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Exoboots

A package to model the signal of hot exozodiacal dust in optical interferometric data using bootstrapping.

Short description

Highlights:

  • Model hot exozodiacal dust in interferometric data.
  • Analyze visibility amplitudes or squared visibilities loaded from an OIFITS file.
  • Account for correlation among spectral channels using Bootstrapping.
  • Explore different analytic models and combinations thereof: Uniform disk, Limb-darkend disk, Uniform emission over the field-of-view, 2d-Gaussian, ring, off-axis point source.
  • Automatic visualization and saving of results.

With this package, you can model the interferometric observables visibility amplitude or squared visibility that are loaded from an OIFITS file (Duvert et al.2017), the standard in optical interferometry.

Interferometric data is typically strongly correlated, especially among spectral channels. To account for this, Exoboots can explore different types of correlations, for instance by assuming data belonging to one interferometric baseline (one pair of telescopes) to be fully correlated. Exoboots capabilities are inspired by an IDL package that was developed to analyze observations with CHARA/FLUOR (Absil et al. 2006).

Installation instructions

I recommend installing Exoboots into a virtual environment, for instance using conda, mamba, or python venv. Exoboots requires Python in version 3.12.8 or later.

Install directly from GitHub

pip install git+https://github.com/tastuber/exoboots

Clone repository, then install

git clone https://github.com/tastuber/exoboots
cd exoboots
pip install .

Usage Example

Find an example Jupyter notebook reproducing published results in the examples folder.

Status

The code is in early development, but its capabilities have already been used in Ollmann et al. 2025.
If you would like to get involved or obtain more information, please contact me either via GitHub or email.

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Model hot exozodiacal dust in optical interferometric data using bootstrapping

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