Physical Review Applied· 2026Q1· Review
Flat optics for analog computing: From fundamental mechanisms to advanced meta-processors
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- Q1SCImago
- 2026year
Short summary
Optical meta-processors using flat optics (metasurfaces) can perform mathematical operations for analog computing, offering a zero-power, speed-of-light alternative to strained electronic systems.
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Key points
- Metasurfaces enable ultra-compact, on-chip optical analog computing for mathematical operations.
- Key computing tasks demonstrated include spatial differentiation and edge detection.
- Meta-processors are evolving from static, linear systems to dynamic, nonlinear, and quantum-assisted platforms.
- Future advancements will leverage AI-driven inverse design and integration with optical neural networks.
AI-generated from the title and abstract; the full text is not read.
Abstract
As the explosive growth of visual data increasingly strains the latency and energy limits of conventional electronic computing, optical analog computing has re-emerged as a disruptive paradigm for zero-power, speed-of-light information processing. Propelled by the unprecedented wave-manipulation capabilities of optical metasurfaces, this field is undergoing a rapid transition from macroscopic physical optics to ultra-compact, on-chip meta-processors. This Review examines the fundamental mechanisms of metasurface-empowered optical computing spanning Fourier-domain, nonlocal spatial-domain, and interferometric architectures that perform mathematical operations, with a particular focus on spatial differentiation and edge detection as representative computing tasks. By emphasizing recent breakthroughs, we highlight the evolution of meta-processors from static, linear regimes to dynamically reconfigurable, nonlinear, and quantum-assisted multidimensional platforms. We also envision how the synergy of AI-driven inverse design and the integration of analog meta-front-ends with optical neural networks will synergistically revolutionize next-generation intelligent machine vision.
The authors' abstract, as published at the source. Physical Review Applied, 2026 · DOI ↗
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Field: Electronic, Optical and Magnetic Materials
Electronic, Optical and Magnetic MaterialsMaterials Science