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Surpassing the diffraction limit via a vectorial Debye integral neural network
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DOI：10.1364/OE.555664.png)
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Abstract
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Breaking the diffraction limit has been a key challenge in optical engineering and super-resolution imaging. In this work, we utilize a vectorial Debye integral neural network to design sub-diffraction focusing fields for high-NA objectives. By training the polarization states of incident light, we flexibly achieve transitions from diffraction-limited focusing to superoscillatory regimes. Through parameter adjustments, we optimize focal spot size, energy efficiency, and sidelobe distribution, achieving a focus with a 0.367 lambda FWHM and enhanced energy utilization. This method significantly simplifies the design process and demonstrates great potential for advanced optical applications, including super-resolution imaging and 3D field engineering. (c) 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement
Keywords:
POLARIZATION
PHASE
FOCUS
Journal
IF:
3.3
Papers:
6.1W
Citations:
14.3W
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