We report direct-write and rewritable photonic circuits based on a low-loss phase change material (PCM) thin film Sb2Se3, in which complete end-to-end functional photonic circuits can be created by direct laser writing in one step without additional fabrication processes. The direct-write phase-change photonic circuit affords exceptional flexibility, allowing any part of the circuit to be erased and rewritten, facilitating rapid design modification and reprogramming. We demonstrate the versatility of this technique with various photonic circuits for diverse applications, including an optical interconnect fabric for reconfigurable networking, a photonic crossbar array as a tensor core for optical computing, and a tunable optical filter for optical signal processing. Our technique unlocks new paradigms for programmable photonic networking, computing, and signal processing. Moreover, the rewritable photonic circuits enable rapid prototyping and testing in a convenient and cost-efficient manner, eliminate the need for nanofabrication facilities, thus promote the proliferation of photonics research and education to a broader research community.
Optical metasurfaces are planar subwavelength nanoantenna arrays engineered to provide on-demand manipulation of light, thereby enabling ultra-compact flat optics with high performance, small form-factor and new functionalities. When integrated with active elements, the pixelated, thin device architecture further facilitates dynamic tuning of local and global optical responses. Leveraging advanced materials, designs and architectures, we develop novel active and passive meta-optics capable of transforming a variety of optical systems that are traditionally bulky and complicated.
We demonstrate a nonvolatile electrically programmable phase-change silicon photonic switch and phase shifter leveraging a monolayer graphene heater with record-high programming energy efficiency (8.7±1.4 aJ/nm3) and endurance (> 1,000 cycles).
Chalcogenide phase change materials (PCMs) are a class of alloys exhibiting gigantic optical property contrast upon structural transition from an amorphous to a crystalline state. The structural transition is also nonvolatile and does not require constant power supply to maintain its optical state. These unique behaviors qualify PCMs as a novel functional material enabling various on-chip and free-space re-programmable optical computing network architectures. Here we present monolithic integration of PCMs with integrated photonics and metasurface optics leveraging standard silicon foundry facilities, and the demonstration of electrically programmable photonic devices for on-chip optical routing, memory, and computing functions
The use of photonics in computing is a hot topic of interest, driven by the need for ever-increasing speed along with reduced power consumption. In existing computing architectures, photonic data storage would dramatically improve the performance by reducing latencies associated with electrical memories. At the same time, the rise of ‘big data’ and ‘deep learning’ is driving the quest for non-von Neumann and brain-inspired computing paradigms. To succeed in both aspects, we have demonstrated non-volatile multi-level photonic memory avoiding the von Neumann bottleneck in the existing computing paradigm and a photonic synapse resembling the biological synapses for brain-inspired computing using phase-change materials (Ge2Sb2Te5).
There exist several image-enhancement algorithms and tasks associated with imaging through turbulence that depend on defining the quality of an image. Examples include: “lucky imaging”, choosing the width of the inverse filter for image reconstruction, or stopping iterative deconvolution. We collected a number of image quality metrics found in the literature. Particularly interesting are the blind, “no-reference” metrics. We discuss ways of evaluating the usefulness of these metrics, even when a fully objective comparison is impossible because of the lack of a reference image. Metrics are tested on simulated and real data. Field data comes from experiments performed by the NATO SET 165 research group over a 7 km distance in Dayton, Ohio.
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