Advancements in nanophotonics have raised the bar for optoelectronic devices, demanding ultra-compact size, fast speeds, high efficiency, and low energy consumption. Emerging materials hold the potential to meet these demands, enabling the creation of high-performing optoelectronic devices. We present our latest breakthroughs and demonstrate device prototypes made from various materials, pushing the boundaries of optoelectronic performance.

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Metalenses are emerging as an alternative to digital micromirror devices (DMDs), with the advantages of compactness and flexibility. The exploration of metalenses has ignited enthusiasm among optical engineers, positioning them as the forthcoming frontier in technology. In this paper, we advocate for the implementation of the phase-change material, Sb2Se3, capable of providing swift, reversible, non-volatile focusing and defocusing within the 1550 nm telecom spectrum. The lens, equipped with a robust ITO microheater, offers unparalleled functionality and constitutes a significant step toward dynamic metalenses that can be integrated with beamforming applications. After a meticulously conducted microfabrication process, we showcase a device capable of rapid tuning (0.1 MHz level) for metalens focusing and defocusing at C band communication, achieved by alternating the PCM state between the amorphous and crystalline states. The findings from the experiment show that the device has a high contrast ratio for switching of 28.7 dB.

Dynamic real-time optical processing has significant potential for accelerating specific tensor algebra. Here we present the first demonstration of simultaneous amplitude and phase modulation of an optical two-dimension signal in the Fourier plane of a thin lens. Two spatial light modulators (SLMs) arranged in a Michelson interferometer modulate the amplitude and the phase while being simultaneously in the focal plane of two Fourier lenses. The lenses frame an interferometer in a 4f-system enabling full modulation in the Fourier domain of a telescope. Main sources of phase noise and losses are discussed such as native to SLMs non-linear inter-pixel crosstalk, variability in modulation efficiency as a function of projected mask parameters, and Fresnel's optics limitations. Such a system is of extreme utility in rapidly progressing fields of optical computing, hardware acceleration, encryption, and machine learning, where neglecting phase modulation can lead to impractical bit-error rates.

In recent years, heterogeneous machine learning accelerators have become of significant interest to science, engineering, and industry. At the same time, the looming post-quantum encryption era instigates the demand for increased data security. From a hardware processing point of view, electronic computing hardware is challenged by electronic capacitive interconnect delay and associated energy consumption. In heterogeneous systems, such as electronic–photonic accelerators, parasitic domain crossings limit throughput and speed. With analog optical accelerators exhibiting a strong potential for high throughput (up to petaoperations per second) and operation efficiency, their ability to perform machine learning classification tasks on encrypted data has not been broadly recognized. This work is a significant step in that direction. Here, we present an optical hashing and compression scheme that is inspired by SWIFFT, a post-quantum hashing family of algorithms. High degree optical hardware-to-algorithm homomorphism allows one to optimally harvest the potential of free-space data processing: innate parallelism, low latency tensor by-element multiplication, and zero-energy Fourier transformation operations. The algorithm can provide several orders of magnitude increase in processing speed as compared to optical machine learning accelerators with non-compressed input. This is achieved by replacing slow, high-resolution CMOS cameras with ultra-fast and signal-triggered CMOS detector arrays. Additionally, information acquired in this way will require much lower transmission throughput, less in silico processing power, storage, and will be pre-hashed, facilitating optical information security. This concept has the potential to allow heterogeneous convolutional Fourier classifiers to approach the performance of their fully electronic counterparts and enables data classification on hashed data.

Phase-change materials offer a compelling platform for low power consumption active integrated optical circuits and meta optics, with their large optical index contrast (Δn, Δk) and nonvolatile phase transition1,2. Here, we demonstrate an electrically driven tunable meta lens in telecom range by exploring the full potential of a low absorption loss and high refractive index contrast PCM alloy, Sb2Se3, to realize non-volatile, reversible, fast focusing and defocusing meta lens in the 1550 telecom spectral range. With a fixed geometric design, the phase change material of Sb2Se3 switches the focusing length of a silicon photonic meta lens between two different values nonviolently. This unique functionality of the hybrid meta surface is attributed to the fact that the silicon’s refractive index is in the middle of the two convertible states in the optical phase change material. The transparency of Sb2Se3 in both states enables near phase-only meta surface structures. Our heterostructure architecture capitalizes over the integration of a robust resistive transparent microheater ITO (Indium Tin Oxide) decoupled from meta lens enabling good model to overlap with PCM meta pillars enables high transmission efficiency. The project be experimentally demonstrating an electrically reconfigurable phase-change meta lens capable of modulation an incident light beam into focusing of defocusing two different statures. This work represents a critical advance towards the development of integrable dynamic meta lens and their potential for beamforming applications.