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Abstract Phase‐sensitive integrated photonic devices are highly susceptible to minor manufacturing deviations, resulting in significant performance inconsistencies. This variability has limited the scalability and widespread adoption of these devices. Here, a major advancement is achieved through continuous‐wave (CW) visible light (405 and 520 nm) trimming of plasma‐enhanced chemical vapor deposition (PECVD) silicon‐rich nitride (SRN) waveguides. The demonstrated method achieves precise, bidirectional refractive index tuning with a single laser source in CMOS‐compatible SRN samples with refractive indices of 2.4 and 2.9 (measured at 1550 nm). By utilizing a cost‐effective setup for real‐time resonance tracking in micro‐ring resonators, the resonant wavelength shifts as fine as 10 pm are attained. Additionally, a record red shift of 49.1 nm and a substantial blue shift of 10.6 nm are demonstrated, corresponding to refractive index changes of approximately 0.11 and −2 × 10⁻². The blue and red shifts are both conclusively attributed to thermal annealing. These results highlight SRN's exceptional capability for permanent optical tuning, establishing a foundation for stable, precisely controlled performance in phase‐sensitive integrated photonic devices. 

This research leverages advanced monolithic silicon‐photonics integrated‐circuit manufacturing capabilities to realize system‐on‐chip photonic‐computing‐based linear‐algebra accelerators for a wide range of applications in artificial intelligence, machine learning, and multiple‐input multiple‐output wireless technology. With holistic codesign in both photonic and electronic domains, strategic electrical‐to‐optical signal conversion, a differential intensity‐modulation technique, and a dual rail‐to‐rail photodetection architecture, the monolithic photonic‐electronic test chip of a sign‐sign dot‐product accelerator achieves 8.92‐Gb/s/MAC computation throughput with 2.22‐pJ/b/MAC energy consumption for next‐generation large‐scale linear‐algebra computing hardware targeting higher than one TMAC/s/mm^2 computation density with only tens of fJ/MAC energy consumption. 

Physical reservoir computing (PRC) is a recently developed variant of neuromorphic computing, where the output from a nonlinear physical system is utilized to perform various machine learning tasks. In this work, we theoretically analyze the performance of a photonic waveguide mesh (WGM) with electro-optic phase shifters for monolithic-hybrid-photonic-electronic reservoir computing (MHPE RC), where the phase-to-intensity relations in the photonic circuit provide nonlinearity and high dimensionality, while the electronic circuit provides the input and feedback with tunable parameters. First, we numerically demonstrate the efficiency and performance superiority of a parallel architecture comprising fabricated WGM. Next, we present the Lyapunov filtered-minimal redundancy maximal relevance (Lf-mRMR) algorithm, which optimizes the electronic parameters of parallel WGMs by analyzing the Lyapunov exponent and the mutual information between the output of the corresponding WGMs and the required task. The Lf-mRMR algorithm is computationally less complex, substantially improves the performance of MHPE RC, and can tolerate fabrication errors. We present the selective parallel architecture for reservoir computing (SPARC), which, assisted by the Lf-mRMR algorithm, can achieve performance close to convolutional neural networks. Finally, we experimentally employ on-chip silicon photonics with thermo-optical phase shifters and external off-chip digital memory and control unit to validate the advantageous performance of Lf-mRMR-assisted RC. 

Polarization control and switchability are among the most unique features of “metasurfaces” as compared with diffractive optics technologies of the past. Here, we review how the polarization control afforded by the advent of present‐day metasurfaces compares to diffractive elements of previous decades, clarifying from a functional perspective what is new, and what is not. 

A low-power time-to-voltage converter (TVC) is composed of a reconfigurable current-mode integrator and a capacitive voltage holder specifically for random sampling-and-averaging (RSA) time-to-digital conversions (TDC) in time-correlated single-photon counting (TCSPC) systems. To accommodate the TVC circuit within each single-photon detection pixel for compact silicon-photonics integration, this paper exploits the Miller-impedance technique to demonstrate the leakage time-constant of the voltage holder being extended up to tens of milliseconds, which represents a more than 100× improvement in high-leakage 22-nm digital CMOS process technology, with only a 9-pF (36-µm × 36-µm) metal-finger hold capacitor and 120-µW power consumption. 

Panel-scale reconfigurable photonic interconnects on a glass substrate up to 500-mm × 500-mm or larger are envisioned by proposing a novel photonic switch fabric that enables all directional panel-edge-to-panel-edge reach without active repeaters while offering high communication bandwidth, planar-direction reconfigurability, low energy consumption, and compelling data bandwidth density for heterogeneous integration of an in-package artificial intelligence computing system on a photonic interposer exceeding thousands of centimeters square. The proposed approach focuses on reconfigurable photonic interconnects, which are integration-compatible with commercial processor chiplets and 3-D high-bandwidth memory stacks, to create a novel panel-scale heterogeneously integrated package enabled by high-capacity wavelength-division-multiplexing optical data links using advanced optical modulators, broadband photodetectors, novel optical crossbar switches with multilayer waveguides, and on-chip frequency comb sources. 

An energy/area-efficient low-cost broadband linearity enhancement technique using the hybrid of notch-filter and bandpass-filter micro-ring modulators (Hybrid-MRMs) is proposed to achieve higher than 3.01-dB improvement in spurious-free-dynamic-ranges with intermodulation distortions (dSFDRIMD) and 17.9-dB improvement in integral nonlinearity (dINLPP) over a conventional notch-filter MRM (NF-MRM) across a 4.8-dB extinction-ratio full-scale range based on rapid silicon-photonics fabrication results for the emerging applications of various analog and digital optical communication systems.