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We present a diffractive terahertz sensor using a single-pixel detector to rapidly sense hidden defects within a target sample volume. Leveraging multiple spatially-engineered diffractive layers optimized via deep learning, this diffractive sensor can all-optically process the sample scattered waves and generate an output spectrum encoding information for indicating the presence/absence of hidden defects. We experimentally validated this framework using a single-pixel terahertz time-domain spectroscopy set-up and 3D-printed diffractive layers, successfully detecting unknown hidden defects within silicon samples. By circumventing raster scanning and digital image formation/reconstruction, this framework holds vast potential for various applications requiring high-throughput, non-destructive defect detection.
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