Installation and References

last update: June 11st (2023) Hajime Kawahara

Linux, Windows WSL, Mac

At the very least, you can start using exojax through pypi.

pip install exojax

Alternatively, clone the code from github page and run

python setup.py install

If the older version of ExoJAX has already been installed, you need to remove all of the old modules (Otherwise, modules that have been deleted and no more exist in the current version remain). To do so, the following procedure is recommended:

python setup.py clean --all
python setup.py install

However, to take advantage of the power of JAX, you need to prepare a GPU environment (if you have). For this, jaxlib need to be linked.

You should check the cuda version of your environment as

nvcc -V

Here is an example of installation for jaxlib in linux system. See JAX installation page for the details.

pip install --upgrade pip
pip install --upgrade "jax[cuda11_pip]" -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html

Windows Anaconda

not supported yet.

References

🟢 ExoJAX Paper I: Kawahara, Kawashima, Masuda, Crossfield, Pannier, van den Bekerom (2021) accepted by ApJS: arXiv:2105.14782

Many techniques/databases are used in ExoJAX.

• JAX: Bradbury, J., Frostig, R., Hawkins, P., et al. 2018, JAX: composable transformations of Python+NumPy programs, JAX

• NumPyro: Phan, D., Pradhan, N., & Jankowiak, M. 2019, arXiv:1912.11554

• JAXopt: Blondel, M., Berthet, Q., Cuturi, M. et al. 2021 arXiv:2105.15183

• Vaex: Breddels and Veljanoski (2018) arXiv:https://arxiv.org/abs/1801.02638

• Algorithm 916: Zaghloul and Ali (2012) arXiv:1106.0151

• DIT: van den Bekerom and Pannier (2021)

• ExoMol: Tennyson et al. (2016)

• HITRAN/HITEMP

• VALD3

• RADIS, see below.

• Other many packages/algorithms. See arXiv:2105.14782 for the details.

Related Projects

• RADIS

ExoJAX draws a lot of inspiration from a fast line-by-line code for high-resolution infrared molecular spectra RADIS, including DIT, the use of Vaex, and so on.

Since version 1.2 we have been using a common molecular database I/O API in Radis.

• REACH

ExoJAX was originally developed to interpret data from a new high-dispersion coronagraphic capability at the Subaru telescope, the REACH project (SCExAO+IRD). REACH is supported by RESCEU, ABC and JSPS KAKENHI JP20H00170 (Kawahara). See also Lozi et al. (2018) for SCExAO, Kotani et al. (2018) for IRD, Jovanovic et al. (2017) for post-coronagraphic injection, and Kawahara et al. (2014) for high dispersion coronagraphy.