Partial coherence enhances parallelized photonic computing

Advancements in optical coherence control1–5 have unlocked many cutting-edge applications, including long-haul communication, light detection and ranging (LiDAR) and optical coherence tomography6–8. Prevailing wisdom suggests that using more coherent light sources leads to enhanced system performance and device functionalities9–11. Our study introduces a photonic convolutional processing system that takes advantage of partially coherent light to boost computing parallelism without substantially sacrificing accuracy, potentially enabling larger-size photonic tensor cores. The reduction of the degree of coherence optimizes bandwidth use in the photonic convolutional processing system. This breakthrough challenges the traditional belief that coherence is essential or even advantageous in integrated photonic accelerators, thereby enabling the use of light sources with less rigorous feedback control and thermal-management requirements for high-throughput photonic computing. Here we demonstrate such a system in two photonic platforms for computing applications: a photonic tensor core using phase-change-material photonic memories that delivers parallel convolution operations to classify the gaits of ten patients with Parkinson’s disease with 92.2% accuracy (92.7% theoretically) and a silicon photonic tensor core with embedded electro-absorption modulators (EAMs) to facilitate 0.108 tera operations per second (TOPS) convolutional processing for classifying the Modified National Institute of Standards and Technology (MNIST) handwritten digits dataset with 92.4% accuracy (95.0% theoretically)

Greatly amplified spontaneous emission of colloidal quantum dots mediated by a dielectric-plasmonic hybrid nanoantenna

Optical nanoantennas can efficiently harvest electromagnetic energy from nanoscale space and boost the local radiation to the far field. The dielectric-metal nanogap is a novel design that can help to overcome the core issue of optical loss in all-metal nanostructures while enabling photon density of states larger than that in all-dielectric counterparts. This article reports that a crystalline spherical silicon nanoparticle on metal film (SiNPoM) nanoantenna can largely enhance the spontaneous emission intensity of quantum dots by an area-normalized factor of 69 and the decay rate by 42-fold compared with quantum dots on glass. A high total quantum efficiency of over 80%, including ~20% for far-field radiation and ~60% for surface plasmon polaritons, is obtained in simulation. Thanks to not only the low optical loss in dielectric nanoparticles but also the appropriate gap thickness which weakens the non-radiative decay due to the quenching from metal. Mie resonant modes additionally provide the flexible control of far-field emission patterns. Such a simple optical nanoantenna can be combined with various nanoscale optical emitters and easily extended to form large area metasurfaces functioning as active regions in light-emitting devices in applications such as advanced display, wireless optical communication, and quantum technology

Probing the origin of highly-efficient third-harmonic generation in plasmonic nanogaps

Plasmonic structures can precisely localize electromagnetic energy to deep subwavelength regions resulting in significant field enhancement useful for efficient on-chip nonlinear generation. However, the origin of large nonlinear enhancements observed in plasmonic nanogap structures consisting of both dielectrics and metals is not fully understood. For the first time, here we probe the third harmonic generation (THG) from a variety of dielectric materials embedded in a nanogap plasmonic cavity. From comprehensive spectral analysis of the THG signal, we conclude that the nonlinear response results primarily from the dielectric spacer layer itself as opposed to the surrounding metal. We achieved a maximum enhancement factor of more than six orders of magnitude compared to a bare gold film, which represents a nonlinear conversion efficiency of 8.78 × 10−4%. We expect this new insight into the nonlinear response in ultrathin gaps between metals to be promising for on-chip nonlinear devices such as ultrafast optical switching and entangled photon sources

Giant longitudinal spin Hall effect for elliptically polarized light under surface plasmon resonance

We propose a novel and simple method for obtaining the giant longitudinal spin Hall effect (SHE) of the reflected light beam when the elliptically polarized light (instead of the linearly polarized light) at the telecommunication wavelength is obliquely incident on a prism-sodium interface excited by surface plasmon resonance. By introducing the spatially averaged Stokes parameter S3 for a non-uniformly polarized reflected light field, understanding the generation mechanism of the giant longitudinal SHE from a new perspective is realized. The giant longitudinal SHE under the elliptically polarized light reaches 60.28 mu m by the optimal parameter setup, and the spin splitting direction of the SHE can be switched by adjusting the amplitude ratio angle and phase difference of the incident elliptically polarized light. These findings open the way for the precise measurement of the ellipticity of the elliptically polarized light and the design of novel fiber-optic devices

Partial coherence enhances parallelized photonic computing

Advancements in optical coherence control have unlocked a plethora of cutting-edge applications, including long-haul communication, light detection and ranging, and optical coherence tomography. Prevailing wisdom suggests that using more coherent light sources leads to enhanced system performance and device functionalities. Our study introduces a photonic convolutional processing system that capitalizes on partially coherent light to boost computing parallelism without substantially sacrificing accuracy, potentially enabling larger-size photonic tensor cores. The reduction of the degree of coherence optimizes bandwidth utilization in the photonic convolutional processing system. This breakthrough challenges the traditional belief that coherence is essential or even advantageous in integrated photonic accelerators, thereby enabling the employment of light sources with less rigorous feedback control and thermal management requirements for high-throughput photonic computing. We demonstrate such a system in two photonic platforms for computing applications: a photonic tensor core using phase-change material photonic memories that delivers parallel convolution operations to classify gaits of ten Parkinson’s disease patients with a 92.2% accuracy (92.7% theoretically), and a silicon photonic tensor core with embedded electroabsorption modulators (EAM) to facilitate 0.108 tera operations per second (TOPS) convolutional processing for classifying MNIST handwritten digits dataset with a 92.4% accuracy (95.0% theoretically)