Machine learning for X-ray astronomical spectroscopy

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We use Simulation Based Inference to construct 34000 artificial spectra that are representative of observed Active Galactic Nuclei X-ray spectra with NASA's NuSTAR X-ray telescope. Based on previous literature results for these spectra, we train, validate, and test a new neural network model, ML-mytorus, which predicts best values for key physical parameters fast, automatically, and with very high degree of accuracy, including error estimates. We make the code publicly available, and set up a dedicated webpage for the community to upload any spectrum...