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Light’s ability to perform massive linear operations in parallel has recently inspired numerous demonstrations of optics-assisted artificial neural networks (ANN). However, a clear system-level advantage of optics over purely digital ANN has not yet been established. While linear operations can indeed be optically performed very efficiently, the lack of nonlinearity and signal regeneration require high-power, low-latency signal transduction between optics and electronics. Additionally, a large power is needed for lasers and photodetectors, which are often neglected in the calculation of the total energy consumption. Here, instead of mapping traditional digital operations to optics, we co-designed a hybrid optical-digital ANN, that operates on incoherent light, and is thus amenable to operations under ambient light. Keeping the latency and power constant between a purely digital ANN and a hybrid optical-digital ANN, we identified a low-power/latency regime, where an optical encoder provides higher classification accuracy than a purely digital ANN. We estimate our optical encoder enables ∼10 kHz rate operation of a hybrid ANN with a power of only 23 mW. However, in that regime, the overall classification accuracy is lower than what is achievable with higher power and latency. Our results indicate that optics can be advantageous over digital ANN in applications, where the overall performance of the ANN can be relaxed to prioritize lower power and latency.

Rapid advancements in autonomous systems and the Internet of Things have necessitated the development of compact and low-power image sensors to bridge the gap between the digital and physical world. To that end, sub-wavelength diffractive optics, commonly known as meta-optics, have garnered significant interest from the optics and photonics community due to their ability to achieve multiple functionalities within a small form factor. Despite years of research, however, the performance of meta-optics has often remained inferior compared to that of traditional refractive optics. In parallel, computational imaging techniques have emerged as a promising path to miniaturize optical systems, albeit often at the expense of higher power and latency. The lack of desired performance from either meta-optical or computational solutions has motivated researchers to look into a jointly optimized meta-optical–digital solution. While the meta-optical front end can preprocess the scene to reduce the computational load on the digital back end, the computational back end can in turn relax requirements on the meta-optics. In this Perspective, we provide an overview of this up-and-coming field, termed here as “software-defined meta-optics.” We highlight recent contributions that have advanced the current state of the art and point out directions toward which future research efforts should be directed to leverage the full potential of subwavelength photonic platforms in imaging and sensing applications. Synergistic technology transfer and commercialization of meta-optic technologies will pave the way for highly efficient, compact, and low-power imaging systems of the future.

Scalable programmable photonic integrated circuits (PICs) can potentially transform the current state of classical and quantum optical information processing. However, traditional means of programming, including thermo-optic, free carrier dispersion, and Pockels effect result in either large device footprints or high static energy consumptions, significantly limiting their scalability. While chalcogenide-based non-volatile phase-change materials (PCMs) could mitigate these problems thanks to their strong index modulation and zero static power consumption, they often suffer from large absorptive loss, low cyclability, and lack of multilevel operation. Here, we report a wide-bandgap PCM antimony sulfide (Sb₂S₃)-clad silicon photonic platform simultaneously achieving low loss (<1.0 dB), high extinction ratio (>10 dB), high cyclability (>1600 switching events), and 5-bit operation. These Sb₂S₃-based devices are programmed via on-chip silicon PIN diode heaters within sub-ms timescale, with a programming energy density of$$\sim 10\,{fJ}/n{m}^{3}$$$~10fJ/n{m}^3$. Remarkably, Sb₂S₃is programmed into fine intermediate states by applying multiple identical pulses, providing controllable multilevel operations. Through dynamic pulse control, we achieve 5-bit (32 levels) operations, rendering 0.50 ± 0.16 dB per step. Using this multilevel behavior, we further trim random phase error in a balanced Mach-Zehnder interferometer.

Programmable photonics play a crucial role in many emerging applications, from optical accelerators for machine learning to quantum information technologies. Conventionally, photonic systems are tuned by mechanisms such as the thermo-optic effect, free carrier dispersion, the electro-optic effect, or micro-mechanical movement. Although these physical effects allow either fast (>100 GHz) or large contrast (>60 dB) switching, their high static power consumption is not optimal for programmability, which requires only infrequent switching and has a long static time. Non-volatile materials, such as phase-change materials, ferroelectrics, vanadium dioxide, and memristive metal oxide materials, can offer an ideal solution thanks to their reversible switching and non-volatile behavior, enabling a truly “set-and-forget” programmable unit with no static power consumption. In recent years, we have indeed witnessed the fast adoption of non-volatile materials in programmable photonic systems, including photonic integrated circuits and free-space meta-optics. Here, we review the recent progress in the field of programmable photonics, based on non-volatile materials. We first discuss the material’s properties, operating mechanisms, and then their potential applications in programmable photonics. Finally, we provide an outlook for future research directions. The review serves as a reference for choosing the ideal material system to realize non-volatile operation for various photonic applications.

Silicon photonics has evolved from lab research to commercial products in the past decade as it plays an increasingly crucial role in data communication for next‐generation data centers and high‐performance computing. Recently, programmable silicon photonics has also found new applications in quantum and classical information processing. A key component of programmable silicon photonic integrated circuits (PICs) is the phase shifter, traditionally realized via thermo‐optic or free‐carrier effects that are weak, volatile, and power hungry. A non‐volatile phase shifter can circumvent these limitations by requiring zero power to maintain the switched phases. Previously non‐volatile phase modulation is achieved via phase‐change or ferroelectric materials, but the switching energy remains high (pico to nano joules) and the speed is slow (micro to milliseconds). Here, a non‐volatile III‐V‐on‐silicon photonic phase shifter based on a HfO₂memristor with sub‐pJ switching energy (≈400 fJ), representing over an order of magnitude improvement in energy efficiency compared to the state of the art, is reported. The non‐volatile phase shifter can be switched reversibly using a single 100 ns pulse and exhibits excellent endurance over 800 cycles. This technology can enable future energy‐efficient programmable PICs for data centers, optical neural networks, and quantum information processing.

Foveated imaging provides a better tradeoff between situational awareness (field of view) and resolution, and is critical in long wavelength infrared regimes because of the size, weight, power, and cost of thermal sensors. We demonstrate computational foveated imaging by exploiting the ability of a meta-optical frontend to discriminate between different polarization states and a computational backend to reconstruct the captured image/video. The frontend is a three-element optic: the first element, which we call the “foveal” element, is a metalens that focuses s-polarized light at a distance off₁without affecting the p-polarized light; the second element, which we call the “perifovea” element, is another metalens that focuses p-polarized light at a distance off₂without affecting thes-polarized light. The third element is a freely rotating polarizer that dynamically changes the mixing ratios between the two polarization states. Both the foveal element (focal length=150mm; diameter=75mm) and the perifoveal element (focal length=25mm; diameter=25mm) were fabricated as polarization-sensitive, all-silicon, meta surfaces resulting in a large-aperture, 1:6 foveal expansion, thermal imaging capability. A computational backend then utilizes a deep image prior to separate the resultant multiplexed image or video into a foveated image consisting of a high resolution center and a lower-resolution large field of view context. We build a prototype system and demonstrate 12 frames per second real-time, thermal, foveated image and video capture..

The wave nature of light sets a fundamental diffraction limit that challenges confinement and control of light in nanoscale structures with dimensions significantly smaller than the wavelength. Here, we study light–matter interaction in van der Waals MoS₂nanophotonic devices. We show that light can be coupled and guided in structures with dimensions as small as ≃λ/16 (∼60nm at 1000 nm excitation wavelength), while offering unprecedented optical field confinement. This deep subwavelength optical field confinement is achieved by exploiting strong lightwave dispersion in MoS₂. We further study the performance of a range of nanophotonic integrated devices via far- and near-field measurements. Our near-field measurements reveal detailed imaging of excitation, evolution, and guidance of fields in nanostructured MoS₂, whereas our far-field study examines light excitation and coupling to highly confined integrated photonics. Nanophotonics at a fraction of a wavelength demonstrated here could dramatically reduce the size of integrated photonic devices and opto-electronic circuits with potential applications in optical information science and engineering.

Sub-wavelength diffractive optics, commonly known as meta-optics, present a complex numerical simulation challenge, due to their multi-scale nature. The behavior of constituent sub-wavelength scatterers, or meta-atoms, needs to be modeled by full-wave electromagnetic simulations, whereas the whole meta-optical system can be modeled using ray/ Fourier optics. Most simulation techniques for large-scale meta-optics rely on the local phase approximation (LPA), where the coupling between dissimilar meta-atoms is neglected. Here we introduce a physics-informed neural network, coupled with the overlapping boundary method, which can efficiently model the meta-optics while still incorporating all of the coupling between meta-atoms. We demonstrate the efficacy of our technique by designing 1mm aperture cylindrical meta-lenses exhibiting higher efficiency than the ones designed under LPA. We experimentally validated the maximum intensity improvement (up to 53%) of the inverse-designed meta-lens. Our reported method can design large aperture ( ~ 10⁴ − 10⁵λ) meta-optics in a reasonable time (approximately 15 minutes on a graphics processing unit) without relying on the LPA.

Excitons, bound electron–hole pairs, in two-dimensional hybrid organic inorganic perovskites (2D HOIPs) are capable of forming hybrid light-matter states known as exciton-polaritons (E–Ps) when the excitonic medium is confined in an optical cavity. In the case of 2D HOIPs, they can self-hybridize into E–Ps at specific thicknesses of the HOIP crystals that form a resonant optical cavity with the excitons. However, the fundamental properties of these self-hybridized E–Ps in 2D HOIPs, including their role in ultrafast energy and/or charge transfer at interfaces, remain unclear. Here, we demonstrate that >0.5 µm thick 2D HOIP crystals on Au substrates are capable of supporting multiple-orders of self-hybridized E–P modes. These E–Ps have high Q factors (>100) and modulate the optical dispersion for the crystal to enhance sub-gap absorption and emission. Through varying excitation energy and ultrafast measurements, we also confirm energy transfer from higher energy E–Ps to lower energy E–Ps. Finally, we also demonstrate that E–Ps are capable of charge transport and transfer at interfaces. Our findings provide new insights into charge and energy transfer in E–Ps opening new opportunities towards their manipulation for polaritonic devices.