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The field of flat optics that uses nanostructured, so‐called metasurfaces, has seen remarkable progress over the last decade. Chalcogenide phase‐change materials (PCMs) offer a promising platform for realizing reconfigurable metasurfaces, as their optical properties can be reversibly tuned. Yet, demonstrations of phase‐change metalenses to date have employed material compositions such as Ge2Sb2Te5, which show high absorption in the visible to near‐IR wavelengths particularly in their crystalline state, limiting the applicability. Here, by using a low‐loss PCM Sb2Se3, for the first time, active polarization‐insensitive phase‐change metalenses at near‐IR wavelengths with comparable efficiencies in both material states are shown. An active metalens with a tunable focusing intensity of 95% and a focusing efficiency of 23% is demonstrated. A varifocal metalens is then demonstrated with a tunable focal length from 41 to 123 µm with comparable focusing efficiency (5.7% and 3%). The ultralow‐loss nature of the material introduces exciting new possibilities for optical communications, multi‐depth imaging, beam steering, optical routing, and holography. [ABSTRACT FROM AUTHOR]

Nonvolatile photonic memory cells are basic building blocks for neuromorphic hardware enabling the realization of all‐optical synapses and artificial neurons. These devices commonly exploit chalcogenide phase‐change materials, which are evanescently coupled to photonic waveguides, and provide fast write/erase speeds and large storage capacity. Here, we report for the first time the programming of a nonvolatile photonic memory cell based on Ag3In4Sb76Te17 (AIST) which is capable of mimicking biphasic synapses. We evaluate the underlying mechanism of biphasic behavior of AIST cells based on numerical simulations and correlate to experimental findings. Switching dynamics demonstrate enhanced performance with a post‐excitation dead time as short as 12.8 ns. Based on AIST double cells, we demonstrate reversible multilevel switching between 45 unique synaptic weights for long‐term depression (LTD) and long‐term potentiation (LTP). The observed biphasic programming and excellent switching performance render AIST‐based photonic memory cells promising for artificial neural networks and neuromorphic photonic computing hardware. [ABSTRACT FROM AUTHOR]

The ever‐increasing demands for data processing and storage will require seamless monolithic co‐integration of electronics and photonics. Phase‐change materials are uniquely suited to fulfill this function due to their dual electro‐optical sensitivity, nonvolatile retention properties, and fast switching dynamics. The extreme size disparity however between CMOS electronics and dielectric photonics inhibits the realization of efficient and compact electrically driven photonic switches, logic and routing elements. Here, the authors achieve an important milestone in harmonizing the two domains by demonstrating an electrically reconfigurable, ultra‐compact and nonvolatile memory that is optically accessible. The platform relies on localized heat, generated within a plasmonic structure; this uniquely allows for both optical and electrical readout signals to be interlocked with the material state of the PCM while still ensuring that the writing operation is electrically decoupled. Importantly, by miniaturization and effective thermal engineering, the authors achieve unprecedented energy efficiency, opening up a path towards low‐energy optoelectronic hardware for neuromorphic and in‐memory computing. [ABSTRACT FROM AUTHOR]