arXiv subjects

Jianqi Hu

Publications and source records attributed to Jianqi Hu.

At least 19 recordsLinked to original sources

arXiv2026

Programmable generation of optical skyrmions on a silicon photonic chip

Optical skyrmions, characterized by topologically stable and spatially varying polarization textures, show immense potential for robust optical communications and metrology. However, conventional methods for generating optical Stokes skyrmions rely on bulky free-space optics, strictly constraining both system miniaturization and dynamic reconfigurability. Here, we demonstrate the efficient and programmable generation of optical skyrmions and bimerons using a compact silicon photonic chip. By integrating a programmable Mach--Zehnder interferometer mesh with a multi-dimensional grating emitter, we dynamically control the amplitudes, phases, and polarizations of emitted fundamental and orbital angular momentum modes. This architecture allows on-demand electrical switching among a complete library of optical quasi-particle states, including N\'eel, Bloch, intermediate, and anti-type skyrmions and bimerons. Experimental full-Stokes polarimetry confirms high-fidelity polarization textures with near-unity skyrmion numbers. Our foundry-compatible platform translates complex topological light generation into simple voltage controls, paving the way for next-generation communication and sensing systems based on optical skyrmions.

physics.optics↗

arXiv2026

A fully integrated dispersion-managed femtosecond mode-locked laser

Femtosecond lasers underpin applications ranging from material processing to corneal surgery, while their regular pulse trains form optical frequency combs that have revolutionized timekeeping, spectroscopy, and metrology. On-chip optical frequency combs, such as Kerr microcombs, have enabled high-repetition-rate applications in optical communications and microwave photonics. However, integrated chip-scale sources operating at low repetition rates (100 MHz to 1 GHz), crucial for high peak intensities, remain elusive, as existing devices typically operate well beyond 10 GHz. Here, we demonstrate a self-starting, photonic integrated mode-locked laser based on a dispersion-managed architecture that accesses this regime. The laser combines erbium-implanted silicon nitride gain waveguides, integrated chirped Bragg gratings, and a semiconductor saturable absorber mirror to generate optical pulses with repetition rates from 0.5 to 1.2 GHz, pulse durations as short as 300 fs, and mode-locking thresholds down to 27.3 mW. The output forms a passively stable optical frequency comb with a comb-line drift below 1% of the repetition rate, surpassing the stability of commercial fiber lasers by two orders of magnitude. Leveraging this ultra-low threshold, we achieve complete hybrid integration by co-packaging the laser with a telecom-grade 980-nm III-V pump diode chip inside a compact photonic module. The resulting electrical-in/optical-out module delivers turnkey, stable mode-locked pulses, providing a compact, low-power, and vibration-insensitive foundry-compatible platform for field-deployable optical metrology and precision sensing.

physics.optics↗

arXiv2026

TRON: Trainable, architecture-reconfigurable random optical neural networks

Deep learning has triggered explosive growth in the demand for specialized hardware processors, thus motivating the development of scalable and reconfigurable computing substrates. Optical processors offer a fundamentally different computing paradigm, combining massive parallelism and ultrahigh bandwidth with the potential for substantial energy savings. However, progress has been constrained by the absence of scalable and reconfigurable architectures that can implement a broad class of network architectures. Here, we introduce TRON, a scalable and trainable optoelectronic deep optical neural network that exploits a multi-scattering medium and a DMD as a learnable, high-dimensional dense optical matrix multiplier, processing with fixed and tunable optical operations. We perform in-situ optimization of the optical parameters involved in the scattering process, together with automated neural architecture search (NAS) and optimization directly on optics. The experimental results demonstrate that in-situ NAS is essential to discover architectures that adapt to both the task and hardware constraints, establishing a viable path towards large-scale optical processors for next-generation machine learning and data-intensive computing.

physics.optics↗

arXiv2026

Self-Configuring Universal Multichannel and Multidimensional Integrated Photonic Processing Engine

Arbitrary manipulation of light across multiple physical dimensions is essential for harnessing its parallelism in fundamental research and advanced applications, such as optical interconnects, computing, imaging, sensing, and quantum networks. However, creating a universal device capable of arbitrary operations of multidimensional optical beams has been challenging, primarily due to their complex mutual interferences and dynamic transmission characteristics. In this study, we experimentally demonstrate a self-configuring integrated photonic processor designed for the arbitrary manipulations of multiple optical waves over their spatial and polarization dimensions. Despite the random nature of the input speckle, the photonic processor relies on an optical singular-value decomposition engine to sort all orthogonal input beams and implement arbitrary processing over both spatial and polarization dimensions precisely. Notably, the photonic processor can be self programmed in situ, enabling versatile functionalities such as beam shaping, optical switching, and reconfigurable optical add-drop multiplexing. Our findings advance the manipulation of multidimensional optical beams through a scalable, CMOS-compatible integration approach, paving the way for fully exploiting the parallelism of light in various applications.

physics.optics↗

arXiv2026

Training deep physical neural networks with local physical information bottleneck

Deep learning has revolutionized modern society but faces growing energy and latency constraints. Deep physical neural networks (PNNs) are interconnected computing systems that directly exploit analog dynamics for energy-efficient, ultrafast AI execution. Realizing this potential, however, requires universal training methods tailored to physical intricacies. Here, we present the Physical Information Bottleneck (PIB), a general and efficient framework that integrates information theory and local learning, enabling deep PNNs to learn under arbitrary physical dynamics. By allocating matrix-based information bottlenecks to each unit, we demonstrate supervised, unsupervised, and reinforcement learning across electronic memristive chips and optical computing platforms. PIB also adapts to severe hardware faults and allows for parallel training via geographically distributed resources. Bypassing auxiliary digital models and contrastive measurements, PIB recasts PNN training as an intrinsic, scalable information-theoretic process compatible with diverse physical substrates.

cs.LG↗

arXiv2025

High-pulse-energy integrated mode-locked lasers based on a Mamyshev oscillator

Ultrafast lasers have unlocked numerous advances across science and technology: they enable corneal surgery, reveal chemical reaction dynamics, and underpin optical atomic clocks. Over the past decades, extensive efforts have been devoted to developing photonic integrated circuit-based mode-locked lasers that are compact, scalable, and compatible with further on-chip functionalities. Yet, existing implementations fall short of pulse energies required for their subsequent uses in nonlinear applications. In this work, we demonstrate the first mode-locked laser that overcomes this limitation in low-loss erbium-doped silicon nitride photonic integrated circuits. The laser is based on the Mamyshev oscillator architecture, which employs alternating spectral filtering and self-phase modulation for mode-locking. It delivers a 176 MHz stream of pulses with nanojoule energy, comparable to fiber lasers and surpassing previous photonic integrated sources by more than two orders of magnitude. The output pulses exhibit excellent coherence, can be linearly compressed to 147 fs and directly drive a 1.5-octave-spanning supercontinuum in an integrated waveguide. Our work establishes a new generation of high-pulse-energy photonic integrated mode-locked lasers and paves the way for their widespread adoption.

physics.optics↗

arXiv2025

Integrated tunable green light source on silicon nitride

Integrated green light sources are essential for telecommunications and quantum applications, while the performance of current on-chip green light generation is still limited in power and tunability. In this work, we demonstrate green light generation in silicon nitride microresonators using photo-induced second-order nonlinearities, achieving up to 3.5 mW green power via second-harmonic generation and densely tunable over a 29 nm range. In addition, we report milliwatt-level all-optical poling (AOP) threshold, allowing for amplifier-free continuous-wave AOP. Furthermore, we demonstrate non-cascaded sum-frequency generation, leveraging the combination of AOP and simultaneous coherent frequency combs generation at 1 $\mu$m. Such comb-assisted AOP enables switching of the green light generation over an 11 nm range while maintaining the pump within a single resonance. The combination of such highly efficient photo-induced nonlinearity and multi-wavelength AOP enables the realization of low-threshold, high-power, widely-tunable on-chip green sources.

physics.optics↗

arXiv2025

Arrayed waveguide gratings in lithium tantalate integrated photonics

Arrayed Waveguide Gratings (AWGs) are widely used photonic components for splitting and combining different wavelengths of light. They play a key role in wavelength division multiplexing (WDM) systems by enabling efficient routing of multiple data channels over a single optical fiber and as a building block for various optical signal processing, computing, imaging, and spectroscopic applications. Recently, there has been growing interest in integrating AWGs in ferroelectric material platforms, as the platform simultaneously provide efficient electro-optic modulation capability and thus hold the promise for fully integrated WDM transmitters. To date, several demonstrations have been made in the X-cut thin-film lithium niobate ($\mathrm{LiNbO}_3$) platform, yet, the large anisotropy of $\mathrm{LiNbO}_3$ complicates the design and degrades the performance of the AWGs. To address this limitation, we use the recently developed photonic integrated circuits (PICs) based on thin-film lithium tantalate ($\mathrm{LiTaO}_3$), a material with a similar Pockels coefficient as $\mathrm{LiNbO}_3$ but significantly reduced optical anisotropy, as an alternative viable platform. In this work, we manufacture $\mathrm{LiTaO}_3$ AWGs using deep ultraviolet lithography on a wafer-scale. The fabricated AWGs feature a channel spacing of 100 GHz, an insertion loss of < 4 dB and crosstalk of < -14 dB. In addition, we demonstrate a cyclic AWG, as well as a multiplexing and demultiplexing AWG pair for the first time on $\mathrm{LiTaO}_3$ platform. The wafer-scale fabrication of these AWGs not only ensures uniformity and reproducibility, but also paves the way for realizing volume-manufactured integrated WDM transmitters in ferroelectric photonic integrated platforms.

physics.optics↗

arXiv2025

Dispersion-Engineered Compact Twisted Metasurfaces Enabling 3D Frequency-Reconfigurable Holography

Flexible dispersion manipulation is critical for holography to achieve broadband imaging or frequency division multiplexing. Within this context, metasurface-based holography offers advanced dispersion control, yet dynamic reconfigurability remains largely unexplored. This work develops a dispersion-engineered inverse design framework that enables 3D frequency-reconfigurable holography through a twisted metasurface system. The physical implementation is based on a compact layered configuration that cascades the broadband radiation-type metasurface (RA-M) and phase-only metasurface (P-M). The RA-M provides a phase-adjustable input to excite P-M, while the rotation of P-M creates a reconfigurable response of holograms. By employing the proposed scheme, dynamic switching of frequency-space multiplexing and achromatic holograms are designed and experimentally demonstrated in the microwave region. This method advances flexible dispersion engineering for metasurface-based holography, and the compact system holds significant potential for applications in ultra-broadband imaging, high-capacity optical display, and switchable meta-devices.

physics.optics↗

arXiv2025

Roadmap on Neuromorphic Photonics

This roadmap consolidates recent advances while exploring emerging applications, reflecting the remarkable diversity of hardware platforms, neuromorphic concepts, and implementation philosophies reported in the field. It emphasizes the critical role of cross-disciplinary collaboration in this rapidly evolving field.

cs.ET↗

arXiv2024

Optical next generation reservoir computing

Artificial neural networks with internal dynamics exhibit remarkable capability in processing information. Reservoir computing (RC) is a canonical example that features rich computing expressivity and compatibility with physical implementations for enhanced efficiency. Recently, a new RC paradigm known as next generation reservoir computing (NGRC) further improves expressivity but compromises its physical openness, posing challenges for realizations in physical systems. Here we demonstrate optical NGRC with computations performed by light scattering through disordered media. In contrast to conventional optical RC implementations, we drive our optical reservoir directly with time-delayed inputs. Much like digital NGRC that relies on polynomial features of delayed inputs, our optical reservoir also implicitly generates these polynomial features for desired functionalities. By leveraging the domain knowledge of the reservoir inputs, we show that the optical NGRC not only predicts the short-term dynamics of the low-dimensional Lorenz63 and large-scale Kuramoto-Sivashinsky chaotic time series, but also replicates their long-term ergodic properties. Optical NGRC shows superiority in shorter training length, increased interpretability and fewer hyperparameters compared to conventional optical RC based on scattering media, while achieving better forecasting performance. Our optical NGRC framework may inspire the realization of NGRC in other physical RC systems, new applications beyond time-series processing, and the development of deep and parallel architectures broadly.

physics.optics↗

arXiv2024

Integrated Triply Resonant Electro-Optic Frequency Comb in Lithium Tantalate

Integrated frequency comb generators based on Kerr parametric oscillation have led to chip-scale, gigahertz-spaced combs with new applications spanning hyperscale telecommunications, low-noise microwave synthesis, LiDAR, and astrophysical spectrometer calibration. Recent progress in lithium niobate (LN) photonic integrated circuits (PICs) has resulted in chip-scale electro-optic (EO) frequency combs, offering precise comb-line positioning and simple operation without relying on the formation of dissipative Kerr solitons. However, current integrated EO combs face limited spectral coverage due to the large microwave power required to drive the non-resonant capacitive electrodes and the strong intrinsic birefringence of Lithium Niobate. Here, we overcome both challenges with an integrated triply resonant architecture, combining monolithic microwave integrated circuits (MMICs) with PICs based on the recently emerged thin-film lithium tantalate. With resonantly enhanced EO interaction and reduced birefringence in Lithium Tantalate, we achieve a four-fold comb span extension and a 16-fold power reduction compared to the conventional non-resonant microwave design. Driven by a hybrid-integrated laser diode, the comb spans over 450nm (60THz) with >2000 lines, and the generator fits within a compact 1cm^2 footprint. We additionally observe that the strong EO coupling leads to an increased comb existence range approaching the full free spectral range of the optical microresonator. The ultra-broadband comb generator, combined with detuning-agnostic operation, could advance chip-scale spectrometry and ultra-low-noise millimeter wave synthesis and unlock octave-spanning EO combs. The methodology of co-designing microwave and optical resonators can be extended to a wide range of integrated electro-optics applications.

physics.optics↗

arXiv2024

Self-organized spatiotemporal quasi-phase-matching in microresonators

Quasi-phase-matching (QPM) is a widely adopted technique for mitigating stringent momentum conservation in nonlinear optical processes such as second-harmonic generation (SHG). It effectively compensates for the phase velocity mismatch between optical harmonics by introducing a periodic spatial modulation to the nonlinear optical medium. Such a mechanism has been further generalized to the spatiotemporal domain, where a non-stationary spatial QPM can induce a frequency shift of the generated light. Here we demonstrate how a spatiotemporal QPM grating, consisting in a concurrent spatial and temporal modulation of the nonlinear response, naturally emerges through all-optical poling in silicon nitride microresonators. Mediated by the coherent photogalvanic effect, a traveling space-charge grating is self-organized, affecting momentum and energy conservation, resulting in a quasi-phase-matched and Doppler-shifted second harmonic. Our observation of the photoinduced spatiotemporal QPM expands the scope of phase matching conditions in nonlinear photonics.

physics.optics↗

arXiv2024

Generalized angle-orbital-angular-momentum Talbot effect and modulo mode sorting

The Talbot effect describes periodic revivals of field patterns and is ubiquitous across wave systems. In optics, it is mostly known for its manifestations in space and time, but is also observed in the wavevector and frequency spectra owing to the Fourier duality. Recently, the Talbot self-imaging has been shown separately in the azimuthal angle and orbital angular momentum (OAM) domains. Here, we unveil the missing link between them and demonstrate the generalized angle-OAM Talbot effect. Versatile transformations of petal fields and OAM spectra are experimentally showcased, based on the synergy of angular Talbot phase modulation and light propagation in a ring-core fiber. Moreover, the generalized self-imaging concept leads to new realizations in mode sorting, which separate OAM modes in a modulo manner, theoretically free from any crosstalk within the congruence classes of OAM modes. We design and experimentally construct various mode sorters with excellent performance, and show the unconventional behavior of Talbot-based sorters where neighboring OAM modes can be mapped to positions far apart. Besides its fundamental interest, our work finds applications in OAM-based information processing, and implies that the physical phenomena in time-frequency and angle-OAM domains are broadly connected as well as their processing techniques may be borrowed interchangeably.

physics.optics↗

arXiv2023

Large-scale photonic computing with nonlinear disordered media

Neural networks find widespread use in scientific and technological applications, yet their implementations in conventional computers have encountered bottlenecks due to ever-expanding computational needs. Photonic neuromorphic hardware, which manipulates information and represents data continuously in the optical domain, is one of the promising platforms with potential advantages of massive parallelism, ultralow latency, and reduced energy consumption. While linear photonic neural networks are within reach, photonic computing with large-scale optical nonlinear nodes remains largely unexplored. Here, we demonstrate a large-scale, high-performance nonlinear photonic neural system based on a disordered polycrystalline slab composed of lithium niobate nanocrystals. Mediated by random quasi-phase-matching and multiple scattering, linear and nonlinear optical speckle features are generated as the interplay between the simultaneous linear random scattering and the second-harmonic generation, defining a complex neural network in which the second-order nonlinearity acts as internal nonlinear activation functions. Benchmarked against linear random projection, such nonlinear mapping embedded with rich physical computational operations shows improved performance across a large collection of machine learning tasks in image classification, regression, and graph classification with varying complexity. Demonstrating up to 27,648 input and 3,500 nonlinear output nodes, the combination of optical nonlinearity and random scattering serves as a scalable computing engine for diverse applications.

physics.optics↗

arXiv2023

Integrated Backward Second-Harmonic Generation Through Optically Induced Quasi-Phase Matching

Quasi-phase-matching for efficient backward second-harmonic generation (BSHG) requires sub-$\rmμ$m poling periods, a non-trivial fabrication feat. For the first time, we report integrated first-order quasi-phase-matched BSHG enabled by seeded all-optical poling. The self-organized grating inscription circumvents all fabrication challenges. We compare backward and forward processes and explain how grating period influences the conversion efficiency. These results showcase unique properties of the coherent photogalvanic effect and how it can bring new nonlinear functionalities to integrated photonics.

physics.optics↗

arXiv2022

Single-shot Kramers-Kronig complex orbital angular momentum spectrum retrieval

Orbital angular momentum (OAM) spectrum diagnosis is a fundamental building block for diverse OAM-based systems. Among others, the simple on-axis interferometric measurement can retrieve the amplitude and phase information of complex OAM spectra in a few shots. Yet, its single-shot retrieval remains illusive, due to the signal-signal beat interference inherent in the measurement. Here, we introduce the concept of Kramers-Kronig (KK) receiver in coherent communications to the OAM domain, enabling rigorous, single-shot OAM spectrum measurement. We explain in detail the working principle and the requirement of the KK method, and then apply the technique to precisely measure various characteristic OAM states. In addition, we discuss the effects of the carrier-to-signal power ratio and the number of sampling points essential for rigorous retrieval, and evaluate the performance on a large set of random OAM spectra and high-dimensional spaces. Single-shot KK interferometry shows enormous potential for characterizing complex OAM states in real-time.

physics.optics↗

arXiv2022

Photo-induced cascaded harmonic and comb generation in silicon nitride microresonators

Silicon nitride (Si$_3$N$_4$) is an ever-maturing integrated platform for nonlinear optics. Yet, due to the absence of second-order ($χ^{(2)}$) nonlinearity, Si$_3$N$_4$ is mostly considered for third-order ($χ^{(3)}$) nonlinear interactions. Recently, this limitation was overcome by optical poling in both Si$_3$N$_4$ waveguides and microresonators via the photogalvanic effect, resulting in the inscription of quasi-phase-matched $χ^{(2)}$ gratings. Here, we report cascaded nonlinear effects in a normal dispersion Si$_3$N$_4$ microresonator with combined $χ^{(2)}$ and $χ^{(3)}$ nonlinearities. We demonstrate that the photo-induced $χ^{(2)}$ grating also provides phase-matching for the sum-frequency generation process, enabling the initiation and successive switching of primary combs at pump wavelength. Additionally, the doubly resonant pump and second-harmonic fields allow for cascaded third-harmonic generation, where a secondary optically written $χ^{(2)}$ grating is identified. Finally, we reach a low-noise, broadband microcomb state evolved from the sum-frequency coupled primary comb. These results expand the scope of cascaded effects in $χ^{(2)}$ and $χ^{(3)}$ microresonators.

physics.optics↗