Tutorials

Below is a set of tutorials highlighting key functionalities of the toolkit. All tutorials can be downloaded as Jupyter notebooks. Please create an issue if you encounter any problems or unexpected behavior.

Tip

Detailed descriptions of all classes, functions, and parameters are available in the API documentation.

Fitting models and parameter inference

• Fitting atmospheric spectra – Inference of atmospheric parameters using model grids and Bayesian inference.

• Comparing with atmospheric spectra – Compare observed spectra and photometry to a full grid of model spectra.

• Fitting evolutionary tracks – Inference of bulk parameters using evolutionary tracks.

• Atmospheric retrieval with petitRADTRANS – Atmospheric retrieval with petitRADTRANS to constrain chemical abundances, P-T profile, and clouds.

• Emission line analysis – Analysis of hydrogen emission lines from accreting planets.

• Flux calibration – Flux calibration by modeling stellar magnitudes with synthetic spectra.

Atmospheric and evolutionary models

• Model spectra and synthetic photometry – Interpolate and visualize atmospheric model spectra.

• Comparing photometric fluxes and model spectra – Combine observational data and atmospheric spectra in a plot.

• Working with evolutionary models – Interpolate and visualize evolutionary tracks and isochrones.

Synthetic photometry, magnitudes, and fluxes

• Flux and magnitude conversion – Convert between fluxes and magnitudes.

• Synthetic photometry – Compute synthetic photometry from a spectrum.

Color and magnitude diagrams

• Color-magnitude diagram: broadband filters – Construct a broadband color–magnitude diagram that compares planets with field objects and model isochrones.

• Color-magnitude diagram: narrowband filters – Construct a narrowband color-magnitude diagram that includes synthetic photometry from a spectral library.

Spectral libraries

• Library with empirical spectra – Load and visualize a spectral library of stars and substellar objects.

Data of directly imaged planets

• Extracting data of directly imaged companions – Access observational data of directly imaged planets and brown dwarfs.

• Plotting companion properties – Extract and visualize the mass ratios of substellar companions.