| --- |
| 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 |
| |
| ```text |
| 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: |
|
|
| ```bibtex |
| @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. |
