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Differentiable spectral modelling of exoplanets/brown dwarfs/M dwarfs using JAX! Read the docs 🐕. In short, ExoJAX allows you to do gradient based optimizations and HMC-NUTS samplings using the latest database.
ExoJAX is at least compatible with
ExoJAX Classes
- Databases: *db (mdb: molecular, adb: atomic, cdb:continuum, pdb: particulates)
- Opacity Calculators: opa (i.e. Voigt profile)
- Atmospheric Radiative Transfer: art (emission w, w/o scattering, refelction, transmission)
- Atompsheric Microphysics: amp (clouds etc)
See this page for the first step!
Voigt Profile ✔️
from exojax.spec import voigt
nu=numpy.linspace(-10,10,100)
voigt(nu,1.0,2.0) #sigma_D=1.0, gamma_L=2.0Cross Section using HITRAN/HITEMP/ExoMol ✔️
from exojax.utils.grids import wavenumber_grid
from exojax.spec.api import MdbExomol
from exojax.spec.opacalc import OpaPremodit
from jax import config
config.update("jax_enable_x64", True)
nu_grid,wav,res=wavenumber_grid(1900.0,2300.0,200000,xsmode="premodit",unit="cm-1",)
mdb = MdbExomol(".database/CO/12C-16O/Li2015",nu_grid)
opa = OpaPremodit(mdb,nu_grid,auto_trange=[900.0,1100.0])
xsv = opa.xsvector(1000.0, 1.0) # cross section for 1000K, 1 bar
Do you just want to plot the line strength at T=1000K?
mdb.change_reference_temperature(1000.) # at 1000K
plt.plot(mdb.nu_lines,mdb.line_strength_ref,".")Emission Spectrum ✔️
art = ArtEmisPure(nu_grid=nu_grid, pressure_btm=1.e2, pressure_top=1.e-8, nlayer=100)
F = art.run(dtau, Tarr)
Transmission Spectrum ✔️
Reflection Spectrum ✔️
pip install exojax
or
python setup.py install
Note on installation w/ GPU support
📚 You need to install CUDA, JAX w/ NVIDIA GPU support.
Visit here for the installation of GPU supported JAX.
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- Paper I: Kawahara, Kawashima, Masuda, Crossfield, Pannier, van den Bekerom, ApJS 258, 31 (2022)
🐈 Copyright 2020-2024 ExoJAX contributors. ExoJAX is publicly available under the MIT license.