Photonic Integrated Circuits Research Articles

Active plasmonic nanodevices: From basic principles to emerging applications

AbstractTunable plasmonics has shown a wide range of applications in (bio)chemical sensing, displays, actuators, photonic chips, biomedicine, etc. in the last 2 decades. This review focuses on their recent development from the device perspective, which involves the understanding of fundamental principles and specific applications with desired functionality and compatibility. We classify these active plasmonic devices based on the nature of their structures and working environment as colloidal‐based, chip‐based, and colloidal chip‐based to further elaborate their performance and functions. We also highlight recent progress on tunable surface‐enhanced Raman spectroscopy, metasurfaces, and chiroptics to show the emerging applications of tunable plasmonic systems. We conclude this review with a general perception of the research trend in this field and challenges for their practical applications.

Mid-infrared arrayed waveguide gratings using a quantum cascade laser gain medium as core material

Mid-infrared photonics is a widely researched field with several applications, such as chemical sensing and spectroscopy. The development of photonic integrated circuits for the mid-infrared can enable the reduction in device size, weight, and power (SWaP) consumption. This paper demonstrates arrayed waveguide gratings working in the mid-infrared regime (5–5.4 µm). Our devices are fabricated on an InP-based quantum cascade laser platform with the gain medium as the waveguide core. To minimize the propagation losses caused by free carrier absorption and intersubband absorption in the unbiased QCL structure, we exposed the photonic chips to proton implantation. The performance of three sets of AWGs with different etch depths was characterized. The lowest waveguide losses were measured to be 2 dB/cm. The best performing 7×1 AWG and 13×1 AWG designs featured insertion losses of −2dB and −2.5dB, respectively. This study showcases the feasibility of applying such a platform for easy integration with active components like lasers and photodetectors, paving the path for on-chip mid-infrared applications.

High-speed optical-waveguide integrated single-walled carbon nanotube bolometer

The rapid development of photonic integrated circuits (PICs) and their applications in various fields of science and technology requires the creation of easy-to-manufacture high-speed integrated detectors. In this work, we fabricated and studied planar waveguide-integrated bolometers based on a thin film of single-walled carbon nanotubes (SWCNTs) on the silicon nitride platform. This bolometer showed good internal responsivity and a high bandwidth >1 GHz. In-depth analysis allowed us to retrieve the main parameters of the SWCNT film that govern the bolometric response that can be difficult to measure directly. The results obtained show a promising prospect of using SWCNT bolometers for PIC applications.

Asymmetric Proton-Exchange-Enhanced Lithium Niobate and Silicon Low-Temperature Direct Bonding with an Ultrathin Heterogeneous Interface.

The integration of lithium niobate (LiNbO3 or LN) and silicon (Si) has emerged as a promising heterogeneous platform for microelectromechanical systems (MEMSs) and photonic integrated circuits (PICs). Particularly, the lithium niobate on silicon (LNOS) architecture leverages the superior piezo-optomechanical properties of LN, making it compatible with superconducting circuits and quantum systems. This opens an avenue for the development of advanced quantum sensors and processors. However, existing LN and Si bonding methods suffer from inherent limitations, such as low interfacial strength and the formation of thick, amorphous interlayers. In this work, we present an asymmetric surface activation strategy to address these challenges. By employing proton-exchange-enhanced chemical activation on the LN surface and oxygen plasma treatment on the Si side, we have achieved remarkable bonding strengths of up to 10 MPa at a moderate annealing temperature of 150 °C. Notably, the bonding mechanism in our approach differs from that in conventional diffusion-based processes. Here, the dehydration condensation of surface functional groups results in an exceptionally thin interfacial layer, less than 2 nm thick, without the presence of amorphous LN. This innovative fabrication method for LNOS demonstrates superior reliability, piezoelectric performance, thermal management capabilities, and optical transmission qualities, paving the way for cutting-edge photonic and quantum applications.

Ultra-compact thin-film-lithium-niobate photonic chip for dispersion compensation

Ultra-compact thin-film-lithium-niobate photonic chip for dispersion compensation

Tolerances of the alignment of fibers to photonic integrated circuits

This work presents the solutions to the alignment of two Gaussian beams representing two sides of the optical connection between a fiber and a photonic integrated circuit (PIC). The focus is to use these solutions to derive equations that allow for the straightforward calculation of alignment tolerances for displacement in all three directions, as well as two axes of rotations. These equations can be used to aid in the design of photonic packages by allowing the determination of precision necessary for fabrication of mechanical alignment features, in addition to packaging process development.

Hybrid III-V/Silicon Quantum Photonic Device Generating Broadband Entangled Photon Pairs

The demand for integrated photonic chips combining the generation and manipulation of quantum states of light is steadily increasing, driven by the need for compact and scalable platforms for quantum information technologies. While photonic circuits with diverse functionalities are being developed in different single material platforms, it has become crucial to realize hybrid photonic circuits that harness the advantages of multiple materials while mitigating their respective weaknesses, resulting in enhanced capabilities. Here, we demonstrate a hybrid III-V/silicon quantum photonic device combining the strong second-order nonlinearity and direct band gap of the III-V semiconductor platform with the high maturity and CMOS compatibility of the silicon photonic platform. Our device embeds the spontaneous parametric down-conversion (SPDC) of photon pairs into an AlGaAs source and their vertical routing to an adhesively bonded silicon-on-insulator circuitry, within an evanescent coupling scheme managing both polarization states. This enables the on-chip generation of broadband (>40 nm) telecom photons by type-0 and type-2 SPDC from the hybrid device, at room temperature and with internal pair generation rates exceeding 105s−1 for both types, while the pump beam is strongly rejected. Two-photon interference with 92% visibility (and up to 99% upon 5-nm spectral filtering) proves the high energy-time entanglement quality of the produced quantum state, thereby enabling a wide range of quantum information applications on chip, within a hybrid architecture compliant with electrical pumping and merging the assets of two mature and highly complementary platforms in view of out-of-the-lab deployment of quantum technologies. Published by the American Physical Society 2024

Anisotropic quantum transport in a programmable photonic topological insulator

Quantum transport in materials describes the behavior of particles at the quantum level. Topological materials exhibit nontrivial transport properties with topological invariants, leading to the emergence of protected states that are immune against disorders at the material boundaries. In many real-world materials, especially those with anisotropic crystal structures, the transport properties can vary significantly along different directions within the material bulk. Here, we experimentally observe counterintuitive quantum transport phenomena in anisotropic topological insulators with controllable anisotropy and disorder, implemented on a programmable topological photonic chip. We examine phase transition from the topological phase to the Anderson phase, between which a new quasi-diffusive phase emerges. Anisotropic topological transport demonstrates unconventional superior robustness in the bulk mode compared to the edge mode, in the presence of disorder and loss in realistic systems. Peculiar topological transport with sophisticated gradient anisotropy, emulating stretched topological materials, occurs at the gradient domain wall that can be reconfigured. Our findings provide fresh insights into the intricate interplay between anisotropy within the bulk and robustness at the boundary of topological materials, which could lead to advancements in the field of topological material science and the development of topological devices with tailored functionalities.

Tunable silicon integrated quantum light source with on-chip FSR-free filters.

In this work, we design and fabricate a telecom band quantum light source (QLS) on a silicon photonic chip, which integrates a piece of a long silicon waveguide as the nonlinear medium for spontaneous four-wave mixing (SFWM) and five narrow FSR-free bandpass filters based on a grating-assisted contra-directional coupler (GACDC). Two optical filtering functions of the silicon integrated QLS have been demonstrated. First, the QLS supports two tunable outputs of photon pair generations by four GACDC filters. A wavelength tunable range of 6 nm is demonstrated. Second, one GACDC bandpass filter is designed as an on-chip pump filter before the silicon waveguide. The performances of the QLSs with and without the on-chip pump filter are measured and compared. It shows that the on-chip pump filter has the effect to enhance the performance of the QLS by suppressing the Raman noise photons generated when a pump light propagated in optical fibers before it is injected into the chip. These results show that FSR-free filters would play important roles in developing silicon integrated QLSs.

16-channel photonic solver for optimization problems on a silicon chip

A programmable photonic solver for quadratic unconstrained binary optimization (QUBO) problems is demonstrated with a hybrid optoelectronic scheme, which consists of a photonic chip and an electronic driving board. The photonic chip is employed to perform the optical vector-matrix multiplication (OVMM) to calculate the cost function of the QUBO problem, while the electronic processor runs the heuristic algorithm to search for the optimal solution. Due to the parallel and low-latency propagation of lightwave, the calculation of the cost function can be accelerated. The photonic chip is fabricated on the silicon on insulator (SOI) substrate and integrates 16 high-speed electro-optic modulators, 88 thermo-optic phase shifters, and 16 balanced photodetectors. The computing speed of the photonic chip is 1.66 TFLOP/s. As a proof of principle, two randomly generated 16-dimensional QUBO problems are solved with high successful probabilities. These results present the potential of fast solving optimization problems with integrated photonic systems.

Ultrafast Laser-Fabricated Fluoride Glass Waveguides with Exceptionally High Positive Refractive Index Change for Mid-Infrared Integrated Optics

Ultrafast Laser-Fabricated Fluoride Glass Waveguides with Exceptionally High Positive Refractive Index Change for Mid-Infrared Integrated Optics

Demonstration of lossy linear transformations and two-photon interference on a photonic chip

Studying quantum correlations in the presence of loss is of critical importance for the physical modeling of real quantum systems. Here, we demonstrate the control of spatial correlations between entangled photons in a photonic chip, designed and modeled using the singular value decomposition approach. We show that engineered loss, using an auxiliary waveguide, allows one to invert the spatial statistics from bunching to antibunching. Furthermore, we study the photon statistics within the loss-emulating channel and observe photon coincidences, which may provide insights into the design of quantum photonic integrated chips. Published by the American Physical Society 2024

Two-dimensional non-Abelian Thouless pump

Non-Abelian Thouless pumps are periodically driven systems designed by the non-Abelian holonomy principle, in which quantized transport of degenerate eigenstates emerges, exhibiting noncommutative features such that the outcome depends on the pumping sequence. The study of non-Abelian Thouless pump is currently restricted to 1D systems, while extending it to higher-dimensional systems will not only provide effective means to probe non-Abelian physics in high-dimensional topological systems, but also expand the dimension and type of associated non-Abelian geometric phase matrix for potential applications. Here, we propose the design and experimental realization of 2D non-Abelian Thouless pumps on a photonic chip with 2D photonic waveguide arrays, where degenerate photonic modes are topologically pumped simultaneously along two real-space directions. We reveal the associated non-Abelian group and experimentally demonstrate the non-Abelian feature by measuring the pumping sequence dependent output. The proposed 2D non-Abelian Thouless pump shows promising applications for robust optical interconnections and optical computing.

Multimodal In-Sensor Computing System Using Integrated Silicon Photonic Convolutional Processor.

Photonic integrated circuits offer miniaturized solutions for multimodal spectroscopic sensory systems by leveraging the simultaneous interaction of light with temperature, chemicals, and biomolecules, among others. The multimodal spectroscopic sensory data is complex and has huge data volume with high redundancy, thus requiring high communication bandwidth associated with high communication power consumption to transfer the sensory data. To circumvent this high communication cost, the photonic sensor and processor are brought into intimacy and propose a photonic multimodal in-sensor computing system using an integrated silicon photonic convolutional processor. A microring resonator crossbar array is used as the photonic processor to implement convolutional operation with 5-bit accuracy, validated through image edge detection tasks. Further integrating the processor with a photonic spectroscopic sensor, the in situ processing of multimodal spectroscopic sensory data is demonstrated, achieving the classification of protein species of different types and concentrations at various temperatures. A classification accuracy of 97.58% across 45 different classes is achieved. The multimodal in-sensor computing system demonstrates the feasibility of integrating photonic processors and photonic sensors to enhance the data processing capability of photonic devices at the edge.

Nonvolatile reconfigurable polarization rotator at datacom wavelengths based on a Sb2Se3/Si waveguide

Silicon photonics has become a key platform for photonic integrated circuits (PICs) due to its high refractive index and compatibility with complementary metal-oxide-semiconductor manufacturing. However, the inherent birefringence in silicon waveguides requires efficient polarization management. Here, we report a reconfigurable polarization rotator (PR) using a Sb2Se3/Si waveguide operating at datacom wavelengths (1310 nm), providing nonvolatile switching with zero static power consumption. The polarization conversion relies on the interference of hybrid electric-magnetic (EH) modes, which can be reconfigured by changing the Sb2Se3 state between amorphous and crystalline. Our experimental device exhibits a polarization conversion efficiency (PCE) and a polarization extinction ratio (PER) as high as -0.08 dB and 17.65 dB, respectively, in a compact footprint of just 21 µm length. Therefore, the proposed reconfigurable PR offers a compact and energy-efficient solution for polarization management in silicon photonics, with potential applications in data communication networks and emerging applications benefiting from polarization information encodings, such as optical neural networks and quantum computing.

Multi-task photonic reservoir computing: wavelength division multiplexing for parallel computing with a silicon microring resonator

Nowadays, as the ever-increasing demand for more powerful computing resources continues, alternative advanced computing paradigms are under extensive investigation. Significant effort has been made to deviate from conventional Von Neumann architectures. In-memory computing has emerged in the field of electronics as a possible solution to the infamous bottleneck between memory and computing processors, which reduces the effective throughput of data. In photonics, novel schemes attempt to collocate the computing processor and memory in a single device. Photonics offers the flexibility of multiplexing streams of data not only spatially and in time, but also in frequency or, equivalently, in wavelength, which makes it highly suitable for parallel computing. Here, we numerically show the use of time and wavelength division multiplexing (WDM) to solve four independent tasks at the same time in a single photonic chip, serving as a proof of concept for our proposal. The system is a time-delay reservoir computing (TDRC) based on a microring resonator (MRR). The addressed tasks cover different applications: Time-series prediction, waveform signal classification, wireless channel equalization, and radar signal prediction. The system is also tested for simultaneous computing of up to 10 instances of the same task, exhibiting excellent performance. The footprint of the system is reduced by using time-division multiplexing of the nodes that act as the neurons of the studied neural network scheme. WDM is used for the parallelization of wavelength channels, each addressing a single task. By adjusting the input power and frequency of each optical channel, we can achieve levels of performance for each of the tasks that are comparable to those quoted in state-of-the-art reports focusing on single-task operation. We also quantify the memory capacity and nonlinearity of each parallelized RC and relate these properties to the performance of each task. Finally, we provide insight into the impact of the feedback mechanism on the performance of the system.

Silicon-based double fano resonances photonic integrated gas sensor

The telecommunication wavelengths are crucial for developing a photonic integrated circuit (PIC). The absorption fingerprints of many gases lie within these spectral ranges, offering the potential to create a miniaturized gas sensor for PIC. This work presents novel double Fano resonances within the telecommunication band, based on silicon metasurfaces for selective gas sensing applications. Our proposed design comprises periodically coupled nanodisk and nanobar resonators mounted on a quartz substrate. Fano resonances can be engineered across the range from λ = 1.52 μm to λ = 1.7 μm by adjusting various geometrical parameters. A double detection sensor of carbon monoxide (CO) at λ = 1.566 μm and nitrous oxide (N2O) at λ = 1.674 μm is developed. The sensor exhibits exceptional refractometric sensitivity to CO of 1,735 nm/RIU with an outstanding FOM of 11,570 at the first Fano resonance (FR1). In addition, the sensor shows a sensitivity to N2O of 194 nm/RIU accompanied by an FOM of 510 at the second Fano resonance (FR2). The structure reveals absorption losses of 6.3% for CO at the FR1, indicating the sensor selectivity to CO. The sensor is less selective at FR2 and limited to spectral shifts induced by each gas type. Our proposed design holds significant promise for the development of a highly sensitive double-sensing refractometric photonic integrated gas sensor.

Quantum Physical Unclonable Function Based on Multidimensional Fingerprint Features of Single Photon Emitters in Random AlN Nanocrystals

AbstractPhysical unclonable function (PUF) has emerged as a unique physical'fingerprint' that is inherently difficult to replicate. It shows tremendous application value in various hardware security areas such as identity authentication, chip anticounterfeiting, communication encryption, blockchain, etc. However, with the rapid development of 3D nanoprinting, classical PUFs constructed with disordered micro‐nanostructures face tremendous threats from physical cloning attacks. Herein, this study proposes and demonstrates the utilization of room‐temperature single‐photon emitters derived from atomic defects in randomly distributed pyramidal aluminum nitride (AlN) nanocrystals as a novel quantum PUF to resist physical cloning attacks. The fabrication of this quantum PUF on silicon (Si) wafers enables seamless integration with silicon photonic integrated circuits. The multidimensional fingerprint features of the single‐photon emitters are highly sensitive to the lattice parameters of the uneven AlN nanocrystals. Furthermore, each single photon emitter can work as a quantum random number generator to ensure the fundamental unpredictability of PUFs. The subatomic precision requirement coupled with unpredictable quantum emission behavior makes it practically impossible to attack the proposed quantum PUF, providing a promising solution for information security in the post‐quantum era.

First demonstration of lithium niobate photonic chip for dense wavelength-division multiplexing transmitters

First demonstration of lithium niobate photonic chip for dense wavelength-division multiplexing transmitters

Multi-particle quantum walks on 3D integrated photonic chip

Quantum walks provide a speed-up in computational power for various quantum algorithms and serve as inspiration for the construction of complex graph representations. Many pioneering works have been dedicated to expanding the experimental state space and the complexity of graphs. However, these experiments are mostly limited to small experimental scale, which do not reach a many-body level and fail to reflect the multi-particle quantum interference effects among non-adjacent modes. Here, we present a quantum walk with three photons on a two-dimensional triangular lattice, which is mapped to a 19 × 19 × 19 high-dimensional state space and constructs a complex graph with 6859 nodes and 45,486 edges. By utilizing the statistical signatures of the output combinations and incorporating machine learning techniques, we successfully validate the nonclassical properties of the experiment. Our implementation provides a paradigm for exponentially expanding the state space and graph complexity of quantum walks, paving the way for surmounting the classical regime in large-scale quantum simulations.