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Data from: Large-scale compressive microscopy via diffractive multiplexing across a sensor array

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Jun 26, 2026 version files 121.39 GB

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Abstract

Microscopes face a trade-off between spatial resolution, field of view, and frame rate—improving one typically sacrifices the others because of the sensor’s limited spatiotemporal throughput. We propose a microscope that achieves snapshot gigapixel-scale imaging using a sensor array and a diffractive optical element (DOE). We increase spatiotemporal throughput in two ways. First, we capture data with an array of 48 sensors, yielding 48x more pixels than a single sensor. Second, we use point spread function (PSF) engineering and compressive sensing algorithms to fill in the missing information from the gaps surrounding individual sensors in the array, providing an additional >5.4x increase. The sensor array is modeled as a single large-format “super-sensor,” with erasures corresponding to the gaps between sensors. The array is placed at the output of a nearly 4f imaging system, and we design a DOE for the Fourier plane that generates a distributed PSF encoding information from the entire super-sensor area, including the gaps. We then computationally recover the large-scale image, assuming the object is sparse in some domain. Our calibration-free microscope achieves approximately 3 micrometers resolution over >5.2 cm2 field of view at up to 120 fps, for a total spatiotemporal throughput of 25.2 billion pixels per second. We demonstrate versatility in two modes: structural imaging via darkfield contrast and functional fluorescence imaging of calcium dynamics across dozens of freely moving C. elegans simultaneously.