Lithium tantalate (LT) exhibits nonlinear optical properties that are comparable to those of lithium niobate (LN), yet the former surpasses the latter in several respects. These include an enhanced optical damage threshold, a wider transparency range, and lower birefringence. Consequently, LT is an excellent material for optical frequency conversion applications. In this study, we have devised a novel device based on thin-film lithium tantalate (TFLT) for the efficient generation of second-harmonic waves. The design employs modal phase-matching (MPM), which circumvents the intricacies of conventional poling techniques, and attains a normalised conversion efficiency of 120% W⁻¹cm⁻². In order to address the challenges presented by higher-order modes, a mode converter with an insertion loss of less than 0.1 dB has been developed, thereby ensuring the efficient utilisation of the second harmonic. This study not only demonstrates the potential of TFLT for high-performance SHG, but also promotes the development of integrated nonlinear TFLT platforms.

This work proposes an all-optical on-chip nonlinear activation function unit for multi-wavelength computing applications. Our proposed unit utilizes the unique properties of silicon, specifically the two-photon absorption and thermo-optic effects, to achieve nonlinearity essential for optical neural networks. We designed the parameters of the corresponding unit structure through simulation, fabricated and tested the actual structure experimentally, and obtained a CELU-like response curve. In practical classification tasks, we evaluated its performance in various classification tasks through numerical simulation and achieved a recognition accuracy of 98.84% on the MNIST dataset. This work addresses a critical gap in multi-wavelength systems and contributes to the development of more powerful and efficient optical computing platforms.

Tunable and low-power microcavities are essential for large-scale photonic integrated circuits. Thermal tuning, a convenient and stable tuning method, has been widely adopted in optical neural networks and quantum information processing. Recently, graphene thermal tuning has been demonstrated to be a power-efficient technique, as it does not require thick spacers to prevent light absorption. In this paper, a silicon-based on-chip Fano resonator with graphene nanoheaters is proposed and fabricated. This novel Fano structure is achieved by introducing a scattering block, and it can be easily fabricated in large quantities. Experimental results demonstrate that the resonator has the characteristics of a high quality factor (∼31,000) and low state-switching power (∼1 mW). The temporal responses of the microcavity exhibit qualified modulation speed with 9.8 μs rise time and 16.6 μs fall time. The thermal imaging and Raman spectroscopy of graphene at different biases were also measured to intuitively show that the tuning is derived from the joule heating effect of graphene. This work provides an alternative for future large-scale tunable and low-power-consumption optical networks, and has potential applications in optical filters and switches.

In today’s era where the demand for computational resources by large models is increasingly high, optical computing offers an alternative physical platform for computation. With its high parallelism and the maturation of integrated photonic technologies, optical computing is expected to further support the computational resources required by large models. For one-dimensional optical convolution accelerators, existing methods can fully utilize the working bandwidth of electro-optic modulators and the frequency resources of light sources. However, most convolution computations currently require the execution of two-dimensional matrix convolutions, and existing encoding schemes suffer a drop in terms of effective computations per second when performing two-dimensional matrix convolutions. In response to this, we propose a new encoding scheme that can fully utilize the computational resources of optical convolution accelerators. For convolution operations with a kernel size of $M\times M$, compared to existing encoding schemes, it can achieve an M-fold increase in effective computation rate. This implies that under the constraints of essentially the same hardware physical performance, adopting our newly proposed encoding scheme can achieve a significant improvement in computational performance. We construct an optical convolution acceleration system to demonstrate the principles of the new encoding.