license: bsd-3-clause
tags:
- atmospheric-retrieval
- exoplanets
- simulation-based-inference
pretty_name: SBI_INAF
size_categories:
- 10K<n<100K
SBI_INAF
SBI_INAF is a dataset designed for Simulation-Based Inference (SBI) on atmospheric retrieval of exoplanets at a spectral resolution of approximately R = 40000, tailored for the GIANO-B echelle spectrograph. It contains transmission spectra (stellar and telluric free) together with their associated physical parameters, auxiliary metadata, normalization statistics, and predefined train/validation/test splits.
The dataset is built upon the Atmospheric Big Challenge (ABC) database, with major modifications to address the research goals of the research paper "Towards Scalable High-Resolution Atmospheric Retrieval of Exoplanets with Flow Matching" - M. Giordano Orsini et al., 2026.
The dataset is intended for supervised learning tasks involving parameter estimation from synthetic or simulated transmission spectra.
Dataset Structure
SBI_INAF_R1500/
├── AuxillaryTable.csv
├── FM_Parameter_Table.csv
├── h5s/
├── norm_params.pkl
├── QuartilesTable.csv
├── test_indices.npy
├── train_indices.npy
├── val_indices.npy
├── wavelengths.npy
├── widths.npy
File Descriptions
| File | Description |
|---|---|
h5s/ |
Collection of HDF5 files containing the spectra and associated sample information. |
FM_Parameter_Table.csv |
Physical parameters (forward-model parameters) associated with each simulated spectrum. These serve as prediction targets. |
AuxillaryTable.csv |
Additional metadata describing each sample (planetary system-related parameters). |
QuartilesTable.csv |
Summary statistics (quartiles) of selected parameters or features. Useful for exploratory data analysis. |
norm_params.pkl |
Stored normalization parameters used during preprocessing. |
wavelengths.npy |
Common wavelength grid for all spectra. |
widths.npy |
Spectral bin widths corresponding to the wavelength grid. |
train_indices.npy |
Indices defining the training split. |
val_indices.npy |
Indices defining the validation split. |
test_indices.npy |
Indices defining the held-out test split. |
Citation
If this dataset contributes to published work, please cite:
@article{GiordanoOrsini_2026,
author = {Giordano Orsini, Massimiliano and Ferone, Alessio and Inno, Laura and Maratea, Antonio and Casolaro, Angelo and Giacobbe, Paolo and Pino, Lorenzo and Bonomo, Aldo S.},
title = {Towards Scalable High-Resolution Atmospheric Retrieval of Exoplanets with Flow Matching},
year = 2026,
journal = {Journal of Computational Physics},
addendum = {(Submitted)},
}
License
Please refer to the accompanying repository or publication for licensing information.
Contact
For questions regarding the dataset, please contact the dataset maintainers or the authors of the accompanying publication.