Absorption by a single species

[1]:

import pyarts
import numpy as np
import matplotlib.pyplot as plt

Select absorption species

[2]:

species = "O2-66"  # Main isotope of O2

Activate the recipe for this species

See SingleSpeciesAbsorption.

[3]:

absorption = pyarts.recipe.SingleSpeciesAbsorption(species=species)

Select a single temperature, a VMR value, and a range of pressures

[4]:

atm = pyarts.arts.AtmPoint()
atm.set_species_vmr("O2", 0.2095)
atm.temperature = 273
ps = np.logspace(5, -2, 8)

Select frequency range

[5]:

line_f0 = 118750348044.712  # Lowest energy absorption line
f = np.linspace(-500e6, 500e6, 1001) + line_f0  # Some range around it

Use the recipe and convert the results to cross-sections

[6]:

xsec = []
for p in ps:
    atm.pressure = p
    xsec.append(absorption(f, atm) / atm.number_density(species))
xsec = np.array(xsec)

Plot the results

[7]:

plt.semilogy((f - line_f0) / 1e6, xsec.T)
plt.xlabel("Frequency offset [MHz]")
plt.ylabel("Cross-section [$m^2$]")
plt.title("Cross-section of O$_2$ 16-16")
plt.ylim(ymin=1e-3 * np.min(xsec))
plt.legend(
    [f"P: $10^{'{'}{round(np.log10(x))}{'}'}$" for x in ps],
    ncols=4,
    loc="lower center",
)

[7]:

<matplotlib.legend.Legend at 0x7ffb2c29e150>

_images/examples.recipes.SingleSpeciesAbsorption_13_1.svg

Integration test by ensuring some statistics look good

[8]:

assert np.isclose(6.792977548868407e-28 / xsec.mean(), 1)
assert np.isclose(5.43981642113382e-24 / xsec.sum(), 1)
assert np.isclose(1.3359834491781882e-24 / xsec.max(), 1)
assert np.isclose(2.537911691540087e-26 / xsec.std(), 1)
assert np.isclose(8.236637542411964e-35 / xsec.min(), 1)