Modern image sensors consist of systems of cascaded and bulky spherical optics for imaging with minimal aberrations. While these systems provide high-quality images, the improved functionality comes at the cost of increased size and weight. One route to reduce a system’s complexity is via computational imaging, in which much of the aberration correction and functionality of the optical hardware is shifted to post-processing in the software realm. Alternatively, a designer could miniaturize the optics by replacing them with diffractive optical elements, which mimic the functionality of refractive systems in a more compact form factor. Metasurfaces are an extreme example of such diffractive elements, in which quasiperiodic arrays of resonant subwavelength optical antennas impart spatially-varying changes on a wavefront. While separately both computational imaging and metasurfaces are promising avenues toward simplifying optical systems, a synergistic combination of these fields can further enhance system performance and facilitate advanced capabilities. In this talk, I will present a method to combine these two techniques to perform full-color imaging across the whole visible spectrum [1]. I will also discuss the use of computational techniques to design new metasurfaces [2], and using metasurfaces to perform computation on wavefronts, with applications in optical information processing and sensing.

Figure: (a) Hybrid cubic-quadratic metasurface; (b) Using the metasurface and computational imaging we demonstrated full-color imaging; (c) We developed inverse design methodologies for metasurfaces made of dielectric spheres.

References: [1] S. Colburn, A. Zhan, and A. Majumdar, “Metasurface optics for full-color computational imaging,” Science Advances, vol. 4, 2018. [2] A. Zhan, T. K. Fryett, S. Colburn, and A. Majumdar, “Inverse design of optical elements based on arrays of dielectric spheres,” Applied Optics, vol. 57, pp. 1437-1446, 2018/02/20 2018.