arXiv subjects

Shurui Wang

Publications and source records attributed to Shurui Wang.

13 recordsLinked to original sources

arXiv2026

2L-LSH: A Locality-Sensitive Hash Function-Based Method For Rapid Point Cloud Indexing

The development of 3D scanning technology has enabled the acquisition of massive point cloud models with diverse structures and large scales, thereby presenting significant challenges in point cloud processing. Fast neighboring points search is one of the most common problems, which is frequently used in model reconstruction, classification, retrieval and feature visualization. Hash function is well known for its high-speed and accurate performance in searching high-dimensional data, which is also the core of the proposed 2L-LSH. Specifically, the 2L-LSH algorithm adopts a two-step hash function strategy, in which the popular step divides the bounding box of the point cloud model and the second step constructs a generalized table-based data structure. The proposed 2L-LSH offers a highly efficient and accurate solution for fast neighboring points search in large-scale 3D point cloud models, making it a promising technique for various applications in the field. The proposed algorithm is compared with the well-known methods including Kd-tree and Octree; the obtained results demonstrated that the proposed method outperforms Kd-tree and Octree in terms of speed, i.e. the time consumption of kNN search can be 51.111% and 94.159% lower than Kd-tree and Octree, respectively. And the RN search time can be 54.519% and 41.840% lower than Kd-tree and Octree, respectively.

cs.CV↗

arXiv2025

Free space optics in two dimensions: optical elements for silicon photonics without lateral confinement

Silicon photonic components based on freely propagating beams in 220 nm thick Si slab waveguides are described and characterized. Examples include optical relays, waveguide crossings, couplers, and resonators with wavelength independent Q factors. The unconfined beams are manipulated using reflecting mirrors etched into the Si layer, which operate in the total internal reflection (TIR) regime. This approach eliminates the back-scattering and waveguide loss arising from sidewall roughness in single mode waveguides, reduces sensitivity to small dimensional variations, and reduces light induced self-heating. Although the detailed behavior of TIR at curved waveguide side wall mirror is too complex to capture by simple models, the experimental results are found to be in qualitative agreement with simple analytical calculations based on Gaussian beam theory and effective index approximations.

physics.optics↗

arXiv2025

Planar Waveguide Circulating Gaussian Beam Resonators on a Silicon Photonic Chip

A Si slab waveguide resonator design with a circulating Gaussian-like cavity mode is described and characterized, for both all-pass and add-drop configurations and several different input/output coupling strengths. The circulating beam propagates in a slab waveguide with no lateral confinement. Three straight mirrors and one curved mirror define a folded two-dimensional Gaussian cavity. Light is coupled to and from the resonator by beam splitters formed by a narrow gap between a cavity mirror and the input slab waveguides. The coupling is determined by the gap width and is wavelength independent and lossless. For a L=100 um path length cavity, resonance line widths of 5 pm with Q-values of Q = 310000 were measured. The resonator drop spectrum exhibited a comb of almost identical resonance lines across a 100 nm tuning range. This resonator design is capable of broadband operation and is less susceptible to sidewall roughness and defect scattering induced loss and mode splitting, when compared with Si rings formed from narrow single mode waveguides.

physics.optics↗

arXiv2025

Hierarchical Information-Guided Spatio-Temporal Mamba for Stock Time Series Forecasting

Mamba has demonstrated excellent performance in various time series forecasting tasks due to its superior selection mechanism. Nevertheless, conventional Mamba-based models encounter significant challenges in accurately predicting stock time series, as they fail to adequately capture both the overarching market dynamics and the intricate interdependencies among individual stocks. To overcome these constraints, we introduce the Hierarchical Information-Guided Spatio-Temporal Mamba (HIGSTM) framework. HIGSTM introduces Index-Guided Frequency Filtering Decomposition to extract commonality and specificity from time series. The model architecture features a meticulously designed hierarchical framework that systematically captures both temporal dynamic patterns and global static relationships within the stock market. Furthermore, we propose an Information-Guided Mamba that integrates macro informations into the sequence selection process, thereby facilitating more market-conscious decision-making. Comprehensive experimental evaluations conducted on the CSI500, CSI800 and CSI1000 datasets demonstrate that HIGSTM achieves state-of-the-art performance.

cs.LG↗

arXiv2024

Calibrated absolute optical contrast for high-throughput characterization of horizontally aligned carbon nanotube arrays

Horizontally aligned carbon nanotube (HACNT) arrays hold significant potential for various applications in nanoelectronics and material science. However, their high-throughput characterization remains challenging due to the lack of methods with both high efficiency and high accuracy. Here, we present a novel technique, Calibrated Absolute Optical Contrast (CAOC), achieved through the implementation of differential principles to filter out stray signals and high-resolution calibration to endow optical contrast with physical significance. CAOC offers major advantages over previous characterization techniques, providing consistent and reliable measurements of HACNT array density with high throughput and non-destructive assessment. To validate its utility, we demonstrate wafer-scale uniformity assessment by rapid density mapping. This technique not only facilitates the practical evaluation of HACNT arrays but also provides insights into balancing high throughput and high resolution in nanomaterial characterization.

physics.app-ph↗

arXiv2024

Transforming the Synthesis of Carbon Nanotubes with Machine Learning Models and Automation

Carbon-based nanomaterials (CBNs) are showing significant potential in various fields, such as electronics, energy, and mechanics. However, their practical applications face synthesis challenges stemming from the complexities of structural control, large-area uniformity, and high yield. Current research methodologies fall short in addressing the multi-variable, coupled interactions inherent to CBNs production. Machine learning methods excel at navigating such complexities. Their integration with automated synthesis platforms has demonstrated remarkable potential in accelerating chemical synthesis research, but remains underexplored in the nanomaterial domain. Here we introduce Carbon Copilot (CARCO), an artificial intelligence (AI)-driven platform that integrates transformer-based language models tailored for carbon materials, robotic chemical vapor deposition (CVD), and data-driven machine learning models, empowering accelerated research of CBNs synthesis. Employing CARCO, we demonstrate innovative catalyst discovery by predicting a superior Titanium-Platinum bimetallic catalyst for high-density horizontally aligned carbon nanotube (HACNT) array synthesis, validated through over 500 experiments. Furthermore, with the assistance of millions of virtual experiments, we achieved an unprecedented 56.25% precision in synthesizing HACNT arrays with predetermined densities in the real world. All were accomplished within just 43 days. This work not only advances the field of HACNT arrays but also exemplifies the integration of AI with human expertise to overcome the limitations of traditional experimental approaches, marking a paradigm shift in nanomaterials research and paving the way for broader applications.

physics.app-ph↗

arXiv2023

Perfectly vertical silicon metamaterial grating couplers with large segmentation periods up to 650 nm

Perfectly vertical grating couplers leveraging metamaterials can achieve both high coupling efficiency and minimal back reflection. The fabricability of these designs, with segmentations in both the longitudinal and transverse dimensions, hinges on the minimum feature size offered by cutting-edge fabrication technologies. In this work we present both numerical and experimental evidence that high performance devices can be obtained while using large transverse segmentation periods of up to 650 nm, thereby increasing the critical feature sizes. For single-step etched couplers produced on the 220 nm silicon-on-insulator platform, we demonstrate coupling efficiencies of nearly 50% in the C-band and remarkably low back reflections of -22 dB at zero-degree incidence angle. Notably, the duty cycles used in our optimized designs deviate significantly from those predicted by traditional effective medium models, even for small periods. Our findings promise to expand the range of optical properties achievable in metamaterials and offer fresh insights into the fine-tuning of nanophotonic devices.

physics.optics↗

arXiv2023

Optical wavefront phase-tilt measurement using Si-photonic waveguide grating couplers

Silicon photonic wavefront phase-tilt sensors for wavefront monitoring using surface coupling grating arrays are demonstrated. The first design employs the intrinsic angle dependence of the grating coupling efficiency to determine local wavefront tilt, with a measured sensitivity of 7 dB/degree. A second design connects four gratings in an interferometric waveguide circuit to determine incident wavefront phase variation across the sensor area. In this device, one fringe spacing corresponds to approximately 2 degree wavefront tilt change. These sensor elements can sample a wavefront incident on the chip surface without the use of bulk optic elements, fiber arrays, or imaging arrays. Both sensor elements are less than 60 um across, and can be combined into larger arrays to monitor wavefront tilt and distortion across an image or pupil plane in adaptive optics systems for free space optical communications, astronomy and beam pointing applications.

physics.optics↗

arXiv2023

Intelligent machines work in unstructured environments by differential neuromorphic computing

Efficient operation of intelligent machines in the real world requires methods that allow them to understand and predict the uncertainties presented by the unstructured environments with good accuracy, scalability and generalization, similar to humans. Current methods rely on pretrained networks instead of continuously learning from the dynamic signal properties of working environments and suffer inherent limitations, such as data-hungry procedures, and limited generalization capabilities. Herein, we present a memristor-based differential neuromorphic computing, perceptual signal processing and learning method for intelligent machines. The main features of environmental information such as amplification (>720%) and adaptation (<50%) of mechanical stimuli encoded in memristors, are extracted to obtain human-like processing in unstructured environments. The developed method takes advantage of the intrinsic multi-state property of memristors and exhibits good scalability and generalization, as confirmed by validation in two different application scenarios: object grasping and autonomous driving. In the former, a robot hand experimentally realizes safe and stable grasping through fast learning (in ~1 ms) the unknown object features (e.g., sharp corner and smooth surface) with a single memristor. In the latter, the decision-making information of 10 unstructured environments in autonomous driving (e.g., overtaking cars, pedestrians) is accurately (94%) extracted with a 40*25 memristor array. By mimicking the intrinsic nature of human low-level perception mechanisms, the electronic memristive neuromorphic circuit-based method, presented here shows the potential for adapting to diverse sensing technologies and helping intelligent machines generate smart high-level decisions in the real world.

eess.SP↗

arXiv2023

Measurement Accuracy in Silicon Photonic Ring Resonator Thermometers: Identifying and Mitigating Intrinsic Impairments

Silicon photonic ring resonator thermometers have been shown to provide temperature measurements with a 10 mK accuracy. In this work we identify and quantify the intrinsic on-chip impairments that may limit further improvement in temperature measurement accuracy. The impairments arise from optically induced changes in the waveguide effective index, and from back-reflections and scattering at defects and interfaces inside the ring cavity and along the path between light source and detector. These impairments are characterized for 220 x 500 nm Si waveguide rings by experimental measurement in a calibrated temperature bath and by phenomenological models of ring response. At different optical power levels both positive and negative light induced resonance shifts are observed. For a ring with L = 100 um cavity length, the self-heating induced resonance red shift can alter the temperature reading by 200 mK at 1 mW incident power, while a small blue shift is observed below 100 uW. The effect of self-heating is shown to be effectively suppressed by choosing longer ring cavities. Scattering and back-reflections often produce split and distorted resonance line shapes. Although these distortions can vary with resonance order, they are almost completely invariant with temperature for a given resonance and do not lead to measurement errors in themselves. The effect of line shape distortions can largely be mitigated by tracking only selected resonance orders with negligible shape distortion, and by measuring the resonance minimum wavelength directly, rather than attempting to fit the entire resonance line shape. The results demonstrate the temperature error due to these impairments can be limited to below the 3 mK level through appropriate design choices and measurement procedures.

physics.optics↗

arXiv2022

Athermal and tunable echelle grating wavelength demultiplexers using a Mach-Zehnder interferometer launch structure

We present a comparative experimental study of three silicon photonic echelle grating demultiplexers that are integrated with a Mach-Zehnder interferometer (MZI) launch structure. By appropriate choice of the MZI configuration, the temperature induced shift of the demultiplexer channel wavelengths can be suppressed (athermal) or enhanced (super-thermal), or be controlled by an on-chip micro-heater. The latter two configurations allow the channel wavelengths to be actively tuned using lower power than possible by temperature tuning a conventional echelle demultiplexer. In the athermal configuration, the measured channel spectral shift is reduced to less than 10 pm/C, compared to the 83 pm/C shift for an unmodified echelle device. In super-thermal operation an enhanced channel temperature tuning rate of 170 pm/C is achieved. Finally, by modulating the MZI phase with an on-chip heater, the demultiplexer channels can be actively tuned to correct for ambient temperature fluctuations up to 20 C, using a drive current of less than 20 mA.

physics.optics↗

arXiv2020

Spectrum-free integrated photonic remote molecular identification and sensing

Absorption spectroscopy is widely used in sensing and astronomy to understand molecular compositions on microscopic to cosmological scales. However, typical dispersive spectroscopic techniques require multichannel detection, fundamentally limiting the ability to detect extremely weak signals when compared to direct photometric methods. We report the realization of direct spectral molecular detection using a silicon nanophotonic waveguide resonator, obviating dispersive spectral acquisition. We use a thermally tunable silicon ring resonator with a transmission spectrum matched and cross-correlated to the quasi-periodic vibronic absorption lines of hydrogen cyanide. We show that the correlation peak amplitude is proportional to the number of overlapping ring resonances and gas lines, and that molecular specificity is obtained from the phase of the correlation signal in a single detection channel. Our results demonstrate on-chip correlation spectroscopy that is less restricted by the signal-to-noise penalty of other spectroscopic approaches, enabling the detection of faint spectral signatures.

physics.ins-det↗

arXiv2016

Ultra broadband waveveguide coupler using an anisotropic sub-wavelength metamaterial

Multimode interference couplers are a fundamental building block in many integrated photonic systems, ranging from high-speed coherent receivers to quantum splitters. However, their basic structure has remained fundamentally unchanged for almost four decades, limiting their size and operation bandwidth. Using sub-wavelength metamaterials, photonic devices with break-through size and performance have been recently reported. Leveraging the inherent anisotropy of these structures, here we derive a semi-analytic expression that enables the design of compact and ultra broadband multimode interference couplers. We experimentally demonstrate virtually perfect operation over a bandwidth in excess of 300nm (500nm in simulation), for a device three times shorter than its conventional counterpart, making this the most broadband multimode interference coupler reported to date. These results will enable ultra broadband integrated systems for applications in communications and sensing.

physics.optics↗