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Zhongjin Lin

Publications and source records attributed to Zhongjin Lin.

10 recordsLinked to original sources

Quantum photonic frequency processor on thin-film lithium niobate

The rapid development of photonic quantum information processing necessitates precise and programmable control over optical frequency, a capability critical not only for achieving photon indistinguishability but also for exploiting a virtually unbounded frequency dimension. However, efficient and scalable processing of frequency-encoded photon states remains challenging, primarily due to the limited nonlinear optical interaction in most photonic materials. Here, by harnessing the high-performance thin-film lithium niobate electro-optic (EO) platform, we demonstrate an integrated quantum photonic frequency processor that enables coherent and programmable control of photon frequency with high precision. We establish a scalable architecture for frequency-encoded quantum information processing. Using a fully integrated photonic chip, we realize a universal set of frequency-encoded quantum logic gates, including arbitrary single-qubit rotation gates and the two-qubit controlled-phase gate. Furthermore, we demonstrate its application in high fidelity characterization of frequency-bin entangled states. Our work reveals the unprecedented potential of utilizing the frequency degree of freedom in integrated quantum photonic systems.

quant-ph

Precise and Robust Domain Engineering Based on Faraday Cage Effect for Thin-film Lithium Niobate Photonics

Thin-film lithium niobate (TFLN) waveguides are promising for efficient second-harmonic generation (SHG) owing to their strong optical confinement and large second-order nonlinearity. However, robust fabrication of high-efficiency devices remains challenging, as existing domain engineering methods lack precise and robust controls of polarity distributions. Here, we propose and demonstrate a domain engineering technique that utilizes nanoscale Faraday cages to shape the electric-field distributions during poling, physically defining polarity distribution by the geometry of the Faraday cages without real-time monitoring. As a proof of concept, the method is used to fabricate a spatially selectively poled TFLN waveguide, where all regions are poled except for a 400-nm-wide central. This waveguide achieves a normalized SHG efficiency of 6242 %W-1cm-2. Systematic investigation of the inverted domain growth dynamics confirms the enhanced precision and robustness of this approach over conventional time-controlled methods, paving the way for scalable nonlinear photonic circuits.

physics.optics

Programmable electro-optic frequency comb empowers integrated parallel convolution processing

Integrated photonic convolution processors make optical neural networks (ONNs) a transformative solution for artificial intelligence applications such as machine vision. To enhance the parallelism, throughput, and energy efficiency of ONNs, wavelength multiplexing is widely applied. However, it often encounters the challenges of low compactness, limited scalability, and high weight reconstruction latency. Here, we proposed and demonstrated an integrated photonic processing unit with a parallel convolution computing speed of 1.62 trillion operations per second (TOPS) and a weight reconstruction speed exceeding 38 GHz. This processing unit simultaneously achieves, for the first time, multi-wavelength generation and weight mapping via a single programmable electro-optic (EO) frequency comb, featuring unprecedented compactness, device-footprint independent scalability, and near-unity optical power conversion efficiency (conversion efficiency from input optical power to output weighted comb lines). To demonstrate the reconfigurability and functionality of this processing unit, we implemented image edge detection and object classification based on EO combs obtained using the particle swarm algorithm and an EO comb neural network training framework, respectively. Our programmable EO comb-based processing framework establishes a new paradigm towards the development of low-latency monolithic photonic processors, promising real-time in-sensor learning for autonomous vehicles, intelligent robotics, and drones.

physics.optics

On-chip real-time detection of optical frequency variations with ultrahigh resolution using the sine-cosine encoder approach

Real-time measurement of optical frequency variations (OFVs) is crucial for various applications including laser frequency control, optical computing, and optical sensing. Traditional devices, though accurate, are often too large, slow and costly. Here we present a photonic integrated circuit (PIC) chip, utilizing the sine-cosine encoder principle, for high-speed and high-resolution real-time OFV measurement. Fabricated on a thin film lithium niobate (TFLN) platform, this chip-sized optical frequency detector (OFD) (5.5 mm * 2.7 mm) achieves a speed of up to 2500 THz/s and a resolution as fine as 2 MHz over a range exceeding 160 nm. Our robust algorithm overcomes the device imperfections and ensures precise quantification of OFV parameters. As a practical demonstration, the PIC OFD surpasses existing fiber Bragg grating (FBG) interrogators in sensitivity and speed for strain and vibration measurements. This work opens new avenues for on-chip OFV detection and offers significant potential for diverse applications involving OFV measurement.

physics.optics

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

120 GOPS Photonic Tensor Core in Thin-film Lithium Niobate for Inference and in-situ Training

Photonics offers a transformative approach to artificial intelligence (AI) and neuromorphic computing by enabling low-latency, high-speed, and energy-efficient computations. However, conventional photonic tensor cores face significant challenges in constructing large-scale photonic neuromorphic networks. Here, we propose a fully integrated photonic tensor core, consisting of only two thin-film lithium niobate (TFLN) modulators, a III-V laser, and a charge-integration photoreceiver. Despite its simple architecture, it is capable of implementing an entire layer of a neural network with a computational speed of 120 GOPS, while also allowing flexible adjustment of the number of inputs (fan-in) and outputs (fan-out). Our tensor core supports rapid in-situ training with a weight update speed of 60 GHz. Furthermore, it successfully classifies (supervised learning) and clusters (unsupervised learning) 112 * 112-pixel images through in-situ training. To enable in-situ training for clustering AI tasks, we offer a solution for performing multiplications between two negative numbers.

physics.optics

High Performance Polarization Management Devices Based on Thin-Film Lithium Niobate

High-speed polarization management is highly desirable for many applications, such as remote sensing, telecommunication, and medical diagnosis. However, most of the approaches for polarization management rely on bulky optical components that are slow to respond, cumbersome to use, and sometimes with high drive voltages. Here, we overcome these limitations by harnessing photonic integrated circuits based on thin-film lithium niobate platform. We successfully realize a portfolio of thin-film lithium niobate devices for essential polarization management functionalities, including arbitrary polarization generation, fast polarization measurement, polarization scrambling, and automatic polarization control. The present devices feature ultra-fast control speed, low drive voltages, low optical losses and compact footprints. Using these devices, we achieve high fidelity polarization generation with a polarization extinction ratio up to 41.9 dB, fast polarization scrambling with a scrambling rate up to 65 Mrad/s, and endless polarization control with a tracking speed up to 10 Krad/s, all of which are best results in integrated optics. The demonstrated devices unlock a drastically new level of performance and scales in polarization management devices, leading to a paradigm shift in polarization management.

physics.optics

Chip-scale Full-Stokes Spectropolarimeter in Silicon Photonic Circuits

Wavelength-dependent polarization state of light carries crucial information about light-matter interactions. However, its measurement is limited to bulky, energy-consuming devices, which prohibits many modern, portable applications. Here, we propose and demonstrate a chip-scale spectropolarimeter implemented using a CMOS-compatible silicon photonics technology. Four compact Vernier microresonator spectrometers are monolithically integrated with a broadband polarimeter consisting of a 2D nanophotonic antenna and a polarimetric circuit to achieve full-Stokes spectropolarimetric analysis. The proposed device offers a solid-state spectropolarimetry solution with a small footprint of 1*0.6 mm2 and low power consumption of 360 mW}. Full-Stokes spectral detection across a broad spectral range of 50 nm with a resolution of 1~nm is demonstrated in characterizing a material possessing structural chirality. The proposed device may enable a broader application of spectropolarimetry in the fields ranging from biomedical diagnostics and chemical analysis to observational astronomy.

physics.optics

A Chip-scale, Full-Stokes Polarimeter

The polarization of light conveys unique information that can be exploited by crucial applications. The bulky and costly discrete optical components used in conventional polarimeters limit their broad adoption. A compact, low-cost polarimeter would bring this functionality into a myriad of new scenarios and revolutionize its exploitation. Here we present a high-performance, full-Stokes polarimeter on a silicon chip. A surface polarization splitter and on-chip optical interferometer circuit produce the analysis matrix of an optimally conditioned polarimeter. This solid-state polarimeter is a system-on-a-chip with exceptional compactness, stability, and speed that could be used singly or in integrated arrays. Large arrays can increase the speed and resolution of full-Stokes imaging; therefore, our design provides a scalable polarimeter solution.

physics.app-ph