A supervised encoder-decoder network trained on simulated GRAND signals and realistic Gaussian noise recovers air-shower radio pulses from real detector noise with >95% efficiency at SNR≈4 and low false positives.
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Denoising radio pulses from air showers using machine-learning methods
A supervised encoder-decoder network trained on simulated GRAND signals and realistic Gaussian noise recovers air-shower radio pulses from real detector noise with >95% efficiency at SNR≈4 and low false positives.