Ultrahigh dynamic range and low noise figure programmable integrated microwave photonic filter

Widely Tunable Photonic Filter Based on Equivalent Chirped Four-Phase-Shifted Sampled Bragg Gratings

We have developed an integrated dual-band photonic filter (PF) utilizing equivalent chirped four-phase-shifted sidewall-sampled Bragg gratings (4PS-SBG) on a silicon-on-insulator platform. Using the reconstruction equivalent-chirp technique, we designed linearly chirped 4PS Bragg gratings with two π-phase shifts (π-PSs) positioned at 1/3 and 2/3 of the grating cavity, introducing two passbands in the + first order channel. Leveraging the significant thermo-optic effect of silicon, dual-band tuning is achieved through integrated microheaters (MHs) on the chip surface. By varying the injection currents from 0 to 85 mA into the MHs, the device demonstrates continuous and wide-range optical frequency division performance, with the frequency interval between the two passbands adjustable from 52.1 to 439.5 GHz. Four notable frequency division setups at 100, 200, 300, and 400 GHz were demonstrated using a 100 GHz, 1535 nm semiconductor passive mode-locked laser as the light source.

Versatile parallel signal processing with a scalable silicon photonic chip

Silicon photonic signal processors promise a new generation of signal processing hardware with significant advancements in processing bandwidth, low power consumption, and minimal latency. Programmable silicon photonic signal processors, facilitated by tuning elements, can reduce hardware development cycles and costs. However, traditional programmable photonic signal processors based on optical switches face scalability and performance challenges due to control complexity and transmission losses. Here, we propose a scalable parallel signal processor on silicon for versatile applications by interleaving wavelength and temporal optical dimensions. Additionally, it incorporates ultra-low-loss waveguides and low-phase-error optical switch techniques, achieving an overall insertion loss of 10 dB. This design offers low loss, high scalability, and simplified control, enabling advanced functionalities such as accurate microwave reception, narrowband microwave photonic filtering, wide-bandwidth arbitrary waveform generation, and high-speed parallel optical computing without the need for tuning elements calibration. Our programmable parallel signal processor demonstrates advantages in both scale and performance, marking a significant advancement in large-scale, high-performance, multifunctional photonic systems.

Versatile photonic molecule switch in multimode microresonators

Harnessing optical supermode interaction to construct artificial photonic molecules has uncovered a series of fundamental optical phenomena analogous to atomic physics. Previously, the distinct energy levels and interactions in such two-level systems were provided by coupled microresonators. The reconfigurability is limited, as they often require delicate external field stimuli or mechanically altering the geometric factors. These highly specific approaches also limit potential applications. Here, we propose a versatile on-chip photonic molecule in a multimode microring, utilizing a flexible regulation methodology to dynamically control the existence and interaction strength of spatial modes. The transition between single/multi-mode states enables the "switched-off/on" functionality of the photonic molecule, supporting wider generalized applications scenarios. In particular, "switched-on" state shows flexible and multidimensional mode splitting control in aspects of both coupling strength and phase difference, equivalent to the a.c. and d.c. Stark effect. "Switched-off" state allows for perfect low-loss single-mode transition (Qi ~ 10 million) under an ultra-compact bend size (FSR ~ 115 GHz) in a foundry-based silicon microring. It breaks the stereotyped image of the FSR-Q factor trade-off, enabling ultra-wideband and high-resolution millimeter-wave photonic operations. Our demonstration provides a flexible and portable solution for the integrated photonic molecule system, extending its research scope from fundamental physics to real-world applications such as nonlinear optical signal processing and sixth-generation wireless communication.

Freeform direct-write and rewritable photonic integrated circuits in phase-change thin films

Photonic integrated circuits (PICs) with rapid prototyping and reprogramming capabilities promise revolutionary impacts on a plethora of photonic technologies. We report direct-write and rewritable photonic circuits on a low-loss phase-change material (PCM) thin film. Complete end-to-end PICs are directly laser-written in one step without additional fabrication processes, and any part of the circuit can be erased and rewritten, facilitating rapid design modification. We demonstrate the versatility of this technique for diverse applications, including an optical interconnect fabric for reconfigurable networking, a photonic crossbar array for optical computing, and a tunable optical filter for optical signal processing. By combining the programmability of the direct laser writing technique with PCM, our technique unlocks opportunities for programmable photonic networking, computing, and signal processing. Moreover, the rewritable photonic circuits enable rapid prototyping and testing in a convenient and cost-efficient manner, eliminate the need for nanofabrication facilities, and thus promote the proliferation of photonics research and education to a broader community.

Integrated microwave photonic notch filter using a heterogeneously integrated Brillouin and active-silicon photonic circuit

Microwave photonics (MWP) has unlocked a new paradigm for Radio Frequency (RF) signal processing by harnessing the inherent broadband and tunable nature of photonic components. Despite numerous efforts made to implement integrated MWP filters, a key RF processing functionality, it remains a long-standing challenge to achieve a fully integrated photonic circuit that can merge the megahertz-level spectral resolution required for RF applications with key electro-optic components. Here, we overcome this challenge by introducing a compact 5 mm × 5 mm chip-scale MWP filter with active E-O components, demonstrating 37 MHz spectral resolution. We achieved this device by heterogeneously integrating chalcogenide waveguides, which provide Brillouin gain, in a complementary metal-oxide-semiconductor (CMOS) foundry-manufactured silicon photonic chip containing integrated modulators and photodetectors. This work paves the way towards a new generation of compact, high-resolution RF photonic filters with wideband frequency tunability demanded by future applications, such as air and spaceborne RF communication payloads.

Deep Learning in the Ubiquitous Human-Computer Interactive 6G Era: Applications, Principles and Prospects

With the rapid development of enabling technologies like VR and AR, we human beings are on the threshold of the ubiquitous human-centric intelligence era. 6G is believed to be an indispensable cornerstone for efficient interaction between humans and computers in this promising vision. 6G is supposed to boost many human-centric applications due to its unprecedented performance improvements compared to 5G and before. However, challenges are still to be addressed, including but not limited to the following six aspects: Terahertz and millimeter-wave communication, low latency and high reliability, energy efficiency, security, efficient edge computing and heterogeneity of services. It is a daunting job to fit traditional analytical methods into these problems due to the complex architecture and highly dynamic features of ubiquitous interactive 6G systems. Fortunately, deep learning can circumvent the interpretability issue and train tremendous neural network parameters, which build mapping relationships from neural network input (status and specific requirements of a 6G application) to neural network output (settings to satisfy the requirements). Deep learning methods can be an efficient alternative to traditional analytical methods or even conquer unresolvable predicaments of analytical methods. We review representative deep learning solutions to the aforementioned six aspects separately and focus on the principles of fitting a deep learning method into specific 6G issues. Based on this review, our main contributions are highlighted as follows. (i) We investigate the representative works in a systematic view and find out some important issues like the vital role of deep reinforcement learning in the 6G context. (ii) We point out solutions to the lack of training data in 6G communication context. (iii) We reveal the relationship between traditional analytical methods and deep learning, in terms of 6G applications. (iv) We identify some frequently used efficient techniques in deep-learning-based 6G solutions. Finally, we point out open problems and future directions.

Tunable bandpass microwave photonic filter with largely reconfigurable bandwidth and steep shape factor based on cascaded silicon nitride micro-ring resonators

Bandpass microwave photonic filter (MPF) can be achieved based on the well-known phase to intensity conversion method by using phase modulation and single micro-ring resonator (MRR) notch filter. Since MRR could introduce residual phase in handling one optical sideband, the out-of-band radio frequency (RF) rejection ratio and the shape factor of the bandpass MPF are very limited. Here, by introducing another MRR to handle the other optical sideband, the residual phase can be greatly suppressed, thus the filter's performance can be greatly improved. The proposed bandpass MPF was both verified theoretically and experimentally. Compared with the single MRR, the out-of-band RF rejection ratio and the shape factor were improved by 20 dB and 1.67, respectively. Furthermore, the bandpass MPF's bandwidth is reconfigurable by adjusting the optical carrier's frequency or the two MRRs' amplitude coupling coefficients. The bandpass MPF's center frequency is also tunable by changing the resonant wavelengths of two MRRs in the opposite direction simultaneously. Experimentally, bandwidth reconfiguration from 0.38 GHz to 15.74 GHz, the shape factor optimization from 2 to 1.23, and frequency tuning from 4 GHz to 21.5 GHz were achieved. We believe that the proposed bandpass MPF has great potential for microwave photonic signal processing.