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Simulation-based inference with neural posterior estimation applied to X-ray spectral fitting -- III Deriving exact posteriors with dimension reduction and importance sampling
Didier Barret, Simon Dupourqué
Simulation-based inference (SBI) with neural posterior estimation (NPE) provides rapid X-ray spectral fitting in both Gaussian and Poisson regimes by learning approximate parameter…
Simulation-based inference with neural posterior estimation applied to X-ray spectral fitting II -- High-resolution spectroscopy with the X-ray Integral Field Unit
Simon Dupourqué, Didier Barret
X-ray spectral fitting in high-energy astrophysics can be reliably accelerated using Machine Learning. In particular, Simulation-based Inference (SBI) produces accurate posterior d…
jaxspec : a fast and robust Python library for X-ray spectral fitting
Simon Dupourqué, Didier Barret, Camille M. Diez +2
Context. Inferring spectral parameters from X-ray data is one of the cornerstones of high-energy astrophysics, and is achieved using software stacks that have been developed over t…
Simulation-Based Inference with Neural Posterior Estimation applied to X-ray spectral fitting: Demonstration of working principles down to the Poisson regime
Didier Barret, Simon Dupourqué
Neural networks are being extensively used for modelling data, especially in the case where no likelihood can be formulated. Although in the case of X-ray spectral fitting, the lik…