On-chip stimulated Brillouin scattering (SBS) has attracted extensive attention by introducing acousto-optic coupling interactions in all-optical signal processing systems. A series of chip-level applications such as Brillouin lasers, amplifiers, gyroscopes, filters, and nonreciprocal devices are realized based on Brillouin acousto-optic interaction. Here, we first introduce the fundamental principle of SBS in integrated photonics and a method for calculating Brillouin gain; then we illustrate the Brillouin effect on different material platforms with diverse applications. Finally, we make a concise conclusion and offer prospects on the future developments of on-chip SBS.

Inverse design focuses on identifying photonic structures to optimize the performance of photonic devices. Conventional scalar-based inverse design approaches are insufficient to design photonic devices of anisotropic materials such as lithium niobate (LN). To the best of our knowledge, this work proposes for the first time the inverse design method for anisotropic materials to optimize the structure of anisotropic-material based photonics devices. Specifically, the orientation dependent properties of anisotropic materials are included in the adjoint method, which provides a more precise prediction of light propagation within such materials. The proposed method is used to design ultra-compact wavelength division demultiplexers in the X-cut thin-film lithium niobate (TFLN) platform. By benchmarking the device performances of our method with those of classical scalar-based inverse design, we demonstrate that this method properly addresses the critical issue of material anisotropy in the X-cut TFLN platform. This proposed method fills the gap of inverse design of anisotropic materials based photonic devices, which finds prominent applications in TFLN platforms and other anisotropic-material based photonic integration platforms.

Photonic waveguides are the most fundamental element for photonic integrated circuits (PICs). Waveguide properties, such as propagation loss, modal areas, nonlinear coefficients, etc., directly determine the functionalities and performance of PICs. Recently, the emerging waveguides with bound states in the continuum (BICs) have opened new opportunities for PICs because of their special properties in resonance and radiation. Here, we review the recent progress of PICs composed of waveguides with BICs. First, fundamentals including background physics and design rules of a BIC-based waveguide will be introduced. Next, two types of BIC-based waveguide structures, including shallowly etched dielectric and hybrid waveguides, will be presented. Lastly, the challenges and opportunities of PICs with BICs will be discussed.

Mode-division multiplexing (MDM) technology enables high-bandwidth data transmission using orthogonal waveguide modes to construct parallel data streams. However, few demonstrations have been realized for generating and supporting high-order modes, mainly due to the intrinsic large material group-velocity dispersion (GVD), which make it challenging to selectively couple different-order spatial modes. We show the feasibility of on-chip GVD engineering by introducing a gradient-index metamaterial structure, which enables a robust and fully scalable MDM process. We demonstrate a record-high-order MDM device that supports TE₀–TE₁₅ modes simultaneously. 40-GBaud 16-ary quadrature amplitude modulation signals encoded on 16 mode channels contribute to a 2.162 Tbit / s net data rate, which is the highest data rate ever reported for an on-chip single-wavelength transmission. Our method can effectively expand the number of channels provided by MDM technology and promote the emerging research fields with great demand for parallelism, such as high-capacity optical interconnects, high-dimensional quantum communications, and large-scale neural networks.

Lithium niobate (LN) thin film has received much attention as an integrated photonic platform, due to its rich and great photoelectric characteristics, based on which various functional photonic devices, such as electro-optic modulators and nonlinear wavelength converters, have been demonstrated with impressive performance. As an important part of the integrated photonic system, the long-awaited laser and amplifier on the LN thin-film platform have made a series of breakthroughs and important progress recently. In this review paper, the research progress of lasers and amplifiers realized on lithium niobate thin film platforms is reviewed comprehensively. Specifically, the research progress on optically pumped lasers and amplifiers based on rare-earth ions doping of LN thin films is introduced. Some important parameters and existing limitations of the current development are discussed. In addition, the implementation scheme and research progress of electrically pumped lasers and amplifiers on LN thin-film platforms are summarized. The advantages and disadvantages of optically and electrically pumped LN thin film light sources are analyzed. Finally, the applications of LN thin film lasers and amplifiers and other on-chip functional devices are envisaged.

The combination of photonic integrated circuits and free-space metaoptics has the ability to untie technological knots that require advanced light manipulation due to their conjoined ability to achieve strong light–matter interaction via wave-guiding light over a long distance and shape them via large space-bandwidth product. Rapid prototyping of such a compound system requires component interchangeability. This represents a functional challenge in terms of fabrication and alignment of high-performance optical systems. Here, we report a flexible and interchangeable interface between a photonic integrated circuit and the free space using an array of low-loss metaoptics and demonstrate multifunctional beam shaping at a wavelength of 780 nm. We show that robust and high-fidelity operation of the designed optical functions can be achieved without prior precise characterization of the free-space input nor stringent alignment between the photonic integrated chip and the metaoptics chip. A diffraction limited spot of ∼3 μm for a hyperboloid metalens of numerical aperture 0.15 is achieved despite an input Gaussian elliptical deformation of up to 35% and misalignments of the components of up to 20 μm. A holographic image with a peak signal-to-noise ratio of >10 dB is also reported.

Light plays a central role in many applications. The key to unlocking its versatility lies in shaping it into the most appropriate form for the task at hand. Specifically tailored refractive index modifications, directly manufactured inside glass using a short pulsed laser, enable an almost arbitrary control of the light flow. However, the stringent requirements for quantitative knowledge of these modifications, as well as for fabrication precision, have so far prevented the fabrication of light-efficient aperiodic photonic volume elements (APVEs). Here, we present a powerful approach to the design and manufacturing of light-efficient APVEs. We optimize application-specific three-dimensional arrangements of hundreds of thousands of microscopic voxels and manufacture them using femtosecond direct laser writing inside millimeter-sized glass volumes. We experimentally achieve unprecedented diffraction efficiencies up to 80%, which is enabled by precise voxel characterization and adaptive optics during fabrication. We demonstrate APVEs with various functionalities, including a spatial mode converter and combined intensity shaping and wavelength multiplexing. Our elements can be freely designed and are efficient, compact, and robust. Our approach is not limited to borosilicate glass but is potentially extendable to other substrates, including birefringent and nonlinear materials, giving a preview of even broader functionalities, including polarization modulation and dynamic elements.

Estimation of physical quantities is at the core of most scientific research, and the use of quantum devices promises to enhance its performances. In real scenarios, it is fundamental to consider that resources are limited, and Bayesian adaptive estimation represents a powerful approach to efficiently allocate, during the estimation process, all the available resources. However, this framework relies on the precise knowledge of the system model, retrieved with a fine calibration, with results that are often computationally and experimentally demanding. We introduce a model-free and deep-learning-based approach to efficiently implement realistic Bayesian quantum metrology tasks accomplishing all the relevant challenges, without relying on any a priori knowledge of the system. To overcome this need, a neural network is trained directly on experimental data to learn the multiparameter Bayesian update. Then the system is set at its optimal working point through feedback provided by a reinforcement learning algorithm trained to reconstruct and enhance experiment heuristics of the investigated quantum sensor. Notably, we prove experimentally the achievement of higher estimation performances than standard methods, demonstrating the strength of the combination of these two black-box algorithms on an integrated photonic circuit. Our work represents an important step toward fully artificial intelligence-based quantum metrology.