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Recent advances in nonlinear optics have revolutionized integrated photonics, providing on-chip solutions to a wide range of new applications. Currently, state of the art integrated nonlinear photonic devices are mainly based on dielectric material platforms, such as Si 3 N 4 and SiO 2 . While semiconductor materials feature much higher nonlinear coefficients and convenience in active integration, they have suffered from high waveguide losses that prevent the realization of efficient nonlinear processes on-chip. Here, we challenge this status quo and demonstrate a low loss AlGaAs-on-insulator platform with anomalous dispersion and quality ( Q ) factors beyond 1.5 × 10 6 . Such a high quality factor, combined with high nonlinear coefficient and small mode volume, enabled us to demonstrate a Kerr frequency comb threshold of only ∼36 µW in a resonator with a 1 THz free spectral range, ∼100 times lower compared to that in previous semiconductor platforms. Moreover, combs with broad spans (>250 nm) have been generated with a pump power of ∼300 µW, which is lower than the threshold power of state-of the-art dielectric micro combs. A soliton-step transition has also been observed for the first time in an AlGaAs resonator. Despite larger nonlinear coefficients, waveguide losses have prevented using semiconductors instead of dielectric materials for on-chip frequency-comb sources. By significantly reducing waveguide loss, ultra-low-threshold Kerr comb generation is demonstrated in a high- Q AlGaAs-on-insulator microresonator system.

Silicon nitride (SiN) waveguides with ultra-low optical loss enable integrated photonic applications including low noise, narrow linewidth lasers, chip-scale nonlinear photonics, and microwave photonics. Lasers are key components to SiN photonic integrated circuits (PICs), but are difficult to fully integrate with low-index SiN waveguides due to their large mismatch with the high-index III-V gain materials. The recent demonstration of multilayer heterogeneous integration provides a practical solution and enabled the first-generation of lasers fully integrated with SiN waveguides. However, a laser with high device yield and high output power at telecommunication wavelengths, where photonics applications are clustered, is still missing, hindered by large mode transition loss, non-optimized cavity design, and a complicated fabrication process. Here, we report high-performance lasers on SiN with tens of milliwatts output power through the SiN waveguide and sub-kHz fundamental linewidth, addressing all the aforementioned issues. We also show Hertz-level fundamental linewidth lasers are achievable with the developed integration techniques. These lasers, together with high- Q SiN resonators, mark a milestone towards a fully integrated low-noise silicon nitride photonics platform. This laser should find potential applications in LIDAR, microwave photonics and coherent optical communications. Achieving high output power and low noise integrated lasers is a major challenge. Here the authors experimentally demonstrate integrated lasers from a Si/SiN heterogeneous platform that shows Hertz-level linewidth, paving the way toward fully integrating low-noise silicon nitride photonics in volume using real devices for lasing.

The emergence of parallel convolution-operation technology has substantially powered the complexity and functionality of optical neural networks (ONN) by harnessing the dimension of optical wavelength. However, this advanced architecture faces remarkable challenges in high-level integration and on-chip operation. In this work, convolution based on time-wavelength plane stretching approach is implemented on a microcomb-driven chip-based photonic processing unit (PPU). To support the operation of this processing unit, we develop a dedicated control and operation protocol, leading to a record high weight precision of 9 bits. Moreover, the compact architecture and high data loading speed enable a preeminent photonic-core compute density of over 1 trillion of operations per second per square millimeter (TOPS mm −2 ). Two proof-of-concept experiments are demonstrated, including image edge detection and handwritten digit recognition, showing comparable processing capability compared to that of a digital computer. Due to the advanced performance and the great scalability, this parallel photonic processing unit can potentially revolutionize sophisticated artificial intelligence tasks including autonomous driving, video action recognition and image reconstruction. Optical neural networks face remarkable challenges in high-level integration and on-chip operation. In this work the authors enable optical convolution utilizing time-wavelength plane stretching approach on a microcomb-driven chip-based photonic processing unit.

The rising demand for high scanning accuracy and resolution in sensors for self-driving vehicles has led to the rapid development of parallelization in light detection and ranging (LiDAR) technologies. However, for the two major existing LiDAR categories—time-of-flight and frequency-modulated continuous wave—the light sources and measurement principles currently used for parallel detection face severe limitations from time- and frequency-domain congestion, leading to degraded measurement performance and increased system complexity. In this work we introduce a light source—the chaotic microcomb—to overcome this problem. This physical entropy light source exhibits naturally orthogonalized light channels that are immune to any congestion problem. Based on this microcomb state, we demonstrate a new type of LiDAR—parallel chaotic LiDAR—that is interference-free and has a greatly simplified system architecture. Our approach also enables the state-of-the-art ranging performance among parallel LiDARs: millimetre-level ranging accuracy and millimetre-per-second-level velocity resolution. Combining all of these desirable properties, this technology has the potential to reshape the entire LiDAR ecosystem.Current LiDAR approaches suffer from congestion issues, which affect measurement performance and increased system complexity. Now researchers demonstrate a chaotic microcomb that exhibits congestion-immune naturally orthogonalized light channels.

Optical chaos is vital for various applications such as private communication, encryption, anti-interference sensing, and reinforcement learning. Chaotic microcombs have emerged as promising sources for generating massive optical chaos. However, their inter-channel correlation behavior remains elusive, limiting their potential for on-chip parallel chaotic systems with high throughput. In this study, we present massively parallel chaos based on chaotic microcombs and high-nonlinearity AlGaAsOI platforms. We demonstrate the feasibility of generating parallel chaotic signals with inter-channel correlation <0.04 and a high random number generation rate of 3.84 Tbps. We further show the application of our approach by demonstrating a 15-channel integrated random bit generator with a 20 Gbps channel rate using silicon photonic chips. Additionally, we achieved a scalable decision-making accelerator for up to 256-armed bandit problems. Our work opens new possibilities for chaos-based information processing systems using integrated photonics, and potentially can revolutionize the current architecture of communication, sensing and computations. Previous chaos suffers from limited parallelism for high-speed systems. Here the authors harness chaotic microcombs as parallel chaos, demonstrating low inter-channel correlation and high throughput for random bit generation and optical decision making.

When employing bonded discrete element models (DEMs) to model rocks, a fundamental problem is how to determine the micro parameters to accurately simulate the rock strength characteristics. One promising way to improve calibration efficiency is to fully utilize the underlying relationship between DEM micro parameters and the macro strengths of rocks. This paper developed an analytical-optimal calibration framework to automatically determine DEM bond strength parameters. Extensive parametric analysis was first conducted to obtain the relationships between DEM micro-parameters and macro strengths. Bond tensile strength, cohesion and local internal friction angle were identified as independent variables for calibration. The automatic calibration method is divided into two stages. Firstly, the rough estimations of the bond tensile and cohesion were obtained by successively performing a direct tensile simulation test and a uniaxial compression simulation test, while the local internal friction angle was estimated by an empirical formula about the Hoek–Brown parameter m i . In the second stage, a finite difference gradient optimization method was used to further approximate the optimal bond parameters. A simplified gradient calculation is proposed based on the sensitivity analysis of macro strengths and DEM parameters. Adaptive moment estimation (Adam) was chosen as the iterative optimization algorithm to avoid the vanishing gradient problem. The advantage of the proposed calibration method is that the relationship between macro strengths and DEM parameters is fully exploited in both the initial estimation of DEM micro parameters and the optimization process. Moreover, the optimization method is a single-solution algorithm without the need to perform a large number of numerical simulations simultaneously. The proposed framework was demonstrated by calibrating the Bukit Timah granite, and a high calibration accuracy was achieved with a few iterations and a small number of simulation runs. Its applicability was also verified by the calibration results of various types of rocks.

Optical microresonators with high quality ( Q ) factors are essential to a wide range of integrated photonic devices. Steady efforts have been directed towards increasing microresonator Q factors across a variety of platforms. With success in reducing microfabrication process-related optical loss as a limitation of Q , the ultimate attainable Q , as determined solely by the constituent microresonator material absorption, has come into focus. Here, we report measurements of the material-limited Q factors in several photonic material platforms. High- Q microresonators are fabricated from thin films of SiO 2 , Si 3 N 4 , Al 0.2 Ga 0.8 As, and Ta 2 O 5 . By using cavity-enhanced photothermal spectroscopy, the material-limited Q is determined. The method simultaneously measures the Kerr nonlinearity in each material and reveals how material nonlinearity and ultimate Q vary in a complementary fashion across photonic materials. Besides guiding microresonator design and material development in four material platforms, the results help establish performance limits in future photonic integrated systems. Optical absorption and nonlinear index are important performance drivers in devices like microcombs. Here the authors use resonance-enhanced nonlinear spectroscopy to characterize absorption limits and nonlinear index for some integrated photonic materials.

Quantum fluctuations disrupt the cyclic motions of dissipative Kerr solitons (DKSs) in nonlinear optical microresonators and consequently cause timing jitter of the emitted pulse trains. This problem is translated to the performance of several applications that employ DKSs as compact frequency comb sources. Recently, device manufacturing and noise reduction technologies have advanced to unveil the quantum properties of DKSs. Here we investigate the quantum decoherence of DKSs existing in normal-dispersion microresonators known as dark pulses. By virtue of the very large material nonlinearity, we directly observe the quantum decoherence of dark pulses in an AlGaAs-on-insulator microresonator, and the underlying dynamical processes are resolved by injecting stochastic photons into the microresonators. Moreover, phase correlation measurements show that the uniformity of comb spacing of quantum-limited dark pulses is better than 1.2 × 10 −16 and 2.5 × 10 −13 when normalized to the optical carrier frequencies and repetition frequencies, respectively. Comparing DKSs generated in different material platforms explicitly confirms the advantages of dark pulses over bright solitons in terms of quantum-limited coherence. Our work establishes a critical performance assessment of DKSs, providing guidelines for coherence engineering of chip-scale optical frequency combs. Authors report quantum decoherence of dissipative Kerr solitons in normal-dispersion microresonators, also known as dark pulses. They show the quantum decoherence of dark pulses and their potential advantages over bright solitons in an AlGaAs-on-insulator system.

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-22031-4

Tunable optical frequency combs offer a flexible solution for specific applications such as dual-comb spectroscopy, optical communications and microwave photonics, delivering improved precision, compatibility, and performance. However, previously, there has been a trade-off between reconfigurability and system simplicity in comb generation. Here, we present a fast-switched repetition rate frequency comb system that utilizes an electro-optic modulation time-lens technique with a high third-order nonlinear AlGaAsOI waveguide. Only one stage of modulator is used in the time-lens system which significantly reduces the complexity of the overall system. Our system allows for tuning of the center wavelength from 1542 nm to 1556 nm, as well as independent adjustment of the repetition rates from 18 GHz to 26.5 GHz, enabling fast-switching capabilities. Additionally, our system exhibits a high pump-to-comb conversion efficiency of up to 67.9%. It also demonstrates robustness to temperature changes and environmental instability. All the involved devices can be integrated onto a single chip, making this comb suitable for various applications.Tunable optical frequency combs are a flexible solution for applications in optics, but they are typically limited in reconfigurability or simplicity of the We agree to use the draft summary by the editor. setups. The authors present a frequency comb platform exploiting electrooptic modulation and nonlinear AlGaAs-on-insulator waveguide, ensuring reconfigurability and fast-switched repetition rates.