Low angular separation point sources are vital in astronomy, such as the search for exoplanets. Traditional imaging is time-consuming, but we propose quantum-accelerated imaging (QAI) to reduce measurement time using an information-theoretic approach. QAI maximizes Fisher information per detected photon by adaptively learning optimal measurements from data. Using linear-projection instruments and single-photon detectors, we estimate the position, brightness, and number of unknown stars 10-100 times faster than direct imaging. QAI is scalable and applicable in high-speed imaging, fluorescence microscopy, and optical read-out of qubits beyond astronomy.
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