Multipurpose self-configuration of programmable photonic circuits

Programmable photonic latch memory

Significant advancements in integrated photonics have enabled high-speed and energy efficient systems for various applications, from data communications and high-performance computing to medical diagnosis, sensing, and ranging. However, data storage in these systems has been dominated by electronic memories that in addition to signal conversion between optical and electrical domains, necessitates conversion between analog to digital domains and electrical data movement between processor and memory that reduce the speed and energy efficiency. To date, scalable optical memory with optical control has remained an open problem. Here, we report an integrated photonic set-reset latch as a fundamental optical static memory unit based on universal optical logic gates. As a proof of concept, experimental implementation of the universal logic gates and realistic simulation of the latch are demonstrated on a programmable silicon photonic platform. Optical set, reset, and complementary outputs, scalability to a large number of memory units via the independent latch supply light, and compatibility with wavelength division multiplexing scheme and different photonic platforms enable more efficient and lower latency optical processing systems.

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.

Silicon photonic MEMS switches based on split waveguide crossings

The continuous push for high-performance photonic switches is one of the most crucial premises for the sustainable scaling of programmable and reconfigurable photonic circuits for a wide spectrum of applications. Conventional optical switches rely on the perturbative mechanisms of mode coupling or mode interference, resulting in inherent bottlenecks in their switching performance concerning size, power consumption and bandwidth. Here we propose and realize a silicon photonic 2×2 elementary switch based on a split waveguide crossing (SWX) consisting of two halves. The propagation direction of the incident light is manipulated to implement the OFF/ON states by splitting/combining the two halves of the SWX, showing excellent performance with low excess loss and low crosstalk over an ultrawide bandwidth. Both elementary switch and a 64×64 switch array based on Benes topology are fabricated and characterized, demonstrating great potential for practical scenarios such as photonic interconnect/routing, Lidar and spectroscopy, photonic computing, as well as microwave photonics.

Agile manipulation of the time-frequency distribution of high-speed electromagnetic waves

Controlling the temporal evolution of an electromagnetic (EM) wave's frequency components, the so-called time-frequency (TF) distribution, in a versatile and real-time fashion remains very challenging, especially at the high speeds (> GHz regime) required in contemporary communication, imaging, and sensing applications. We propose a general framework for manipulating the TF properties of high-speed EM waves. Specifically, the TF distribution is continuously mapped along the time domain through phase-only processing, enabling its user-defined manipulation via widely-available temporal modulation techniques. The time-mapping operations can then be inverted to reconstruct the TF-processed signal. Using off-the-shelf telecommunication components, we demonstrate arbitrary control of the TF distribution of EM waves over a full bandwidth approaching 100 GHz with nanosecond-scale programmability and MHz-level frequency resolution. We further demonstrate applications for mitigating rapidly changing frequency interference terms and the direct synthesis of fast waveforms with customized TF distributions. The reported method represents a significant advancement in TF processing of EM waves and it fulfills the stringent requirements for many modern and emerging applications.

Information processing at the speed of light

In recent years, quantum computing has made significant strides, particularly in light-based technology. The introduction of quantum photonic chips has ushered in an era marked by scalability, stability, and cost-effectiveness, paving the way for innovative possibilities within compact footprints. This article provides a comprehensive exploration of photonic quantum computing, covering key aspects such as encoding information in photons, the merits of photonic qubits, and essential photonic device components including light squeezers, quantum light sources, interferometers, photodetectors, and waveguides. The article also examines photonic quantum communication and internet, and its implications for secure systems, detailing implementations such as quantum key distribution and long-distance communication. Emerging trends in quantum communication and essential reconfigurable elements for advancing photonic quantum internet are discussed. The review further navigates the path towards establishing scalable and fault-tolerant photonic quantum computers, highlighting quantum computational advantages achieved using photons. Additionally, the discussion extends to programmable photonic circuits, integrated photonics and transformative applications. Lastly, the review addresses prospects, implications, and challenges in photonic quantum computing, offering valuable insights into current advancements and promising future directions in this technology.

High-fidelity and polarization-insensitive universal photonic processors fabricated by femtosecond laser writing

Universal photonic processors (UPPs) are fully programmable photonic integrated circuits that are key components in quantum photonics. With this work, we present a novel platform for the realization of low-loss, low-power, and high-fidelity UPPs based on femtosecond laser writing (FLW) and compatible with a large wavelength spectrum. In fact, we demonstrate different UPPs, tailored for operation at 785 nm and 1550 nm, providing similar high-level performances. Moreover, we show that standard calibration techniques applied to FLW-UPPs result in Haar random polarization-insensitive photonic transformations implemented with average amplitude fidelity as high as 0.9979 at 785 nm (0.9970 at 1550 nm), with the possibility of increasing the fidelity over 0.9990 thanks to novel optimization algorithms. Besides being the first demonstrations of polarization-insensitive UPPs, these devices show the highest level of control and reconfigurability ever reported for a FLW circuit. These qualities will be greatly beneficial to applications in quantum information processing.

Towards large-scale programmable silicon photonic chip for signal processing

Optical signal processing has been playing a crucial part as powerful engine for various information systems in the practical applications. In particular, achieving large-scale programmable chips for signal processing are highly desirable for high flexibility, low cost and powerful processing. Silicon photonics, which has been developed successfully in the past decade, provides a promising option due to its unique advantages. Here, recent progress of large-scale programmable silicon photonic chip for signal processing in microwave photonics, optical communications, optical computing, quantum photonics as well as dispersion controlling are reviewed. Particularly, we give a discussion about the realization of high-performance building-blocks, including ultra-low-loss silicon photonic waveguides, 2 × 2 Mach-Zehnder switches and microring resonator switches. The methods for configuring large-scale programmable silicon photonic chips are also discussed. The representative examples are summarized for the applications of beam steering, optical switching, optical computing, quantum photonic processing as well as optical dispersion controlling. Finally, we give an outlook for the challenges of further developing large-scale programmable silicon photonic chips.

Monolithic back-end-of-line integration of phase change materials into foundry-manufactured silicon photonics

Monolithic integration of novel materials without modifying the existing photonic component library is crucial to advancing heterogeneous silicon photonic integrated circuits. Here we show the introduction of a silicon nitride etch stop layer at select areas, coupled with low-loss oxide trench, enabling incorporation of functional materials without compromising foundry-verified device reliability. As an illustration, two distinct chalcogenide phase change materials (PCMs) with remarkable nonvolatile modulation capabilities, namely Sb2Se3 and Ge2Sb2Se4Te1, were monolithic back-end-of-line integrated, offering compact phase and intensity tuning units with zero-static power consumption. By employing these building blocks, the phase error of a push-pull Mach-Zehnder interferometer optical switch could be reduced with a 48% peak power consumption reduction. Mirco-ring filters with >5-bit wavelength selective intensity modulation and waveguide-based >7-bit intensity-modulation broadband attenuators could also be achieved. This foundry-compatible platform could open up the possibility of integrating other excellent optoelectronic materials into future silicon photonic process design kits.

General-purpose programmable photonic processor for advanced radiofrequency applications

A general-purpose photonic processor can be built integrating a silicon photonic programmable core in a technology stack comprising an electronic monitoring and controlling layer and a software layer for resource control and programming. This processor can leverage the unique properties of photonics in terms of ultra-high bandwidth, high-speed operation, and low power consumption while operating in a complementary and synergistic way with electronic processors. These features are key in applications such as next-generation 5/6 G wireless systems where reconfigurable filtering, frequency conversion, arbitrary waveform generation, and beamforming are currently provided by microwave photonic subsystems that cannot be scaled down. Here we report the first general-purpose programmable processor with the remarkable capability to implement all the required basic functionalities of a microwave photonic system by suitable programming of its resources. The processor is fabricated in silicon photonics and incorporates the full photonic/electronic and software stack.

Deep photonic network platform enabling arbitrary and broadband optical functionality

Expanding applications in optical communications, computing, and sensing continue to drive the need for high-performance integrated photonic components. Designing these on-chip systems with arbitrary functionality requires beyond what is possible with physical intuition, for which machine learning-based methods have recently become popular. However, computational demands for physically accurate device simulations present critical challenges, significantly limiting scalability and design flexibility of these methods. Here, we present a highly-scalable, physics-informed design platform for on-chip optical systems with arbitrary functionality, based on deep photonic networks of custom-designed Mach-Zehnder interferometers. Leveraging this platform, we demonstrate ultra-broadband power splitters and a spectral duplexer, each designed within two minutes. The devices exhibit state-of-the-art experimental performance with insertion losses below 0.66 dB, and 1-dB bandwidths exceeding 120 nm. This platform provides a tractable path towards systematic, large-scale photonic system design, enabling custom power, phase, and dispersion profiles for high-throughput communications, quantum information processing, and medical/biological sensing applications.

Analog spatiotemporal feature extraction for cognitive radio-frequency sensing with integrated photonics

Analog feature extraction (AFE) is an appealing strategy for low-latency and efficient cognitive sensing systems since key features are much sparser than the Nyquist-sampled data. However, applying AFE to broadband radio-frequency (RF) scenarios is challenging due to the bandwidth and programmability bottlenecks of analog electronic circuitry. Here, we introduce a photonics-based scheme that extracts spatiotemporal features from broadband RF signals in the analog domain. The feature extractor structure inspired by convolutional neural networks is implemented on integrated photonic circuits to process RF signals from multiple antennas, extracting valid features from both temporal and spatial dimensions. Because of the tunability of the photonic devices, the photonic spatiotemporal feature extractor is trainable, which enhances the validity of the extracted features. Moreover, a digital-analog-hybrid transfer learning method is proposed for the effective and low-cost training of the photonic feature extractor. To validate our scheme, we demonstrate a radar target recognition task with a 4-GHz instantaneous bandwidth. Experimental results indicate that the photonic analog feature extractor tackles broadband RF signals and reduces the sampling rate of analog-to-digital converters to 1/4 of the Nyquist sampling while maintaining a high target recognition accuracy of 97.5%. Our scheme offers a promising path for exploiting the AFE strategy in the realm of cognitive RF sensing, with the potential to contribute to the efficient signal processing involved in applications such as autonomous driving, robotics, and smart factories.

Programmable integrated photonics for topological Hamiltonians

A variety of topological Hamiltonians have been demonstrated in photonic platforms, leading to fundamental discoveries and enhanced robustness in applications such as lasing, sensing, and quantum technologies. To date, each topological photonic platform implements a specific type of Hamiltonian with inexistent or limited reconfigurability. Here, we propose and demonstrate different topological models by using the same reprogrammable integrated photonics platform, consisting of a hexagonal mesh of silicon Mach-Zehnder interferometers with phase shifters. We specifically demonstrate a one-dimensional Su-Schrieffer-Heeger Hamiltonian supporting a localized topological edge mode and a higher-order topological insulator based on a two-dimensional breathing Kagome Hamiltonian with three corner states. These results highlight a nearly universal platform for topological models that may fast-track research progress toward applications of topological photonics and other coupled systems.

A system-on-chip microwave photonic processor solves dynamic RF interference in real time with picosecond latency

Radio-frequency interference is a growing concern as wireless technology advances, with potentially life-threatening consequences like interference between radar altimeters and 5 G cellular networks. Mobile transceivers mix signals with varying ratios over time, posing challenges for conventional digital signal processing (DSP) due to its high latency. These challenges will worsen as future wireless technologies adopt higher carrier frequencies and data rates. However, conventional DSPs, already on the brink of their clock frequency limit, are expected to offer only marginal speed advancements. This paper introduces a photonic processor to address dynamic interference through blind source separation (BSS). Our system-on-chip processor employs a fully integrated photonic signal pathway in the analogue domain, enabling rapid demixing of received mixtures and recovering the signal-of-interest in under 15 picoseconds. This reduction in latency surpasses electronic counterparts by more than three orders of magnitude. To complement the photonic processor, electronic peripherals based on field-programmable gate array (FPGA) assess the effectiveness of demixing and continuously update demixing weights at a rate of up to 305 Hz. This compact setup features precise dithering weight control, impedance-controlled circuit board and optical fibre packaging, suitable for handheld and mobile scenarios. We experimentally demonstrate the processor's ability to suppress transmission errors and maintain signal-to-noise ratios in two scenarios, radar altimeters and mobile communications. This work pioneers the real-time adaptability of integrated silicon photonics, enabling online learning and weight adjustments, and showcasing practical operational applications for photonic processing.

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.

Fully reconfigurable MEMS-based second-order coupled-resonator optical waveguide (CROW) with ultra-low tuning energy

Integrated microring resonators are well suited for wavelength-filtering applications in optical signal processing, and cascaded microring resonators allow flexible filter design in coupled-resonator optical waveguide (CROW) configurations. However, the implementation of high-order cascaded microring resonators with high extinction ratios (ERs) remains challenging owing to stringent fabrication requirements and the need for precise resonator tunability. We present a fully integrated on-chip second-order CROW filter using silicon photonic microelectromechanical systems (MEMS) to adjust tunable directional couplers and a phase shifter using nanoscale mechanical out-of-plane waveguide displacement. The filter can be fully reconfigured with regard to both the ER and center wavelength. We experimentally demonstrated an ER exceeding 25 dB and continuous wavelength tuning across the full free spectral range of 0.123 nm for single microring resonator, and showed reconfigurability in second-order CROW by tuning the ER and resonant wavelength. The tuning energy for an individual silicon photonic MEMS phase shifter or tunable coupler is less than 22 pJ with sub-microwatt static power consumption, which is far better than conventional integrated phase shifters based on other physical modulation mechanisms.

Integrated Bragg grating filters based on silicon-Sb2Se3 with non-volatile bandgap engineering capability

Integrated optical filters show outstanding capability in integrated reconfigurable photonic applications, including wavelength division multiplexing (WDM), programmable photonic processors, and on-chip quantum photonic networks. Present schemes for reconfigurable filters either have a large footprint or suffer from high static power consumption, hindering the development of reconfigurable photonic integrated systems. Here, a reconfigurable hybrid Bragg grating filter is elaborately designed through a precise, modified coupling mode theory. It is also experimentally presented by integrating non-volatile phase change material (PCM) Sb2Se3 on silicon to realize compact, low-loss, and broadband engineering operations. The fabricated filter holds a compact footprint of 0.5 µm × 43.5 µm and maintains a low insertion loss of < 0.5 dB after multiple levels of engineering to achieve crystallization. The filter is able to switch from a low-loss transmission state to the Bragg reflection state, making it a favorable solution for large-scale reconfigurable photonic circuits. With a switching extinction ratio over 30 dB at 1504.85 nm, this hybrid filter breaks the tradeoff between insertion loss and tuning range. These results reveal its potential as a new candidate for a basic element in large-scale non-volatile reconfigurable systems.

Transferable learning on analog hardware

While analog neural network (NN) accelerators promise massive energy and time savings, an important challenge is to make them robust to static fabrication error. Present-day training methods for programmable photonic interferometer circuits, a leading analog NN platform, do not produce networks that perform well in the presence of static hardware errors. Moreover, existing hardware error correction techniques either require individual retraining of every analog NN (which is impractical in an edge setting with millions of devices), place stringent demands on component quality, or introduce hardware overhead. We solve all three problems by introducing one-time error-aware training techniques that produce robust NNs that match the performance of ideal hardware and can be exactly transferred to arbitrary highly faulty photonic NNs with hardware errors up to five times larger than present-day fabrication tolerances.

In-memory photonic dot-product engine with electrically programmable weight banks

Electronically reprogrammable photonic circuits based on phase-change chalcogenides present an avenue to resolve the von-Neumann bottleneck; however, implementation of such hybrid photonic-electronic processing has not achieved computational success. Here, we achieve this milestone by demonstrating an in-memory photonic-electronic dot-product engine, one that decouples electronic programming of phase-change materials (PCMs) and photonic computation. Specifically, we develop non-volatile electronically reprogrammable PCM memory cells with a record-high 4-bit weight encoding, the lowest energy consumption per unit modulation depth (1.7 nJ/dB) for Erase operation (crystallization), and a high switching contrast (158.5%) using non-resonant silicon-on-insulator waveguide microheater devices. This enables us to perform parallel multiplications for image processing with a superior contrast-to-noise ratio (≥87.36) that leads to an enhanced computing accuracy (standard deviation σ ≤ 0.007). An in-memory hybrid computing system is developed in hardware for convolutional processing for recognizing images from the MNIST database with inferencing accuracies of 86% and 87%.

Hardware Error Correction for MZI-Based Matrix Computation

With the rapid development of artificial intelligence, the electronic system has fallen short of providing the needed computation speed. It is believed that silicon-based optoelectronic computation may be a solution, where Mach-Zehnder interferometer (MZI)-based matrix computation is the key due to its advantages of simple implementation and easy integration on a silicon wafer, but one of the concerns is the precision of the MZI method in the actual computation. This paper will identify the main hardware error sources of MZI-based matrix computation, summarize the available hardware error correction methods from the perspective of the entire MZI meshes and a single MZI device, and propose a new architecture that will largely improve the precision of MZI-based matrix computation without increasing the size of the MZI's mesh, which may lead to a fast and accurate optoelectronic computing system.

A self-similar sine-cosine fractal architecture for multiport interferometers

Multiport interferometers based on integrated beamsplitter meshes have recently captured interest as a platform for many emerging technologies. In this paper, we present a novel architecture for multiport interferometers based on the sine-cosine fractal decomposition of a unitary matrix. Our architecture is unique in that it is self-similar, enabling the construction of modular multi-chiplet devices. Due to this modularity, our design enjoys improved resilience to hardware imperfections as compared to conventional multiport interferometers. Additionally, the structure of our circuit enables systematic truncation, which is key in reducing the hardware footprint of the chip as well as compute time in training optical neural networks, while maintaining full connectivity. Numerical simulations show that truncation of these meshes gives robust performance even under large fabrication errors. This design is a step forward in the construction of large-scale programmable photonics, removing a major hurdle in scaling up to practical machine learning and quantum computing applications.

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

Microwave photonics has adopted a number of important concepts and technologies over the recent pasts, including photonic integration, versatile programmability, and techniques for enhancing key radio frequency performance metrics such as the noise figure and the dynamic range. However, to date, these aspects have not been achieved simultaneously in a single circuit. Here, we report a multi-functional photonic integrated circuit that enables programmable filtering functions with record-high performance. We demonstrate reconfigurable filter functions with record-low noise figure and a RF notch filter with ultra-high dynamic range. We achieve this unique feature using versatile complex spectrum tailoring enabled by an all integrated modulation transformer and a double injection ring resonator as a multi-function optical filtering component. Our work breaks the conventional and fragmented approach of integration, functionality and performance that currently prevents the adoption of integrated MWP systems in real applications.

Ultrahigh-responsivity waveguide-coupled optical power monitor for Si photonic circuits operating at near-infrared wavelengths

A phototransistor is a promising candidate as an optical power monitor in Si photonic circuits since the internal gain of photocurrent enables high responsivity. However, state-of-the-art waveguide-coupled phototransistors suffer from a responsivity of lower than 10³A/W, which is insufficient for detecting very low power light. Here, we present a waveguide-coupled phototransistor operating at a 1.3 μm wavelength, which consists of an InGaAs ultrathin channel on a Si waveguide working as a gate electrode to increase the responsivity. The Si waveguide gate underneath the InGaAs ultrathin channel enables the effective control of transistor current without optical absorption by the gate metal. As a result, our phototransistor achieved the highest responsivity of approximately 10⁶ A/W among the waveguide-coupled phototransistors, allowing us to detect light of 621 fW propagating in the Si waveguide. The high responsivity and the reasonable response time of approximately 100 μs make our phototransistor promising as an effective optical power monitor in Si photonic circuits.

Chirality logic gates

The ever-growing demand for faster and more efficient data transfer and processing has brought optical computation strategies to the forefront of research in next-generation computing. Here, we report a universal computing approach with the chirality degree of freedom. By exploiting the crystal symmetry-enabled well-known chiral selection rules, we demonstrate the viability of the concept in bulk silica crystals and atomically thin semiconductors and create ultrafast (<100-fs) all-optical chirality logic gates (XNOR, NOR, AND, XOR, OR, and NAND) and a half adder. We also validate the unique advantages of chirality gates by realizing multiple gates with simultaneous operation in a single device and electrical control. Our first demonstrations of logic gates using chiral selection rules suggest that optical chirality could provide a powerful degree of freedom for future optical computing.

On-chip photonics and optoelectronics with a van der Waals material dielectric platform

During the last few decades, photonic integrated circuits have increased dramatically, facilitating many high-performance applications, such as on-chip sensing, data processing, and inter-chip communications. The currently dominating material platforms (i.e., silicon, silicon nitride, lithium niobate, and indium phosphide), which have exhibited great application successes, however, suffer from their own disadvantages, such as the indirect bandgap of silicon for efficient light emission, and the compatibility challenges of indium phosphide with the silicon industry. Here, we report a new dielectric platform using nanostructured bulk van der Waals materials. On-chip light propagation, emission, and detection are demonstrated by taking advantage of different van der Waals materials. Low-loss passive waveguides with MoS2 and on-chip light sources and photodetectors with InSe have been realised. Our proof-of-concept demonstration of passive and active on-chip photonic components endorses van der Waals materials for offering a new dielectric platform with a large material-selection degree of freedom and unique properties toward close-to-atomic scale manufacture of on-chip photonic and optoelectronic devices.

Thermo-optic phase shifters based on silicon-on-insulator platform: state-of-the-art and a review

Silicon photonic platforms offer relevance to large markets in many applications, such as optical phased arrays, photonic neural networks, programmable photonic integrated circuits, and quantum computation devices. As one of the basic tuning devices, the thermo-optic phase shifter (TOPS) plays an important role in all these applications. A TOPS with the merits of easy fabrication, low power consumption, small thermal time constant, low insertion loss, small footprint, and low crosstalk, is needed to improve the performance and lower the cost of the above applications. To meet these demands, various TOPS have been proposed and experimentally demonstrated on different foundry platforms In this paper, we review the state-of-the-art of TOPS, including metal heater, doped silicon, silicide, with silicon substrate undercut for heat insulation, folded waveguide structure, and multi-pass waveguide structure. We further compare these TOPSs and propose the directions of the future developments on TOPS.

Non-Volatile Programmable Ultra-Small Photonic Arbitrary Power Splitters

A series of reconfigurable compact photonic arbitrary power splitters are proposed based on the hybrid structure of silicon and Ge₂Sb₂Se₄Te₁ (GSST), which is a new kind of non-volatile optical phase change material (O-PCM) with low absorption. Our pixelated meta-hybrid has an extremely small photonic integrated circuit (PIC) footprint with a size comparable to that of the most advanced electronic integrated circuits (EICs). The power-split ratio can be reconfigured in a completely digital manner through the amorphous and crystalline switching of the GSST material, which only coated less than one-fifth of the pattern allocation area. The target power–split ratio between the output channels can be arbitrarily reconfigured digitally with high precision and in the valuable C-band (1530–1560 nm) based on the analysis of three-dimensional finite-difference time-domain. The 1 × 2, 1 × 3, and 1 × 4 splitting configurations were all investigated with a variety of power–split ratios for each case, and the corresponding true value tables of GSST distribution are given. These non-volatile hybrid photonic splitters offer the advantages of an extremely small footprint and non-volatile digital programmability, which are favorable to the truly optoelectronic fusion chip.

Ge Ion Implanted Photonic Devices and Annealing for Emerging Applications

Germanium (Ge) ion implantation into silicon waveguides will induce lattice defects in the silicon, which can eventually change the crystal silicon into amorphous silicon and increase the refractive index from 3.48 to 3.96. A subsequent annealing process, either by using an external laser or integrated thermal heaters can partially or completely remove those lattice defects and gradually change the amorphous silicon back into the crystalline form and, therefore, reduce the material’s refractive index. Utilising this change in optical properties, we successfully demonstrated various erasable photonic devices. Those devices can be used to implement a flexible and commercially viable wafer-scale testing method for a silicon photonics fabrication line, which is a key technology to reduce the cost and increase the yield in production. In addition, Ge ion implantation and annealing are also demonstrated to enable post-fabrication trimming of ring resonators and Mach–Zehnder interferometers and to implement nonvolatile programmable photonic circuits.

Programmable wavelength filter with double ring loaded MZI

We propose a novel filter circuit that incorporates a double ring resonator with a balanced Mach–Zehnder interferometer (MZI). The circuit has a response equivalent to a conventional ring loaded MZI filter, but with added flexibility in terms of configurability. The second-order filter can also be cascaded to realize higher-order filters. The circuit incorporates a two-stage input and output coupler to further reduce the effect of dispersion. A combination of local and global optimization strategies to program the filter, using tailored objective functions, have been tested in simulation and experiments. To our best knowledge, this is the first time a global optimization strategy is directly used in ARMA filter synthesis and simulation without any additional requirement. We further extend the optimization strategy into experiments and demonstrated its use in practical case for programmable filter circuits.

Architecture agnostic algorithm for reconfigurable optical interferometer programming

We develop the learning algorithm to build an architecture agnostic model of a reconfigurable optical interferometer. A procedure of programming a unitary transformation of optical modes of an interferometer either follows an analytical expression yielding a unitary matrix given a set of phase shifts or requires an optimization routine if an analytic decomposition does not exist. Our algorithm adopts a supervised learning strategy which matches a model of an interferometer to a training set populated by samples produced by a device under study. A simple optimization routine uses the trained model to output phase shifts corresponding to a desired unitary transformation of the interferometer with a given architecture. Our result provides the recipe for efficient tuning of interferometers even without rigorous analytical description which opens opportunity to explore new architectures of the interferometric circuits.

Silicon nitride programmable photonic processor with folded heaters

General-purpose programmable photonic processors rely on the large-scale integration of beamsplitters and reconfigurable phase shifters, distributed within unit cells or photonic gates. With their future evolution threatened by several hardware constrains, including the integration density that can be achieved with current mesh topologies, in this work, we present a unit cell topology design to increase the integration density of waveguide mesh arrangements based on folded Mach-Zehnder Interferometers. We report the design details of a 40-unit cell waveguide mesh integrated in a 11mm x 5.5 mm silicon nitride chip achieving, to the best of our knowledge, the highest integration density reported to date for a general-purpose photonic processor. The chip is electrically interfaced to a PCB and we report examples of reconfigurable optical beamsplitters, basic tunable microwave photonic filters with high peak rejection (40 dB approx.), as well as the dynamic interconnection and routing of 5G digitally modulated signals within the photonic mesh.