Tutorial#
- Getting Started
- Getting Started… with JAX
- Imports and Floating-Point Precision
- 1.
jax.numpyLooks and Feels Like NumPy - 2. Devices and Execution Backends
- 3. Building a Differentiable petitRADTRANS Model
- 4. JIT Compilation with
jax.jit - 5. Automatic Differentiation
- 6. Automatic Vectorization with
jax.vmap - 7. Gradients as a Function of Wavelength
- 8. Choosing the Execution Device Explicitly
- Why This Matters for Atmospheric Retrievals
- High-resolution spectra
- Including clouds
- Scattering for Emission Spectra
- Chemistry in petitRADTRANS
- Retrieval Examples
- Retrieval Parameter Reference
- Retrieval Samplers
- Retrievals: Basic Retrieval Tutorial
- Retrievals: Advanced features
- Retrievals with JAX
- Retrievals: JAX Emission Tutorial
- Retrievals: Using the Model Functions
- Retrievals: Dealing with multiple datasets
- Retrievals: Emission Spectra Retrieval
- Retrievals: Emission Spectra Retrieval with NumPyro NUTS
- Leave-One-Out Analysis with petitRADTRANS 4
- JWST retrieval workflow with
SpectralModel - High-resolution retrieval workflow with
SpectralModel - Retrievals: Exploring the built-in models
- Analysis tools
SpectralModel- Introduction
- Basic usage
- Calculating a transmission spectrum
- Calculating an emission spectrum
- Calculating a time-varying high-resolution spectrum
- Built-in functions
- Spectral modifications in details
- Tellurics, deformations, and noise
- Preparing ground-based high-resolution spectra
- Saving and loading
- Modifying the model functions and the spectral modification functions
- Useful tips
Planet: a convenient way to access planetary data- Rebinning opacities
- Utility functions