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Learning Astrophysical Uncertainties in Dark Matter Direct Detection with Simulation-Based Inference
We present a proof-of-concept study of neural ratio estimation (NRE) - a simulation-based inference algorithm - applied to WIMP direct detection using the XENONnT experiment as an example. A binary classifier is trained on simulated parameter-observation pairs to approximate the likelihood ratio for
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