Authors: Francesco Monticone, Andrea Alu
Source: FERMAT, Volume 28, Communication 4, Jul.-Aug., 2018
Abstract: Focusing and imaging are common operations, typically performed with lenses whose designs have been optimized for centuries. Conventional lenses suffer from fundamental limitations, however, such as limits in resolution and the inherent presence of optical aberrations, which stem from the well-established laws of reflection and refraction. In addition, systems based on conventional refractive optics are inherently limited to plane-to-plane imaging, and they cannot realize volume-to-volume imaging of three-dimensional regions of space. Recent advances in the area of metamaterials have shown potential ways to relax some of these limitations, yet several challenges still stand in the way of ideal imaging systems. Here, we introduce an imaging platform based on parity-time symmetric surfaces composed of a suitable combination of absorbing and emitting elements, time-reversed of each other, which enables enticing possibilities for focusing and imaging. We first derive a general recipe to obtain aberration-free volumetric imaging, showing the potential offered by parity-time symmetric systems in this context. A key aspect of this goal is the realization of an appropriate nonlocal parity-time symmetric response, which we achieve using multilayered metamaterials. Based on this scheme, we design a flat, transversely invariant lens based on a pair of parity-time symmetric, spatially dispersive metasurfaces that realizes robust all-angle negative refraction and volumetric imaging with reduced reflections and aberrations. Our findings offer interesting opportunities in the application of active electromagnetic systems, shed light on the practical implementation challenges of nonlocal active metamaterials, and open uncharted territory in the centuries-old field of imaging.
Index Terms: Metasurfaces, Metamaterials, Imaging, Negative Refraction, Spatial Dispersion
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Parity-time symmetric nonlocal metasurfaces: Focusing and imaging through balanced loss and gain