 | 4.875239e+09 |
| 27 | 6436.3629 | 3.831673e+07 | 3.338691e+13 | 4.853654e+06 | 6.007844e+09 |
| 28 | 6563.6356 | 3.060270e+07 | 2.878293e+13 | 4.106246e+06 | 7.298140e+09 |
| 29 | 6690.9083 | 2.459422e+07 | 2.495858e+13 | 3.496479e+06 | 8.760624e+09 |
| 30 | 6818.1810 | 1.987946e+07 | 2.176088e+13 | 2.995622e+06 | 1.041072e+10 |
| 31 | 6945.4537 | 1.615349e+07 | 1.907039e+13 | 2.581498e+06 | 1.226452e+10 |
| 32 | 7072.7264 | 1.318902e+07 | 1.679310e+13 | 2.236899e+06 | 1.433852e+10 |
| 33 | 7199.9991 | 1.081518e+07 | 1.485432e+13 | 1.948348e+06 | 1.664929e+10 |
| 34 | 7327.2718 | 8.902745e+06 | 1.319438e+13 | 1.705244e+06 | 1.921325e+10 |
| 35 | 7454.5445 | 7.353404e+06 | 1.176550e+13 | 1.499227e+06 | 2.204644e+10 |
| 36 | 7581.8172 | 6.091811e+06 | 1.052916e+13 | 1.323658e+06 | 2.516441e+10 |
| 37 | 7709.0899 | 5.059765e+06 | 9.454148e+12 | 1.173235e+06 | 2.858187e+10 |
| 38 | 7836.3626 | 4.211974e+06 | 8.514986e+12 | 1.043695e+06 | 3.231249e+10 |
| 39 | 7963.6353 | 3.512942e+06 | 7.690794e+12 | 9.315901e+05 | 3.636858e+10 |
| 40 | 8090.9080 | 2.934686e+06 | 6.964403e+12 | 8.341261e+05 | 4.076100e+10 |
| 41 | 8218.1807 | 2.455215e+06 | 6.322030e+12 | 7.490830e+05 | 4.550051e+10 |
| 42 | 8345.4534 | 2.056922e+06 | 5.752291e+12 | 6.746483e+05 | 5.059739e+10 |
| 43 | 8472.7261 | 1.725497e+06 | 5.245502e+12 | 6.092985e+05 | 5.606044e+10 |
| 44 | 8599.9988 | 1.449272e+06 | 4.793406e+12 | 5.517493e+05 | 6.189667e+10 |
| 45 | 8727.2715 | 1.218709e+06 | 4.388942e+12 | 5.009152e+05 | 6.811107e+10 |
| 46 | 8854.5442 | 1.025989e+06 | 4.026059e+12 | 4.558764e+05 | 7.470626e+10 |
| 47 | 8981.8169 | 8.646861e+05 | 3.699559e+12 | 4.158519e+05 | 8.168222e+10 |
| 48 | 9109.0896 | 7.294670e+05 | 3.404836e+12 | 3.801574e+05 | 8.903400e+10 |
| 49 | 9236.3623 | 6.157404e+05 | 3.137219e+12 | 3.481090e+05 | 9.674025e+10 |
| 50 | 9363.6350 | 5.197659e+05 | 2.892626e+12 | 3.191165e+05 | 1.047672e+11 |
| 51 | 9490.9077 | 4.385582e+05 | 2.667754e+12 | 2.927082e+05 | 1.130724e+11 |
| 52 | 9618.1804 | 3.697125e+05 | 2.459928e+12 | 2.685063e+05 | 1.216042e+11 |
| 53 | 9745.4531 | 3.112730e+05 | 2.266986e+12 | 2.462078e+05 | 1.303018e+11 |
| 54 | 9872.7258 | 2.616349e+05 | 2.087180e+12 | 2.255704e+05 | 1.390956e+11 |
| 55 | 9999.9985 | 2.194700e+05 | 1.919105e+12 | 2.064002e+05 | 1.479072e+11 |
[9]:
fig = plt.figure(figsize=(8, 8))
ax1 = plt.subplot(211)
plt.plot(stellar_model.temperatures, stellar_plasma.molecule_number_density.loc['C2'], label='stardis')
plt.plot(korg_densities['T'], korg_densities['C2'], label='Korg')
plt.yscale('log')
plt.xlabel('T [K]')
plt.ylabel('C2 Number Density $[cm^{-3}]$')
plt.xlim(4000, 10000)
plt.legend()
ax2 = plt.subplot(212, sharex= ax1)
plt.plot(stellar_model.temperatures, (stellar_plasma.molecule_number_density.loc['C2'] - korg_densities['C2']) / korg_densities['C2'], label='Fractional Difference')
plt.yscale('log')
plt.xlabel('T [K]')
plt.ylabel('C2 Fractional Difference')
plt.ylim(1e-4, 1e4)
plt.xlim(4000, 10000)
plt.legend()
[9]:
<matplotlib.legend.Legend at 0x7faf365b1790>
[10]:
fig = plt.figure(figsize=(8, 8))
ax1 = plt.subplot(211)
plt.plot(stellar_model.temperatures, stellar_plasma.molecule_number_density.loc['H2'], label='stardis')
plt.plot(korg_densities['T'], korg_densities['H2'], label='Korg')
plt.yscale('log')
plt.xlabel('T [K]')
plt.ylabel('H2 Number Density $[cm^{-3}]$')
plt.xlim(4000, 10000)
plt.legend()
ax2 = plt.subplot(212, sharex= ax1)
plt.plot(stellar_model.temperatures, (stellar_plasma.molecule_number_density.loc['H2'] - korg_densities['H2']) / korg_densities['H2'], label='Fractional Difference')
plt.yscale('log')
plt.xlabel('T [K]')
plt.ylabel('H2 Fractional Difference')
plt.ylim(1e-4, 1)
plt.xlim(4000, 10000)
plt.legend()
[10]:
<matplotlib.legend.Legend at 0x7faf347773b0>
[11]:
fig = plt.figure(figsize=(8, 8))
ax1 = plt.subplot(211)
plt.plot(stellar_model.temperatures, stellar_plasma.molecule_number_density.loc['H2+'], label='stardis')
plt.plot(korg_densities['T'], korg_densities['HHplus'], label='Korg')
plt.yscale('log')
plt.xlabel('T [K]')
plt.ylabel('H2+ Number Density $[cm^{-3}]$')
plt.xlim(4000, 10000)
plt.legend()
ax2 = plt.subplot(212, sharex= ax1)
plt.plot(stellar_model.temperatures, (stellar_plasma.molecule_number_density.loc['H2+'] - korg_densities['HHplus']) / korg_densities['HHplus'], label='Fractional Difference')
plt.yscale('log')
plt.xlabel('T [K]')
plt.ylabel('H2+ Fractional Difference')
plt.ylim(1e-4, 1)
plt.xlim(4000, 10000)
plt.legend()
[11]:
<matplotlib.legend.Legend at 0x7faf34777b00>
[12]:
fig = plt.figure(figsize=(8, 8))
ax1 = plt.subplot(211)
plt.plot(stellar_model.temperatures, stellar_plasma.molecule_number_density.loc['O2'], label='stardis')
plt.plot(korg_densities['T'], korg_densities['O2'], label='Korg')
plt.yscale('log')
plt.xlabel('T [K]')
plt.ylabel('O2 Number Density $[cm^{-3}]$')
plt.xlim(4000, 10000)
plt.legend()
ax2 = plt.subplot(212, sharex= ax1)
plt.plot(stellar_model.temperatures, (stellar_plasma.molecule_number_density.loc['O2'] - korg_densities['O2']) / korg_densities['O2'], label='Fractional Difference')
plt.yscale('log')
plt.xlabel('T [K]')
plt.ylabel('O2 Fractional Difference')
plt.ylim(1e-4, 1e4)
plt.xlim(4000, 10000)
plt.legend()
[12]:
<matplotlib.legend.Legend at 0x7faf34421010>
This was a small comparison of choice molecules between stardis and korg, but the stellar plasma object contains much more information. We could also choose to look at any given ionization or excitation level of each atomic species.
[13]:
stellar_plasma.ion_number_density
[13]:
| 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | ... | 46 | 47 | 48 | 49 | 50 | 51 | 52 | 53 | 54 | 55 | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| atomic_number | ion_number | |||||||||||||||||||||
| 1 | 0 | 1.333170e+17 | 1.333170e+17 | 1.333170e+17 | 1.333170e+17 | 1.333170e+17 | 1.333170e+17 | 1.333170e+17 | 1.333170e+17 | 1.333170e+17 | 1.333170e+17 | ... | 1.311392e+17 | 1.308210e+17 | 1.304675e+17 | 1.300761e+17 | 1.296441e+17 | 1.291690e+17 | 1.286481e+17 | 1.280788e+17 | 1.274584e+17 | 1.267844e+17 |
| 1 | 2.738518e+03 | 1.887806e+04 | 1.119614e+05 | 5.766579e+05 | 2.585475e+06 | 1.013382e+07 | 3.515037e+07 | 1.098660e+08 | 3.153993e+08 | 8.458353e+08 | ... | 2.177806e+15 | 2.495957e+15 | 2.849473e+15 | 3.240910e+15 | 3.672864e+15 | 4.147965e+15 | 4.668853e+15 | 5.238170e+15 | 5.858540e+15 | 6.532551e+15 | |
| 2 | 0 | 1.093668e+16 | 1.093668e+16 | 1.093668e+16 | 1.093668e+16 | 1.093668e+16 | 1.093668e+16 | 1.093668e+16 | 1.093668e+16 | 1.093668e+16 | 1.093668e+16 | ... | 1.093668e+16 | 1.093668e+16 | 1.093668e+16 | 1.093668e+16 | 1.093668e+16 | 1.093668e+16 | 1.093668e+16 | 1.093668e+16 | 1.093667e+16 | 1.093667e+16 |
| 1 | 3.111301e-16 | 1.209731e-14 | 3.534625e-13 | 7.954445e-12 | 1.400211e-10 | 1.957991e-09 | 2.223270e-08 | 2.105025e-07 | 1.706455e-06 | 1.212486e-05 | ... | 4.042059e+08 | 5.695133e+08 | 7.949838e+08 | 1.099874e+09 | 1.508779e+09 | 2.052884e+09 | 2.771466e+09 | 3.713671e+09 | 4.940619e+09 | 6.527878e+09 | |
| 2 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | ... | 3.922646e-17 | 1.355096e-16 | 4.524227e-16 | 1.461956e-15 | 4.578652e-15 | 1.391617e-14 | 4.109761e-14 | 1.180691e-13 | 3.303397e-13 | 9.010497e-13 | |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 92 | 88 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | ... | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 |
| 89 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | ... | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | |
| 90 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | ... | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | |
| 91 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | ... | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | |
| 92 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | ... | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 |
4370 rows × 56 columns
[14]:
stellar_plasma.level_number_density
[14]:
| 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | ... | 46 | 47 | 48 | 49 | 50 | 51 | 52 | 53 | 54 | 55 | |||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| atomic_number | ion_number | level_number | |||||||||||||||||||||
| 1 | 0 | 0 | 1.333170e+17 | 1.333170e+17 | 1.333170e+17 | 1.333170e+17 | 1.333170e+17 | 1.333170e+17 | 1.333170e+17 | 1.333170e+17 | 1.333170e+17 | 1.333170e+17 | ... | 1.311392e+17 | 1.308210e+17 | 1.304675e+17 | 1.300761e+17 | 1.296441e+17 | 1.291690e+17 | 1.286481e+17 | 1.280788e+17 | 1.274584e+17 | 1.267844e+17 |
| 1 | 0 | 2.738518e+03 | 1.887806e+04 | 1.119614e+05 | 5.766579e+05 | 2.585475e+06 | 1.013382e+07 | 3.515037e+07 | 1.098660e+08 | 3.153993e+08 | 8.458353e+08 | ... | 2.177806e+15 | 2.495957e+15 | 2.849473e+15 | 3.240910e+15 | 3.672864e+15 | 4.147965e+15 | 4.668853e+15 | 5.238170e+15 | 5.858540e+15 | 6.532551e+15 | |
| 2 | 0 | 0 | 1.093668e+16 | 1.093668e+16 | 1.093668e+16 | 1.093668e+16 | 1.093668e+16 | 1.093668e+16 | 1.093668e+16 | 1.093668e+16 | 1.093668e+16 | 1.093668e+16 | ... | 1.093668e+16 | 1.093668e+16 | 1.093668e+16 | 1.093668e+16 | 1.093668e+16 | 1.093668e+16 | 1.093668e+16 | 1.093668e+16 | 1.093667e+16 | 1.093667e+16 |
| 1 | 1.661479e-17 | 3.763092e-16 | 6.677489e-15 | 9.542576e-14 | 1.124429e-12 | 1.114832e-11 | 9.464682e-11 | 6.986081e-10 | 4.543251e-09 | 2.633726e-08 | ... | 1.718646e+05 | 2.483340e+05 | 3.551559e+05 | 5.029440e+05 | 7.055253e+05 | 9.807612e+05 | 1.351537e+06 | 1.846951e+06 | 2.503720e+06 | 3.367851e+06 | ||
| 2 | 2.546131e-19 | 6.536775e-18 | 1.301989e-16 | 2.070421e-15 | 2.693755e-14 | 2.928577e-13 | 2.709363e-12 | 2.167044e-11 | 1.519374e-10 | 9.452067e-10 | ... | 2.017951e+04 | 2.959249e+04 | 4.293446e+04 | 6.165615e+04 | 8.767468e+04 | 1.235012e+05 | 1.723973e+05 | 2.385645e+05 | 3.273739e+05 | 4.456396e+05 | ||
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 92 | 88 | 0 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | ... | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 |
| 89 | 0 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | ... | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | |
| 90 | 0 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | ... | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | |
| 91 | 0 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | ... | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | |
| 92 | 0 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | ... | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 |
41033 rows × 56 columns
[ ]: