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https://github.com/HajimeKawahara/exojax

🐈 Automatic differentiable spectrum modeling of exoplanets/brown dwarfs using JAX, compatible with NumPyro and JAXopt
https://github.com/HajimeKawahara/exojax

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🐈 Automatic differentiable spectrum modeling of exoplanets/brown dwarfs using JAX, compatible with NumPyro and JAXopt

Host: GitHub
URL: https://github.com/HajimeKawahara/exojax
Owner: HajimeKawahara
License: mit
Created: 2020-12-12T03:46:49.000Z (almost 4 years ago)
Default Branch: master
Last Pushed: 2024-07-20T07:55:24.000Z (2 months ago)
Last Synced: 2024-07-22T11:16:20.599Z (about 2 months ago)
Language: Jupyter Notebook
Homepage: http://secondearths.sakura.ne.jp/exojax/
Size: 187 MB
Stars: 41
Watchers: 4
Forks: 14
Open Issues: 25
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE

Awesome Lists containing this project

awesome-jax - exojax - Automatic differentiable spectrum modeling of exoplanets/brown dwarfs compatible to JAX. <img src="https://img.shields.io/github/stars/HajimeKawahara/exojax?style=social" align="center"> (Libraries / New Libraries)

README

        # ExoJAX

 [![License](https://img.shields.io/github/license/HajimeKawahara/exojax)](https://github.com/HajimeKawahara/exojax/blob/develop/LICENSE)

 [![Docs](https://img.shields.io/badge/docs-exojax-brightgreen)](http://secondearths.sakura.ne.jp/exojax/)

 [![arxiv](https://img.shields.io/badge/arxiv-2105.14782-blue)](http://arxiv.org/abs/2105.14782)

 [![paper](https://img.shields.io/badge/paper-ApJS_258_31_(2022)-orange)](https://iopscience.iop.org/article/10.3847/1538-4365/ac3b4d) 

 

Differentiable spectral modelling of exoplanets/brown dwarfs/M dwarfs using JAX!

Read [the docs](http://secondearths.sakura.ne.jp/exojax/develop) 🐕. 

In short, ExoJAX allows you to do gradient based optimizations and HMC-NUTS samplings using the latest database.

ExoJAX is at least compatible with

- PPLs: [NumPyro](https://github.com/pyro-ppl/numpyro), [blackjax](https://github.com/blackjax-devs/blackjax) 

- Optimizers: [JAXopt](https://github.com/google/jaxopt), [optax](https://github.com/google-deepmind/optax), [bayeux](https://github.com/jax-ml/bayeux)



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)

## Get Started 

See [this page](http://secondearths.sakura.ne.jp/exojax/develop/tutorials/get_started.html) for the first step!

## Functions

Voigt Profile :heavy_check_mark: 

```python3

from exojax.spec import voigt

nu=numpy.linspace(-10,10,100)

voigt(nu,1.0,2.0) #sigma_D=1.0, gamma_L=2.0

```

Cross Section using HITRAN/HITEMP/ExoMol :heavy_check_mark: 

 

```python

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? 

```python

mdb.change_reference_temperature(1000.) # at 1000K

plt.plot(mdb.nu_lines,mdb.line_strength_ref,".")

```

Emission Spectrum :heavy_check_mark: 

```python

art = ArtEmisPure(nu_grid=nu_grid, pressure_btm=1.e2, pressure_top=1.e-8, nlayer=100)

F = art.run(dtau, Tarr)

```

 

Transmission Spectrum :heavy_check_mark: 

Reflection Spectrum :heavy_check_mark: 

## Installation

```

pip install exojax

```

or

```

python setup.py install

```

Note on installation w/ GPU support

:books: You need to install CUDA, JAX w/ NVIDIA GPU support.

Visit [here](https://github.com/google/jax) for the installation of GPU supported JAX.

## References

[![paper](https://img.shields.io/badge/paper_I-ApJS_258_31_(2022)-orange)](https://iopscience.iop.org/article/10.3847/1538-4365/ac3b4d) 

- Paper I: Kawahara, Kawashima, Masuda, Crossfield, Pannier, van den Bekerom, [ApJS 258, 31 (2022)](https://iopscience.iop.org/article/10.3847/1538-4365/ac3b4d)

## License

🐈 Copyright 2020-2024 ExoJAX contributors. ExoJAX is publicly available under the MIT license.