Showing 1–49 of 49 results for author: Su, R

Hierarchical rank-evolving representation for physics-informed neural networks

Authors: Ruoyang Su, Xi-Le Zhao, Kun Li, Liang Li

Abstract: Recently, tensor-based physics-informed neural networks (T-PINNs) have received increasing attention. However, existing T-PINNs still face a fundamental challenge: they mainly rely on pre-specified low-rank tensor decompositions with manually tuned ranks, which limits their ability to capture the underlying structures of multivariate solution functions and hinders their practical deployment. To ad… ▽ More Recently, tensor-based physics-informed neural networks (T-PINNs) have received increasing attention. However, existing T-PINNs still face a fundamental challenge: they mainly rely on pre-specified low-rank tensor decompositions with manually tuned ranks, which limits their ability to capture the underlying structures of multivariate solution functions and hinders their practical deployment. To address this challenge, we propose a hierarchical rank-evolving (abbreviated as HRE) representation for multivariate functions, which endows us to faithfully capture the underlying structure of the targeted multivariate function accompanying with automatic rank determination. Concretely, in the hierarchical design of HRE representation, the target multivariate function is decomposed as a small-scale inner tensor with a set of univariate functions along each mode, where a customized tensor network decomposition can be readily deployed to capture the underlying structure of the small-scale inner tensor. In HRE representation, the crucial hyperparameters, ranks, can be adaptively revealed during the decomposition, freeing us from manual rank tuning and making HRE practically applicable to real-world problems. Besides, we build the HRE-PINNs correspondingly. Extensive numerical experiments, including high-dimensional static problems (Helmholtz equation and Poisson equation), nonlinear time-dependent problems (Klein-Gordon equation), and complex fluid-dynamics problems (flow mixing equation and Navier-Stokes equation), demonstrate that HRE-PINNs consistently outperform existing state-of-the-art approaches in terms of accuracy. △ Less

Submitted 10 August, 2026; originally announced August 2026.

From Materials Database to Materials Bank: Assetizing Data for AI Driven Materials Innovation

Authors: Chenyao Ma, Di Zhang, Weibo Gong, Wei Du, Rui Su, Yuhang Chen, Kan Xu, Huan Gu, Limin Li, Piao Ma, Zhenghao Li, Hao Li

Abstract: Driven by high-throughput experimentation, computational modeling, and artificial intelligence (AI), materials data has expanded at an unprecedented rate. Conventional materials databases function only as passive repositories, archiving raw experimental records indiscriminately including both successful and failed data, without systematic value filtering or asset management. This creates a critica… ▽ More Driven by high-throughput experimentation, computational modeling, and artificial intelligence (AI), materials data has expanded at an unprecedented rate. Conventional materials databases function only as passive repositories, archiving raw experimental records indiscriminately including both successful and failed data, without systematic value filtering or asset management. This creates a critical gap between massive data accumulation and actionable innovation, hindering the identification of high-potential materials and industrial translation. To address this bottleneck, we propose an industrialization-oriented Materials Bank, a dedicated valuefiltering and assetization layer that operates beyond traditional databases. It does not merely curate high-quality data but systematically elevates qualified candidates into standardized, upgradable materials assets via a multi-dimensional BankCard framework covering scientific validity, synthesis feasibility, application readiness, and industrial value. By unifying databases, AI models, automated experimentation, and multi-criteria assessment into a cohesive closed-loop ecosystem, the Materials Bank establishes a clear trajectory from data to knowledge, candidate, asset, and product. It serves not as an enhanced database or screening tool, but as a decision infrastructure bridging academic discovery and industrial demand, offering a scalable paradigm to accelerate AI-driven materials innovation and deliver tangible real-world impact. △ Less

Submitted 25 July, 2026; v1 submitted 30 June, 2026; originally announced June 2026.

Journal ref: AI for Materials 2026, 1(1), 9

Empowering Polymeric Materials Discovery by Artificial Intelligence

Authors: Chenyao Ma, Linda Zhang, Yuheng Chen, Wei Du, Shangwen Fang, Zihao Jiang, Chuanyu Liu, Xinyu Ma, Rui Su, Gang Wang, Muyao Yu, Dong Zhong, Jie Zhu, Weibo Gong, Huan Gu, Limin Li, Chen Shen, Rui Wu, Zhenghao Wu, Kan Xu, Min Zhou, Donglin He, Xiayun Huang, Shan Jiang, Pengfei Ou , et al. (7 additional authors not shown)

Abstract: Polymeric materials underpin modern technologies spanning energy storage, microelectronics, healthcare and sustainable manufacturing. Yet their rational design remains exceptionally challenging because material performance emerges from complex interactions among molecular composition, chain architecture, processing history and hierarchical structural evolution across multiple length and time scale… ▽ More Polymeric materials underpin modern technologies spanning energy storage, microelectronics, healthcare and sustainable manufacturing. Yet their rational design remains exceptionally challenging because material performance emerges from complex interactions among molecular composition, chain architecture, processing history and hierarchical structural evolution across multiple length and time scales. Consequently, polymer research has long relied on labor-intensive experimentation and fragmented modeling approaches, limiting both mechanistic understanding and innovation efficiency. Recent advances in data infrastructure, machine learning, large artificial intelligence (AI) models and laboratory automation are beginning to reshape this landscape. Rather than functioning as isolated tools, polymer databases, predictive models, AI agents and automated laboratories are increasingly converging into interconnected discovery ecosystems. As a result, the central challenge is shifting from improving predictive accuracy alone to enabling reliable decision-making, adaptive learning and seamless integration across computation, experimentation and scientific reasoning. We argue that polymer science is entering an era of autonomous discovery, in which data, simulation, reasoning and experimentation operate within self-improving feedback loops that continuously generate hypotheses, design materials, execute experiments and refine predictive models. By unifying molecular design, process optimization, experimental validation and industrial translation, such autonomous ecosystems establish a more predictive, reproducible and scalable paradigm for polymer innovation, fundamentally transforming how polymer research is conducted. △ Less

Submitted 16 August, 2026; v1 submitted 18 June, 2026; originally announced June 2026.

Burst-Mode Ultrafast Laser Welding of Sapphire and Invar Alloy Across Large Interfacial Gaps up to 10 $μ$m

Authors: Yuxuan Li, Nan Li, Yu Wang, Yitong Chen, Rong Su, Qingwei Zhang, Rongxian Wen, Guochang Jiang, Feng Chen, Shanglu Yang

Abstract: Achieving reliable joining between transparent materials and metals under non-optical-contact conditions remains challenging due to limited energy coupling and uncontrolled interfacial reaction across $μ$m-scale gaps. Burst-mode ultrafast lasers provide a potential solution for large-gap welding through temporally distributed energy deposition. However, the underlying interaction mechanisms and ac… ▽ More Achieving reliable joining between transparent materials and metals under non-optical-contact conditions remains challenging due to limited energy coupling and uncontrolled interfacial reaction across $μ$m-scale gaps. Burst-mode ultrafast lasers provide a potential solution for large-gap welding through temporally distributed energy deposition. However, the underlying interaction mechanisms and achievable joining limits remain unclear. In this study, burst-mode ultrafast laser welding of sapphire to Invar alloy was investigated under controlled interfacial gaps from 3 to 10 $μ$m. Cross-sectional microscopy, elemental mapping, white-light interferometry, and shear testing were employed to analyze joint morphology, elemental distribution, fracture behavior, and mechanical performance.After optimization of the processing parameters for burst-mode ultrafast laser welding, the interfacial morphological evolution and joint strength under different gap conditions were systematically investigated. At a 3 $μ$m gap, cyclic thermal stresses induced by burst pulses generate transverse micro-crack networks in sapphire, accompanied by a reduction in joint strength with increasing sub-pulse numbers. Notably, at a 10 $μ$m gap, where single-pulse welding fails, burst-mode ultrafast laser welding enables interfacial bridging with a maximum shear strength of 6.3 MPa, representing the highest level among published studies.These results indicate a gap-dependent evolution in burst-mode welding behavior governed by crack formation and energy accumulation. This study provides an important theoretical basis and practical guidance for achieving high-performance joining of dissimilar materials under large gap conditions. △ Less

Submitted 13 May, 2026; originally announced May 2026.

Comments: 31pages 15figures

Beam canalization by a non-Abelian gauge field

Authors: Olha Bahrova, Jiahao Ren, Feng Jin, Rui Su, Guillaume Malpuech, Dmitry Solnyshkov

Abstract: Hyperbolic and quasi-flat isofrequency contours (IFCs) are used for beam canalization and can be created by tilted Dirac points in photonic systems. Dirac points in microcavities are generated by the combination of transverse-electric/transverse-magnetic splitting and linear birefringence. We show that the canalization is here strongly assisted by the coupling between the spatial dynamics and pola… ▽ More Hyperbolic and quasi-flat isofrequency contours (IFCs) are used for beam canalization and can be created by tilted Dirac points in photonic systems. Dirac points in microcavities are generated by the combination of transverse-electric/transverse-magnetic splitting and linear birefringence. We show that the canalization is here strongly assisted by the coupling between the spatial dynamics and polarization pseudospin precession. This dynamics is well described analytically and numerically as the action of a non-Abelian gauge field on emergent charges (spin current). We demonstrate a ten-fold enhancement of the canalization for a Gaussian beam by the gauge field, as compared to a description based solely on the group velocity associated with the IFCs. △ Less

Submitted 4 May, 2026; originally announced May 2026.

Reconfigurable ultrafast perovskite polariton logic gates via nonlinear dynamics

Authors: Yuyang Zhang, Zhuoya Zhu, Xin Zeng, Shuai Zhang, Xinyi Deng, Tian Lan, Changhai Zhu, Kwok Kwan Tang, Qinglin Jia, Yuexing Xia, Yiyang Gong, Wenna Du, Feng Li, Rui Su, Xuekai Ma, Xinfeng Liu, Qing Zhang

Abstract: Exciton-polaritons provide a great platform for developing ultrafast all-optical logic gates for quantum and optical chips. However, progress toward practical polariton logic remains limited due to incomplete logical functionality on a single device. Herein, we present a single-device perovskite polariton platform enabling reconfigurable, ultrafast logic gates with functional completeness. The dev… ▽ More Exciton-polaritons provide a great platform for developing ultrafast all-optical logic gates for quantum and optical chips. However, progress toward practical polariton logic remains limited due to incomplete logical functionality on a single device. Herein, we present a single-device perovskite polariton platform enabling reconfigurable, ultrafast logic gates with functional completeness. The device consists of an optically trapped perovskite microwire, generating well-controlled non-equilibrium polariton condensation states for multiple logic operation channels. By tailoring the power of signal and gate beams, the same device is programmed to execute three basic Boolean functions (AND,OR,and NOT) and a high-order XOR function with a high on/off ratio of 21 dB, and a fast response time 6.7 ps. The reconfigurability arises from the selective activation of different nonlinear responses of polariton condensates, including amplification, seeding state transitions, and nonlinear interaction. These results provide valuable insights for advancing exciton-polariton logic gates. △ Less

Submitted 23 April, 2026; originally announced April 2026.

Comments: 16 pages, 5 figures

Dynamic topological exciton-polaritons enabling ultrafast logic operations

Authors: Feng Jin, Hao Zheng, Zhe Zhang, Jiaohao Ren, Yuxi Liu, Qing Zhang, Daniele Sanvitto, Timothy C. H. Liew, Baile Zhang, Rui Su

Abstract: Topological active materials have emerged as powerful paradigm bridging the discovery of exotic topological phases of matter with the development of functional topological devices. The recent extension of these material systems into dynamic regime, where topological properties can be actively manipulated at ultrafast timescales, promises unprecedented control over topological states and their func… ▽ More Topological active materials have emerged as powerful paradigm bridging the discovery of exotic topological phases of matter with the development of functional topological devices. The recent extension of these material systems into dynamic regime, where topological properties can be actively manipulated at ultrafast timescales, promises unprecedented control over topological states and their functionalities. However, translating the static topological lasing signals into high-performance logic functions remain highly challenging, which imposes a far more stringent set of materials attributes. Here, leveraging the strong nonlinearity and pronounced spectral isolation of perovskite exciton-polaritons embedded in a Dirac vortex microcavity, we experimentally demonstrate the dynamic topological Majorana-like state polariton condensation with its ultrafast logic operations at room temperature. By actively coordinating pump and control beams in both spectral and temporal domain, we dynamically steer the topological polariton condensation process and demonstrate AND and NOT logic operations, achieving record extinction ratio (~20 dB), extremely low control fluence (~0.2 nJ/cm2) and sub-picosecond response time (~500 fs). Our results expand the frontier of dynamic topology and establish a novel pathway towards robust, ultrafast, and reconfigurable on-chip polaritonic logic circuits. △ Less

Submitted 19 February, 2026; originally announced February 2026.

Optically reconfigurable canalization of exciton-polaritons in a non-hyperbolic perovskite

Authors: Jiahao Ren, Olha Bahrova, Feng Jin, Hao Zheng, Dmitry Solnyshkov, Cheng-Wei Qiu, Guillaume Malpuech, Rui Su

Abstract: The ability to steer polariton flow on-demand holds significant promise towards nanophotonic applications and photonic circuitry. Polariton canalization, exhibiting intrinsic collimation and diffractionless transport, emerges as a promising solution without guiding structures. However, earlier demonstrations have been restricted to certain crystal surfaces with intrinsic hyperbolic responses and o… ▽ More The ability to steer polariton flow on-demand holds significant promise towards nanophotonic applications and photonic circuitry. Polariton canalization, exhibiting intrinsic collimation and diffractionless transport, emerges as a promising solution without guiding structures. However, earlier demonstrations have been restricted to certain crystal surfaces with intrinsic hyperbolic responses and operated in the linear regime. Here, we experimentally demonstrate canalization of nonlinear exciton polariton condensates with optical reconfigurability in a birefringent CsPbBr3 perovskite crystal without intrinsic hyperbolic response. By embedding the birefringent perovskite crystal into a planar microcavity, the interplay between cavity transverse-electric-transverse-magnetic splitting and crystalline birefringence produces an anisotropic band geometry with a hyperbolic-flat-parabolic evolution of polaritonic isofrequency contours (IFCs). Nonresonant pumping drives exciton polariton condensation onto flat far-field contours with nonlinear emission amplification, leading to coherent canalized flows with over twentyfold collimation with respect to arc-shaped contours. Reconfiguring the optical pumping-spot size allows switching the nonlinear polariton condensates into hyperbolic and parabolic IFC regimes, leading to divergent propagation behaviour with collimating reconfiguration. Our study reveals a distinct canalization framework for shaping the nonlinear exciton-polariton condensate flows, opening opportunities for all-optical polaritonic logic circuits based on stabilized nonlinear quantum interconnects. △ Less

Submitted 29 January, 2026; originally announced January 2026.

Observation of polaritonic flat-band bound states in the continuum in a 2D magnet

Authors: Fuhuan Shen, Jiahao Ren, Zhiyi Yuan, Kai Wu, Sai Yan, Kunal Parasad, Hai Son Nguyen, Rui Su

Abstract: Flat-band bound states in the continuum (BICs) are topological states with suppressed group velocity and robustness against radiation loss, offering a powerful platform for the exploration of non-Hermitian, nonlinear, topological phenomena and device applications. Van der Waals (vdW) metasurfaces have recently emerged as promising candidates for sustaining BICs and hybridizing with material transi… ▽ More Flat-band bound states in the continuum (BICs) are topological states with suppressed group velocity and robustness against radiation loss, offering a powerful platform for the exploration of non-Hermitian, nonlinear, topological phenomena and device applications. Van der Waals (vdW) metasurfaces have recently emerged as promising candidates for sustaining BICs and hybridizing with material transitions. However, the realization of flat-band BICs remains elusive. Here, we experimentally demonstrate polaritonic high-order BICs on a wide-angle flat band utilizing a subwavelength metasurface made of a vdW magnet CrSBr. The large oscillator strength of direct excitons in CrSBr enables near ultrastrong coupling with BICs, leading to strongly suppressed polaritonic angular dispersions. Remarkably, second-order polaritonic BICs become flat-band across a wide angular range, with corresponding Q factors exceeding 1500. Additionally, we find that these polaritonic BICs vanish in the transverse magnetic configuration, while leading to fascinating surface hyperbolic exciton-polaritons within the Reststrahlen band. Our findings underscore CrSBr as an exceptional platform for exploring flat-band photonics and polaritonics, paving the new avenue for advances in next-generation optical and quantum technologies. △ Less

Submitted 23 January, 2026; originally announced January 2026.

Temporal Beam Self-Cleaning in Second-Harmonic Generation

Authors: Siyu Chen, Jun Ye, Lei Du, Wenwen Cheng, Jiangming Xu, Rongtao Su, Pu Zhou, Zongfu Jiang

Abstract: The spatial-temporal beam quality of laser sources is crucial for applications such as nonlinear spectroscopy and master oscillator power amplification systems. However, the temporal stability remains challenged by issues like line-width broadening and high-power demand in efforts to improve it. In this work, we investigate the effect of the second-harmonic generation process on the laser characte… ▽ More The spatial-temporal beam quality of laser sources is crucial for applications such as nonlinear spectroscopy and master oscillator power amplification systems. However, the temporal stability remains challenged by issues like line-width broadening and high-power demand in efforts to improve it. In this work, we investigate the effect of the second-harmonic generation process on the laser characteristics under three longitudinal mode regimes: single-longitudinal-mode, dual-longitudinal-mode, and multi-longitudinal-mode. The results demonstrate that the second-harmonic generation process effectively stabilizes the temporal characteristics of the laser and enhances its correlation, leading to a temporally clean output beam. The physical mechanism of the observed temporal stabilization effect can be attributed to a high-peak-pulse attenuation effect, jointly induced by nonuniform longitudinal-mode depletion and phase preservation in the residual fundamental wave. Statistical analysis indicates that at the maximum fundamental-wave power in the multi-longitudinal-mode regime, the standard deviation and peak-to-valley values derived from the normalized temporal profile decrease from 0.6122 and 5.6846 for the fundamental wave to 0.189 and 0.8847 for the residual fundamental wave. Meanwhile, the background level of the intensity auto-correlation function rises from ~0.72 to ~0.96, revealing its evolution toward a more coherent state. To the best of our knowledge, this research presents the first demonstration of laser temporal stabilization and correlation enhancement via second-harmonic generation. It not only deepens the comprehension of second-harmonic generation mechanisms, but also opens up a new avenue for realizing temporal beam self-cleaning of light. △ Less

Submitted 17 January, 2026; originally announced January 2026.

PyPeT: A Python Perfusion Tool for Automated Quantitative Brain CT and MR Perfusion Analysis

Authors: Marijn Borghouts, Ruisheng Su

Abstract: Computed tomography perfusion (CTP) and magnetic resonance perfusion (MRP) are widely used in acute ischemic stroke assessment and other cerebrovascular conditions to generate quantitative maps of cerebral hemodynamics. While commercial perfusion analysis software exists, it is often costly, closed source, and lacks customizability. This work introduces PyPeT, an openly available Python Perfusion… ▽ More Computed tomography perfusion (CTP) and magnetic resonance perfusion (MRP) are widely used in acute ischemic stroke assessment and other cerebrovascular conditions to generate quantitative maps of cerebral hemodynamics. While commercial perfusion analysis software exists, it is often costly, closed source, and lacks customizability. This work introduces PyPeT, an openly available Python Perfusion Tool for head CTP and MRP processing. PyPeT is capable of producing cerebral blood flow (CBF), cerebral blood volume (CBV), mean transit time (MTT), time-to-peak (TTP), and time-to-maximum (Tmax) maps from raw four-dimensional perfusion data. PyPeT aims to make perfusion research as accessible and customizable as possible. This is achieved through a unified framework in which both CTP and MRP data can be processed, with a strong focus on modularity, low computational burden, and significant inline documentation. PyPeT's outputs can be validated through an extensive debug mode in which every step of the process is visualized. Additional validation was performed via visual and quantitative comparison with reference perfusion maps generated by three FDA-approved commercial perfusion tools and a research tool. These comparisons show a mean SSIM around 0.8 for all comparisons, indicating a good and stable correlation with FDA-approved tools. The code for PyPeT is openly available at our GitHub https://github.com/Marijn311/CT-and-MR-Perfusion-Tool △ Less

Submitted 18 May, 2026; v1 submitted 17 November, 2025; originally announced November 2025.

OpenSWI: A Massive-Scale Benchmark Dataset for Surface Wave Dispersion Curve Inversion

Authors: Feng Liu, Sijie Zhao, Xinyu Gu, Fenghua Ling, Peiqin Zhuang, Yaxing Li, Rui Su, Lihua Fang, Lianqing Zhou, Jianping Huang, Lei Bai

Abstract: Surface wave dispersion curve inversion plays a critical role in both shallow resource exploration and deep geological studies, yet it remains hindered by sensitivity to initial models and low computational efficiency. Recently, data-driven deep learning methods, inspired by advances in computer vision, have shown promising potential to address these challenges. However, the lack of large-scale, d… ▽ More Surface wave dispersion curve inversion plays a critical role in both shallow resource exploration and deep geological studies, yet it remains hindered by sensitivity to initial models and low computational efficiency. Recently, data-driven deep learning methods, inspired by advances in computer vision, have shown promising potential to address these challenges. However, the lack of large-scale, diverse benchmark datasets remains a major obstacle to their development and evaluation. To bridge this gap, we present OpenSWI, a comprehensive benchmark dataset generated through the Surface Wave Inversion Dataset Preparation (SWIDP) pipeline. OpenSWI includes two synthetic datasets tailored to different research scales and scenarios, OpenSWI-shallow and OpenSWI-deep, and an AI-ready real-world dataset for generalization evaluation, OpenSWI-real. OpenSWI-shallow, derived from the 2-D OpenFWI geological model dataset, contains over 22 million 1-D velocity profiles paired with fundamental-mode phase and group velocity dispersion curves, spanning a wide range of shallow geological structures (e.g., flat layers, faults, folds, realistic stratigraphy). OpenSWI-deep, built from 14 global and regional 3-D geological models, comprises 1.26 million high-fidelity 1-D velocity-dispersion pairs for deep-Earth studies. OpenSWI-real, compiled from open-source projects, contains two sets of observed dispersion curves with corresponding reference models, serving as a benchmark for evaluating model generalization. To demonstrate utility, we trained models on OpenSWI-shallow and -deep and evaluated them on OpenSWI-real, demonstrating strong agreement between predictions and references, which confirms the diversity and representativeness of the dataset. To advance intelligent surface wave inversion, we release the SWIDP toolbox, OpenSWI datasets, and trained models for the research community. △ Less

Submitted 14 August, 2025; originally announced August 2025.

Comments: 27 pages, 13 Figures

Revisiting Fourier-Based Reflection Spectrum Measurement in Coherence Scanning Interferometry

Authors: Cheng Chen, Sotero Ordones, Jeremy Coupland, Rong Su

Abstract: Recent advancements have extended the capabilities of coherence scanning interferometry (CSI) beyond surface topography measurement to reflectivity spectrum imaging. It is commonly accepted that the one-dimensional(1-D) Fourier magnitude of a pixel-wise CSI signal is proportional to the product of the sample's absolute reflection coefficient spectrum and the light source spectrum. However, this as… ▽ More Recent advancements have extended the capabilities of coherence scanning interferometry (CSI) beyond surface topography measurement to reflectivity spectrum imaging. It is commonly accepted that the one-dimensional(1-D) Fourier magnitude of a pixel-wise CSI signal is proportional to the product of the sample's absolute reflection coefficient spectrum and the light source spectrum. However, this assumption holds true only for low numerical aperture (NA) CSI systems. In this work, we establish a generalized mathematical framework that represents the CSI signal a matrix multiplication of the spectrum measurement matrix with the element-wise product of the reflection spectrum and the light source spectrum, assuming spectral independence from the incident angles. Considering the light source spectrum and wavenumber channel summation, we utilize a reflection spectrum measurement matrix and its conditioned counterpart to linearly relate the CSI signal to the absolute reflection spectrum. Through simulations, we quantitatively analyze the impacts of various error sources, including NA inaccuracy, pupil apodization, height reconstruction errors, spectral inaccuracies of the light source, and phase change on reflection (PCOR) from the sample, on the reconstruction performance of the absolute reflection coefficient spectrum. It is found that the PCOR is the dominant factor influencing the reconstruction of the reflection coefficient spectrum. △ Less

Submitted 15 June, 2025; originally announced June 2025.

On-chip Non-Hermitian Cavity Quantum Electrodynamics

Authors: Yan Chen, Xudong Wang, Jin Li, Rongbin Su, Kaili Xiong, Xueshi Li, Ying Yu, Tao Zhang, Kexun Wu, Xiao Li, Jiawei Wang, Jiaxiang Zhang, Jin Liu, Tian Jiang

Abstract: Exceptional points (EPs) promise revolutionary control over quantum light-matter interactions. Here, we experimentally demonstrate flexible and reversible engineering of quantum vacuum fluctuation in an integrated microcavity supporting chiral Eps. We develop a hybrid lithium niobate (LN)-GaAs quantum photonic platform, seamlessly combining high-quality quantum emitters, a low-loss photonic circui… ▽ More Exceptional points (EPs) promise revolutionary control over quantum light-matter interactions. Here, we experimentally demonstrate flexible and reversible engineering of quantum vacuum fluctuation in an integrated microcavity supporting chiral Eps. We develop a hybrid lithium niobate (LN)-GaAs quantum photonic platform, seamlessly combining high-quality quantum emitters, a low-loss photonic circuit, efficient electro-optic (EO) effect, and local strain actuator in a single device. Chiral EPs are implemented by dynamically tuning the coupling between the modes associated with a micro-ring resonator, resulting in anomalous spontaneous emission dynamic with a 7-fold modulation of the lifetime (120 ps to 850 ps). Meanwhile, we reshape single-photon spectra via cavity local density of states (LDOS) engineering and generate non-Lorentzian spectral profiles: squared-Lorentzian, Fano-like, and EP-induced transparency (EPIT), a suppression of emission at zero detuning. This work unveils exotic cavity quantum electrodynamics (cQED) effects unique to EPs and establishes a universal paradigm for non-Hermitian quantum photonics. △ Less

Submitted 1 May, 2025; originally announced May 2025.

Deep Reparameterization for Full Waveform Inversion: Architecture Benchmarking, Robust Inversion, and Multiphysics Extension

Authors: Feng Liu, Yaxing Li, Rui Su, Jianping Huang, Lei Bai

Abstract: Full waveform inversion (FWI) is a high-resolution subsurface imaging technique, but its effectiveness is limited by challenges such as noise contamination, sparse acquisition, and artifacts from multiparameter coupling. To address these limitations, this study develops a deep reparameterized FWI (DR-FWI) framework, in which subsurface parameters are represented by a deep neural network. Instead o… ▽ More Full waveform inversion (FWI) is a high-resolution subsurface imaging technique, but its effectiveness is limited by challenges such as noise contamination, sparse acquisition, and artifacts from multiparameter coupling. To address these limitations, this study develops a deep reparameterized FWI (DR-FWI) framework, in which subsurface parameters are represented by a deep neural network. Instead of directly optimizing the parameters, DR-FWI optimizes the network weights to reconstruct them, thereby embedding structural priors and facilitating optimization. To provide benchmark guidelines for the design of DR-FWI, we conduct a comparative analysis of three representative architectures (U-Net, CNN, MLP) combined with two initial model embedding strategies: one pretraining the network to generate predefined initial models (pretraining-based), while the other directly adds network outputs to the initial models. Extensive ablation experiments show that combining CNN with pretraining-based initialization significantly enhances inversion accuracy, offering valuable insights into network design. To further understand the mechanism of DR-FWI, spectral bias analysis reveals that the network first captures low-frequency features and gradually reconstructs high-frequency details, enabling an adaptive multi-scale inversion strategy. Notably, the robustness of DR-FWI is validated under various noise levels and sparse acquisition scenarios, where its strong performance with limited shots and receivers demonstrates reduced reliance on dense observational data. Additionally, a backbone-branch structure is proposed to extend DR-FWI to multiparameter inversion, and its efficacy in mitigating cross-parameter interference is validated on a synthetic anomaly model and the Marmousi2 model. These results suggest a promising direction for joint inversion involving multiple parameters or multiphysics. △ Less

Submitted 21 June, 2025; v1 submitted 24 April, 2025; originally announced April 2025.

Comments: 11 pages, 12 figures, 2 tables. The relevant code is available at https://github.com/liufeng2317/ADFWI

Why do Opinions and Actions Diverge? A Dynamic Framework to Explore the Impact of Subjective Norms

Authors: Chen Song, Vladimir Cvetkovic, Rong Su

Abstract: Socio-psychological studies have identified a common phenomenon where an individual's public actions do not necessarily coincide with their private opinions, yet most existing models fail to capture the dynamic interplay between these two aspects. To bridge this gap, we propose a novel agent-based modeling framework that integrates opinion dynamics with a decision-making mechanism. More precisely,… ▽ More Socio-psychological studies have identified a common phenomenon where an individual's public actions do not necessarily coincide with their private opinions, yet most existing models fail to capture the dynamic interplay between these two aspects. To bridge this gap, we propose a novel agent-based modeling framework that integrates opinion dynamics with a decision-making mechanism. More precisely, our framework generalizes the classical Hegselmann-Krause model by combining it with a utility maximization problem. Preliminary results from our model demonstrate that the degree of opinion-action divergence within a population can be effectively controlled by adjusting two key parameters that reflect agents' personality traits, while the presence of social network amplifies the divergence. In addition, we study the social diffusion process by introducing a small number of committed agents into the model, and identify three key outcomes: adoption of innovation, rejection of innovation, and the enforcement of unpopular norms, consistent with findings in socio-psychological literature. The strong relevance of the results to real-world phenomena highlights our framework's potential for future applications in understanding and predicting complex social behaviors. △ Less

Submitted 22 March, 2025; originally announced March 2025.

Comments: This work has been submitted to the IEEE for possible publication. 12 pages, 12 figures

Prior-enhanced reflection spectra imaging with a white light interfermetry

Authors: Cheng Chen, Lixuan Xu, Rong Su

Abstract: We present a simple but effective method to extract the reflectivity spectra from the interference signals with a large NA white light interferometry. Numerical simulations and experiments have demonstrated the effectiveness of our method. Furthermore, some insights are also disclosed We present a simple but effective method to extract the reflectivity spectra from the interference signals with a large NA white light interferometry. Numerical simulations and experiments have demonstrated the effectiveness of our method. Furthermore, some insights are also disclosed △ Less

Submitted 8 March, 2025; originally announced March 2025.

Error Source Sensitivity Analysis in Model-Based Coherence Scanning Interferometry for Thin Film Metrology

Authors: Lixuan Xu, Cheng Chen, Rong Su

Abstract: In semiconductor manufacturing processes, silicon dioxide films are commonly used as barrier layers, insulating layers, and protective layers. Coherence scanning interferometry (CSI) offers thin film thickness measurements with a millimeter-scale field of view and micrometer-scale lateral resolution. When the film thickness is less than the coherence length of a CSI system, a model-based film thic… ▽ More In semiconductor manufacturing processes, silicon dioxide films are commonly used as barrier layers, insulating layers, and protective layers. Coherence scanning interferometry (CSI) offers thin film thickness measurements with a millimeter-scale field of view and micrometer-scale lateral resolution. When the film thickness is less than the coherence length of a CSI system, a model-based film thickness measurement method is typically employed, which relies on a priori information about the thin film and the instrument. This study quantitatively analyzes how the accuracy of a priori information would affect the accuracy of thickness measurement when using a model-based CSI method. The influence factors include camera noise, numerical aperture (NA), pupil apodization, light source spectrum, and thin film refractive index. A series of SiO$_2$/Si thin films with varying thicknesses are analyzed by combining simulation and experimental approaches. The results reveal that the accuracy of thickness measurements exhibits varying sensitivity to different a priori information. The refractive index of the thin film is identified as the most sensitive source of error, where 1\% deviation in refractive index may cause 1\% relative thickness error, whereas 5\% deviation in NA results in less than 1\% relative thickness error. The simulation and experimental results show good agreement, validating the correctness and effectiveness of this study. △ Less

Submitted 8 March, 2025; originally announced March 2025.

DispFormer: A Pretrained Transformer Incorporating Physical Constraints for Dispersion Curve Inversion

Authors: Feng Liu, Bao Deng, Rui Su, Lei Bai, Wanli Ouyang

Abstract: Surface wave dispersion curve inversion is crucial for estimating subsurface shear-wave velocity (vs), yet traditional methods often face challenges related to computational cost, non-uniqueness, and sensitivity to initial models. While deep learning approaches show promise, many require large labeled datasets and struggle with real-world datasets, which often exhibit varying period ranges, missin… ▽ More Surface wave dispersion curve inversion is crucial for estimating subsurface shear-wave velocity (vs), yet traditional methods often face challenges related to computational cost, non-uniqueness, and sensitivity to initial models. While deep learning approaches show promise, many require large labeled datasets and struggle with real-world datasets, which often exhibit varying period ranges, missing values, and low signal-to-noise ratios. To address these limitations, this study introduces DispFormer, a transformer-based neural network for $v_s$ profile inversion from Rayleigh-wave phase and group dispersion curves. DispFormer processes dispersion data independently at each period, allowing it to handle varying lengths without requiring network modifications or strict alignment between training and testing datasets. A depth-aware training strategy is also introduced, incorporating physical constraints derived from the depth sensitivity of dispersion data. DispFormer is pre-trained on a global synthetic dataset and evaluated on two regional synthetic datasets using zero-shot and few-shot strategies. Results show that even without labeled data, the zero-shot DispFormer generates inversion profiles that outperform the interpolated reference model used as the pretraining target, providing a deployable initial model generator to assist traditional workflows. When partial labeled data available, the few-shot trained DispFormer surpasses traditional global search methods. Real-world tests further confirm that DispFormer generalizes well to dispersion data with varying lengths and achieves lower data residuals than reference models. These findings underscore the potential of DispFormer as a foundation model for dispersion curve inversion and demonstrate the advantages of integrating physics-informed deep learning into geophysical applications. △ Less

Submitted 7 September, 2025; v1 submitted 8 January, 2025; originally announced January 2025.

Comments: 20 pages, 12 figures, related codes and data are available at https://github.com/liufeng2317/DispFormer

Journal ref: Journal of Geophysical Research: Machine Learning and Computation, 2, e2025JH000648 (2025)

Room temperature spin-layer locking of exciton-polariton nonlinearities

Authors: Jiaxin Zhao, Antonio Fieramosca, Kevin Dini, Qiuyu Shang, Ruiqi Bao, Yuan Luo, Kaijun Shen, Yang Zhao, Rui Su, Jesus Zuniga Perez, Weibo Gao, Vincenzo Ardizzone, Daniele Sanvitto, Qihua Xiong, Timothy C. H. Liew

Abstract: Recent advancements in transition metal dichalcogenides (TMDs) have unveiled exceptional optical and electronic characteristics, opened up new opportunities, and provided a unique platform for exploring light-matter interactions under the strong coupling regime. The exploitation of exciton-polaritons, with their peculiar hybrid light-matter properties, for the development of spintronic customizabl… ▽ More Recent advancements in transition metal dichalcogenides (TMDs) have unveiled exceptional optical and electronic characteristics, opened up new opportunities, and provided a unique platform for exploring light-matter interactions under the strong coupling regime. The exploitation of exciton-polaritons, with their peculiar hybrid light-matter properties, for the development of spintronic customizable devices that enhance both the information capacity and functionality at ambient temperatures is often suggested as a promising route. However, although TMD polaritons have shown promising potential, the microscopic mechanisms leading to nonlinearities in TMD polaritons are complex and their spin-anisotropy, a crucial requirement for many proposed polaritonic devices, has been missing. Here, we demonstrate the absence of spin-anisotropic interaction in a monolayer WS2 microcavity (at room temperature) and show how spin-dependent interactions can be controlled and spin anisotropy recovered by engineering double WS2 layer structures with varied interlayer spacing. We attribute this phenomenon to a distinctive feature in exciton-polariton physics: layer-dependent polariton-phonon coupling. We use theoretical calculations of the phonon electrostatic potentials finding a drastically different coupling strength for single and double monolayer samples and discuss qualitatively how this explains the observed spin-anisotropic response. This is further consistent with experiments on multi WS2 layer samples and the identification of a critical separation distance, above which an effective single monolayer spin-anisotropic response is recovered, both in experiment and theory. Our work lays the groundwork for the development of spin-optronic polaritonic devices at room temperature. △ Less

Submitted 24 October, 2024; originally announced October 2024.

Optical alignment of contamination-sensitive Far-Ultraviolet spectrographs for Aspera SmallSat mission

Authors: Aafaque R. Khan, Erika Hamden, Haeun Chung, Heejoo Choi, Daewook Kim, Nicole Melso, Keri Hoadley, Carlos J. Vargas, Daniel Truong, Elijah Garcia, Bill Verts, Fernando Coronado, Jamison Noenickx, Jason Corliss, Hannah Tanquary, Tom Mcmahon, Dave Hamara, Simran Agarwal, Ramona Augustin, Peter Behroozi, Harrison Bradley, Trenton Brendel, Joe Burchett, Jasmine Martinez Castillo, Jacob Chambers , et al. (26 additional authors not shown)

Abstract: Aspera is a NASA Astrophysics Pioneers SmallSat mission designed to study diffuse OVI emission from the warm-hot phase gas in the halos of nearby galaxies. Its payload consists of two identical Rowland Circle-type long-slit spectrographs, sharing a single MicroChannel plate detector. Each spectrograph channel consists of an off-axis parabola primary mirror and a toroidal diffraction grating optimi… ▽ More Aspera is a NASA Astrophysics Pioneers SmallSat mission designed to study diffuse OVI emission from the warm-hot phase gas in the halos of nearby galaxies. Its payload consists of two identical Rowland Circle-type long-slit spectrographs, sharing a single MicroChannel plate detector. Each spectrograph channel consists of an off-axis parabola primary mirror and a toroidal diffraction grating optimized for the 1013-1057 Angstroms bandpass. Despite the simple configuration, the optical alignment/integration process for Aspera is challenging due to tight optical alignment tolerances, driven by the compact form factor, and the contamination sensitivity of the Far-Ultraviolet optics and detectors. In this paper, we discuss implementing a novel multi-phase approach to meet these requirements using state-of-the-art optical metrology tools. For coarsely positioning the optics we use a blue-laser 3D scanner while the fine alignment is done with a Zygo interferometer and a custom computer-generated hologram. The detector focus requires iterative in-vacuum alignment using a Vacuum UV collimator. The alignment is done in a controlled cleanroom facility at the University of Arizona. △ Less

Submitted 22 July, 2024; originally announced July 2024.

Comments: Manuscript submitted for Proceedings of Astronomical Telescopes + Instrumentation 2024, Paper no. 13093-9

Trembling Motion of Exciton-Polaritons Close to the Rashba-Dresselhaus Regime

Authors: Wen Wen, Jie Liang, Huawen Xu, Feng Jin, Yuri G. Rubo, Timothy C. H. Liew, Rui Su

Abstract: We report the experimental emulation of trembling quantum motion, or Zitterbewegung, of exciton polaritons in a perovskite microcavity at room temperature. By introducing liquid crystal molecules into the microcavity, we achieve spinor states with synthetic Rashba-Dresselhaus spin-orbit coupling and tunable energy splitting. Under a resonant excitation, the polariton fluid exhibits clear trembling… ▽ More We report the experimental emulation of trembling quantum motion, or Zitterbewegung, of exciton polaritons in a perovskite microcavity at room temperature. By introducing liquid crystal molecules into the microcavity, we achieve spinor states with synthetic Rashba-Dresselhaus spin-orbit coupling and tunable energy splitting. Under a resonant excitation, the polariton fluid exhibits clear trembling motion perpendicular to its flowing direction, accompanied by a unique spin pattern resembling interlocked fingers. Furthermore, leveraging on the sizable tunability of energy gaps by external electrical voltages, we observe the continuous transition of polariton Zitterbewegung from relativistic (small gaps) to non-relativistic (large gaps) regimes. Our findings pave the way for using exciton polaritons in the emulation of relativistic quantum physics. △ Less

Submitted 30 May, 2024; originally announced May 2024.

Journal ref: Phys. Rev. Lett. 133, 116903 (2024)

Observation of perovskite topological valley exciton-polaritons at room temperature

Authors: Feng Jin, Subhaskar Mandal, Zhenhan Zhang, Jinqi Wu, Wen Wen, Jiahao Ren, Baile Zhang, Timothy C. H. Liew, Qihua Xiong, Rui Su

Abstract: Topological exciton-polaritons are a burgeoning class of topological photonic systems distinguished by their hybrid nature as part-light, part-matter quasiparticles. Their further control over novel valley degree of freedom (DOF) has offered considerable potential for developing active topological optical devices towards information processing. However, the experimental demonstration of propagatin… ▽ More Topological exciton-polaritons are a burgeoning class of topological photonic systems distinguished by their hybrid nature as part-light, part-matter quasiparticles. Their further control over novel valley degree of freedom (DOF) has offered considerable potential for developing active topological optical devices towards information processing. However, the experimental demonstration of propagating topological exciton-polaritons with valley DOF remains elusive at room temperature. Here, employing a two-dimensional (2D) valley-Hall perovskite lattice, we report the experimental observation of valley-polarized topological exciton-polaritons and their valley-dependent propagations at room temperature. The 2D valley-Hall perovskite lattice consists of two mutually inverted honeycomb lattices with broken inversion symmetry. By measuring their band structure with angle-resolved photoluminescence spectra, we experimentally verify the existence of valley-polarized polaritonic topological kink states with a large gap opening of ~ 9 meV in the bearded interface at room temperature. Moreover, these valley-polarized states exhibit counter-propagating behaviors under a resonant excitation at room temperature. Our results not only expand the landscape of realizing topological exciton-polaritons, but also pave the way for the development of topological valleytronic devices employing exciton-polaritons with valley DOF at room temperature △ Less

Submitted 25 May, 2024; originally announced May 2024.

Perovskite topological exciton-polariton disclination laser at room temperature

Authors: Feng Jin, Subhaskar Mandal, Xutong Wang, Baile Zhang, Rui Su

Abstract: Topologically nontrivial systems can be protected by band topology in momentum space, as seen in topological insulators and semimetals, or real-space topology, such as in lattice deformations known as topological disclinations (TDs). TDs, with inherent chiral symmetry, can support localized states pinned spectrally to the middle of the topological gap, preventing hybridization with bulk bands, and… ▽ More Topologically nontrivial systems can be protected by band topology in momentum space, as seen in topological insulators and semimetals, or real-space topology, such as in lattice deformations known as topological disclinations (TDs). TDs, with inherent chiral symmetry, can support localized states pinned spectrally to the middle of the topological gap, preventing hybridization with bulk bands, and making them promising for topological lasers. Here, we experimentally realize a C4v symmetric TD laser based on perovskite exciton-polariton lattices at room temperature. Protected by the chiral and point group symmetries of the lattice, the TD state emerges in the middle of the gap and at the core of the perovskite lattice. Under a non-resonant pulsed excitation, coherent polariton lasing occurs precisely at the TD state with a low threshold of 9.5 uJ/cm2, as confirmed by momentum space and real space spectra measurements. This study not only introduces a class of symmetry-protected topological lasers, but also expands the landscape for exploring exciton-polariton light-matter interactions with novel topological structures. △ Less

Submitted 28 April, 2024; originally announced April 2024.

Ultra-broadband near-field Josephson microwave microscopy

Authors: Ping Zhang, Yang-Yang Lyu, Jingjing Lv, Zihan Wei, Shixian Chen, Chenguang Wang, Hongmei Du, Dingding Li, Zixi Wang, Shoucheng Hou, Runfeng Su, Hancong Sun, Yuan Du, Li Du, Liming Gao, Yong-Lei Wang, Huabing Wang, Peiheng Wu

Abstract: Advanced microwave technologies constitute the foundation of a wide range of modern sciences, including quantum computing, microwave photonics, spintronics, etc. To facilitate the design of chip-based microwave devices, there is an increasing demand for state-of-the-art microscopic techniques capable of characterizing the near-field microwave distribution and performance. In this work, we integrat… ▽ More Advanced microwave technologies constitute the foundation of a wide range of modern sciences, including quantum computing, microwave photonics, spintronics, etc. To facilitate the design of chip-based microwave devices, there is an increasing demand for state-of-the-art microscopic techniques capable of characterizing the near-field microwave distribution and performance. In this work, we integrate Josephson junctions onto a nano-sized quartz tip, forming a highly sensitive microwave mixer on-tip. This allows us to conduct spectroscopic imaging of near-field microwave distributions with high spatial resolution. Leveraging its microwave-sensitive characteristics, our Josephson microscope achieves a broad detecting bandwidth of up to 200 GHz with remarkable frequency and intensity sensitivities. Our work emphasizes the benefits of utilizing the Josephson microscope as a real-time, non-destructive technique to advance integrated microwave electronics. △ Less

Submitted 23 January, 2024; originally announced January 2024.

Single-Shot Readout of a Nuclear Spin in Silicon Carbide

Authors: Xiao-Yi Lai, Ren-Zhou Fang, Tao Li, Ren-Zhu Su, Jia Huang, Hao Li, Li-Xing You, Xiao-Hui Bao, Jian-Wei Pan

Abstract: Solid-state qubits with a photonic interface is very promising for quantum networks. Color centers in silicon carbide have shown excellent optical and spin coherence, even when integrated with membranes and nano-structures. Additionally, nuclear spins coupled with electron spins can serve as long-lived quantum memories. Pioneering work in previous has realized the initialization of a single nuclea… ▽ More Solid-state qubits with a photonic interface is very promising for quantum networks. Color centers in silicon carbide have shown excellent optical and spin coherence, even when integrated with membranes and nano-structures. Additionally, nuclear spins coupled with electron spins can serve as long-lived quantum memories. Pioneering work in previous has realized the initialization of a single nuclear spin and demonstrated its entanglement with an electron spin. In this paper, we report the first realization of single-shot readout for a nuclear spin in SiC. We obtain a deterministic readout fidelity of 98.2% with a measurement duration of 1.13 ms. With a dual-step readout scheme, we obtain a readout fidelity as high as 99.5% with a success efficiency of 89.8%. Our work complements the experimental toolbox of harnessing both electron and nuclear spins in SiC for future quantum networks. △ Less

Submitted 9 January, 2024; originally announced January 2024.

Comments: 5 pages, 4 figures

Journal ref: Phys. Rev. Lett. 132, 180803 (2024)

Experimental Generation of Spin-Photon Entanglement in Silicon Carbide

Authors: Ren-Zhou Fang, Xiao-Yi Lai, Tao Li, Ren-Zhu Su, Bo-Wei Lu, Chao-Wei Yang, Run-Ze Liu, Yu-Kun Qiao, Cheng Li, Zhi-Gang He, Jia Huang, Hao Li, Li-Xing You, Yong-Heng Huo, Xiao-Hui Bao, Jian-Wei Pan

Abstract: A solid-state approach for quantum networks is advantages, as it allows the integration of nanophotonics to enhance the photon emission and the utilization of weakly coupled nuclear spins for long-lived storage. Silicon carbide, specifically point defects within it, shows great promise in this regard due to the easy of availability and well-established nanofabrication techniques. Despite of remark… ▽ More A solid-state approach for quantum networks is advantages, as it allows the integration of nanophotonics to enhance the photon emission and the utilization of weakly coupled nuclear spins for long-lived storage. Silicon carbide, specifically point defects within it, shows great promise in this regard due to the easy of availability and well-established nanofabrication techniques. Despite of remarkable progresses made, achieving spin-photon entanglement remains a crucial aspect to be realized. In this paper, we experimentally generate entanglement between a silicon vacancy defect in silicon carbide and a scattered single photon in the zero-phonon line. The spin state is measured by detecting photons scattered in the phonon sideband. The photonic qubit is encoded in the time-bin degree-of-freedom and measured using an unbalanced Mach-Zehnder interferometer. Photonic correlations not only reveal the quality of the entanglement but also verify the deterministic nature of the entanglement creation process. By harnessing two pairs of such spin-photon entanglement, it becomes straightforward to entangle remote quantum nodes at long distance. △ Less

Submitted 29 November, 2023; originally announced November 2023.

Comments: 8 pages in total, 4 figures in the main text, 1 figure in the supplemental material

Journal ref: Phys. Rev. Lett. 132, 160801 (2024)

Ray computational ghost imaging based on rotational modulation method

Authors: Zhi Zhou, Sangang Li, Shan Liao, Sirun Gong, Rongrong Su, Chuxiang Zhao, Li Yang, Qi Liu, Yucheng Yan, Mingzhe Liu, Yi Cheng

Abstract: The CGI (CGI) has the potential of low cost, low dose, and high resolution, which is very attractive for the development of radiation imaging field. However, many sub-coding plates must be used in the modulation process, which greatly affects the development of CGI technology. In order to reduce the coding plates, we refer to the rotation method of computed tomography (CT), then propose a novel CG… ▽ More The CGI (CGI) has the potential of low cost, low dose, and high resolution, which is very attractive for the development of radiation imaging field. However, many sub-coding plates must be used in the modulation process, which greatly affects the development of CGI technology. In order to reduce the coding plates, we refer to the rotation method of computed tomography (CT), then propose a novel CGI method based on rotational modulation method of a single-column striped coding plate. This method utilizes the spatial variation of a single sub-coding plate (rotation) to realize multiple modulation of the ray field and improves the utilization rate of a single sub-coding plate. However, for this rotation scheme of CGI, the traditional binary modulation matrix is no longer applicable. To obtain the system matrix of the rotated striped coding plate, an area model based on beam boundaries is established. Subsequently, numerical and Monte Carlo simulations were conducted. The results reveal that our scheme enables high-quality imaging of N*N resolution objects using only N sub-coding plates, under both full-sampling and under-sampling scenarios. Moreover, our scheme demonstrates superiority over the Hadamard scheme in both imaging quality and the number of required sub-coding plates, whether in scenarios of full-sampling or under-sampling. Finally, an α ray imaging platform was established to further demonstrate the feasibility of the rotational modulation method. By employing our scheme, a mere 8 sub-coding plates were employed to achieve CGI of the radiation source intensity distribution, achieving a resolution of 8*8. Therefore, the novel ray CGI based on rotational modulation method can achieve high-quality imaging effect with fewer sub-coding plates, which has important practical value and research significance for promoting single-pixel radiation imaging technology. △ Less

Submitted 1 November, 2023; originally announced November 2023.

Multifunctional magnetic oxide-MoS$_2$ heterostructures on silicon

Authors: Allen Jian Yang, Liang Wu, Yanran Liu, Xinyu Zhang, Kun Han, Ying Huang, Shengyao Li, Xian Jun Loh, Qiang Zhu, Rui Su, Ce-Wen Nan, X. Renshaw Wang

Abstract: Correlated oxides and related heterostructures are intriguing for developing future multifunctional devices by exploiting their exotic properties, but their integration with other materials, especially on Si-based platforms, is challenging. Here, van der Waals heterostructures of La$_{0.7}$Sr$_{0.3}$MnO$_3$ (LSMO), a correlated manganite perovskite, and MoS$_2$ are demonstrated on Si substrates wi… ▽ More Correlated oxides and related heterostructures are intriguing for developing future multifunctional devices by exploiting their exotic properties, but their integration with other materials, especially on Si-based platforms, is challenging. Here, van der Waals heterostructures of La$_{0.7}$Sr$_{0.3}$MnO$_3$ (LSMO), a correlated manganite perovskite, and MoS$_2$ are demonstrated on Si substrates with multiple functions. To overcome the problems due to the incompatible growth process, technologies involving freestanding LSMO membranes and van der Waals force-mediated transfer are used to fabricate the LSMO-MoS$_2$ heterostructures. The LSMO-MoS$_2$ heterostructures exhibit a gate-tunable rectifying behavior, based on which metal-semiconductor field-effect transistors (MESFETs) with on-off ratios of over 104 can be achieved. The LSMO-MoS$_2$ heterostructures can function as photodiodes displaying considerable open-circuit voltages and photocurrents. In addition, the colossal magnetoresistance of LSMO endows the LSMO-MoS$_2$ heterostructures with an electrically tunable magnetoresponse at room temperature. This work not only proves the applicability of the LSMO-MoS$_2$ heterostructure devices on Si-based platform but also demonstrates a paradigm to create multifunctional heterostructures from materials with disparate properties. △ Less

Submitted 11 October, 2023; originally announced October 2023.

Journal ref: Advanced Materials 35, 2302620 (2023)

FengWu: Pushing the Skillful Global Medium-range Weather Forecast beyond 10 Days Lead

Authors: Kang Chen, Tao Han, Junchao Gong, Lei Bai, Fenghua Ling, Jing-Jia Luo, Xi Chen, Leiming Ma, Tianning Zhang, Rui Su, Yuanzheng Ci, Bin Li, Xiaokang Yang, Wanli Ouyang

Abstract: We present FengWu, an advanced data-driven global medium-range weather forecast system based on Artificial Intelligence (AI). Different from existing data-driven weather forecast methods, FengWu solves the medium-range forecast problem from a multi-modal and multi-task perspective. Specifically, a deep learning architecture equipped with model-specific encoder-decoders and cross-modal fusion Trans… ▽ More We present FengWu, an advanced data-driven global medium-range weather forecast system based on Artificial Intelligence (AI). Different from existing data-driven weather forecast methods, FengWu solves the medium-range forecast problem from a multi-modal and multi-task perspective. Specifically, a deep learning architecture equipped with model-specific encoder-decoders and cross-modal fusion Transformer is elaborately designed, which is learned under the supervision of an uncertainty loss to balance the optimization of different predictors in a region-adaptive manner. Besides this, a replay buffer mechanism is introduced to improve medium-range forecast performance. With 39-year data training based on the ERA5 reanalysis, FengWu is able to accurately reproduce the atmospheric dynamics and predict the future land and atmosphere states at 37 vertical levels on a 0.25° latitude-longitude resolution. Hindcasts of 6-hourly weather in 2018 based on ERA5 demonstrate that FengWu performs better than GraphCast in predicting 80\% of the 880 reported predictands, e.g., reducing the root mean square error (RMSE) of 10-day lead global z500 prediction from 733 to 651 $m^{2}/s^2$. In addition, the inference cost of each iteration is merely 600ms on NVIDIA Tesla A100 hardware. The results suggest that FengWu can significantly improve the forecast skill and extend the skillful global medium-range weather forecast out to 10.75 days lead (with ACC of z500 > 0.6) for the first time. △ Less

Submitted 6 April, 2023; originally announced April 2023.

Comments: 12 pages

Journal ref: Commun. Earth Environ. 6, 518 (2025)

Bright Semiconductor Single-Photon Sources Pumped by Heterogeneously Integrated Micropillar lasers with Electrical Injections

Authors: Xueshi Li, Shunfa Liu, Yuming Wei, Jiantao Ma, Changkun Song, Ying Yu, Rongbin Su, Wei Geng, Haiqiao Ni, Hanqing Liu, Xiangbin Su, Zhichuan Niu, Youling Chen, Jin Liu

Abstract: The emerging hybrid integrated quantum photonics combines advantages of different functional components into a single chip to meet the stringent requirements for quantum information processing. Despite the tremendous progress in hybrid integrations of III-V quantum emitters with silicon-based photonic circuits and superconducting single-photon detectors, on-chip optical excitations of quantum emit… ▽ More The emerging hybrid integrated quantum photonics combines advantages of different functional components into a single chip to meet the stringent requirements for quantum information processing. Despite the tremendous progress in hybrid integrations of III-V quantum emitters with silicon-based photonic circuits and superconducting single-photon detectors, on-chip optical excitations of quantum emitters via miniaturized lasers towards single-photon sources (SPSs) with low power consumptions, small device footprints and excellent coherence properties is highly desirable yet illusive. In this work, we present realizations of bright semiconductor singe-photon sources heterogeneously integrated with on-chip electrically-injected microlasers. Different from previous one-by-one transfer printing technique implemented in hybrid quantum dot (QD) photonic devices, multiple deterministically coupled QD-circular Bragg Grating (CBG) SPSs were integrated with electrically-injected micropillar lasers at one time via a potentially scalable transfer printing process assisted by the wide-field photoluminescence (PL) imaging technique. Optically pumped by electrically-injected microlasers, pure single photons are generated with a high-brightness of a count rate of 3.8 M/s and an extraction efficiency of 25.44%. Such a high-brightness is due to the enhancement by the cavity mode of the CBG, which is confirmed by a Purcell factor of 2.5. Our work provides a powerful tool for advancing hybrid integrated quantum photonics in general and boosts the developments for realizing highly-compact, energy-efficient and coherent SPSs in particular. △ Less

Submitted 3 February, 2023; originally announced February 2023.

Unveiling the Enhancement of Spontaneous Emission at Exceptional Points

Authors: Lydie Ferrier, Paul Bouteyre, Adi Pick, Sébastien Cueff, Nguyen Ha My Dang, Carole Diederichs, Ali Belarouci, Taha Benyattou, Jiaxin Zhao, Rui Su, Jun Xing, Qihua Xiong, Hai-Son Nguyen

Abstract: Exceptional points (EPs), singularities of non-Hermitian physics where complex spectral resonances degenerate, are one of the most exotic features of nonequilibrium open systems with unique properties. For instance, the emission rate of quantum emitters placed near resonators with EPs is enhanced (compared to the free-space emission rate) by a factor that scales quadratically with the resonance qu… ▽ More Exceptional points (EPs), singularities of non-Hermitian physics where complex spectral resonances degenerate, are one of the most exotic features of nonequilibrium open systems with unique properties. For instance, the emission rate of quantum emitters placed near resonators with EPs is enhanced (compared to the free-space emission rate) by a factor that scales quadratically with the resonance quality factor. Here, we verify the theory of spontaneous emission at EPs by measuring photoluminescence from photonic-crystal slabs that are embedded with a high-quantum-yield active material. While our experimental results verify the theoretically predicted enhancement, it also highlights the practical limitations on the enhancement due to material loss. Our designed structures can be used in applications that require enhanced and controlled emission, such as quantum sensing and imaging. △ Less

Submitted 16 July, 2022; v1 submitted 4 March, 2022; originally announced March 2022.

Direct Measurement of a Non-Hermitian Topological Invariant in a Hybrid Light-Matter System

Authors: Rui Su, Eliezer Estrecho, Dąbrówka Biegańska, Yuqing Huang, Matthias Wurdack, Maciej Pieczarka, Andrew G. Truscott, Timothy C. H. Liew, Elena A. Ostrovskaya, Qihua Xiong

Abstract: Topology is central to understanding and engineering materials that display robust physical phenomena immune to imperfections. Different topological phases of matter are characterised by topological invariants. In energy-conserving (Hermitian) systems, these invariants are determined by the winding of eigenstates in momentum space. In non-Hermitian systems, a novel topological invariant is predict… ▽ More Topology is central to understanding and engineering materials that display robust physical phenomena immune to imperfections. Different topological phases of matter are characterised by topological invariants. In energy-conserving (Hermitian) systems, these invariants are determined by the winding of eigenstates in momentum space. In non-Hermitian systems, a novel topological invariant is predicted to emerge from the winding of the complex eigenenergies. Here, we directly measure the non-Hermitian topological invariant arising from exceptional points in the momentum-resolved spectrum of exciton polaritons. These are hybrid light-matter quasiparticles formed by photons strongly coupled to electron-hole pairs (excitons) in a halide perovskite semiconductor at room temperature. We experimentally map out both the real (energy) and imaginary (linewidth) parts of the spectrum near the exceptional points and extract the novel topological invariant - fractional spectral winding. Our work represents an essential step towards realisation of non-Hermitian topological phases in a condensed matter system. △ Less

Submitted 17 November, 2021; v1 submitted 11 December, 2020; originally announced December 2020.

Journal ref: Sci. Adv. 7, eabj8905 (2021)

Optical Control of Topological Polariton Phase in a Perovskite Lattice

Authors: Rui Su, Sanjib Ghosh, Timothy C. H. Liew, Qihua Xiong

Abstract: Strong light-matter interaction enriches topological photonics by dressing light with matter, which provides the possibility to realize tuneable topological devices with immunity to defects. Topological exciton polaritons, half-light half-matter quasiparticles with giant optical nonlinearity represent a unique platform for active topological photonics with phase tunability. Previous demonstrations… ▽ More Strong light-matter interaction enriches topological photonics by dressing light with matter, which provides the possibility to realize tuneable topological devices with immunity to defects. Topological exciton polaritons, half-light half-matter quasiparticles with giant optical nonlinearity represent a unique platform for active topological photonics with phase tunability. Previous demonstrations of exciton polariton topological insulators still demand cryogenic temperatures and their topological properties are usually fixed without phase tunability. Here, we experimentally demonstrate a room-temperature exciton polariton topological insulator with active phase tunability in a perovskite zigzag lattice. Polarization serves as a degree of freedom to control the reversible transition between distinct topological phases, thanks to the polarization-dependent anisotropy in halide perovskite microcavities. The topologically nontrivial polariton states localized in the edges persist in the presence of a natural defect, showing strong immunity to disorder. We further demonstrate that exciton polaritons can condense into the topological edge states under optical pumping. These results provide an ideal platform for realizing tuneable topological polaritonic devices with room-temperature operation, which can find important applications in optical control, modulation and switching. △ Less

Submitted 10 December, 2020; originally announced December 2020.

Ultralow Threshold Polariton Condensate in a Monolayer Semiconductor Microcavity at Room Temperature

Authors: Jiaxin Zhao, Rui Su, Antonio Fieramosca, Weijie Zhao, Wei Du, Xue Liu, Carole Diederichs, Daniele Sanvitto, Timothy C. H. Liew, Qihua Xiong

Abstract: Atomically thin transition metal dichalcogenides possess valley dependent functionalities that are usually available only at crogenic temperatures, constrained by various valley depolarization scatterings. The formation of exciton polaritons by coherently superimposing excitons and microcavity photons potentially harnesses the valley polarized polariton polariton interactions for novel valleytroni… ▽ More Atomically thin transition metal dichalcogenides possess valley dependent functionalities that are usually available only at crogenic temperatures, constrained by various valley depolarization scatterings. The formation of exciton polaritons by coherently superimposing excitons and microcavity photons potentially harnesses the valley polarized polariton polariton interactions for novel valleytronics devices. Robust EPs have been demonstrated at room temperature in TMDs microcavity, however, the coherent polariton lasing and condensation remain elusive. Herein, we demonstrate for the first time the realization of EP condensation in a TMD microcavity at room temperature. The continuous wave pumped EP condensation and lasing with ultralow thresholdsis evidenced by the macroscopic occupation of the ground state, that undergoes a nonlinear increase of the emission and a continuous blueshift, a build up of spatial coherence, and a detuning-controlled threshold. Our work presents a critically important step towards exploiting nonlinear polariton polariton interactions and polaritonic devices with valley functionality at room temperature. △ Less

Submitted 9 October, 2020; originally announced October 2020.

Comments: 21 pages, 5 figures

Correlative infrared optical coherence tomography and hyperspectral chemical imaging

Authors: Ivan Zorin, Rong Su, Bettina Heise, Bernhard Lendl, Markus Brandstetter

Abstract: Optical coherence tomography (OCT) is a high-resolution three-dimensional imaging technique that enables non-destructive measurements of surface and subsurface microstructures. Recent developments of OCT operating in the mid-infrared (MIR) range (around 4 μm) lifted fundamental scattering limitations and initiated applied material research in formerly inaccessible fields. The MIR spectral region,… ▽ More Optical coherence tomography (OCT) is a high-resolution three-dimensional imaging technique that enables non-destructive measurements of surface and subsurface microstructures. Recent developments of OCT operating in the mid-infrared (MIR) range (around 4 μm) lifted fundamental scattering limitations and initiated applied material research in formerly inaccessible fields. The MIR spectral region, however, is also of great interest for spectroscopy and hyperspectral imaging, which allow highly selective and sensitive chemical studies of materials. In this contribution, we introduce an OCT system (dual-band, central wavelengths of 2 μm m and 4 μm) combined with MIR spectroscopy that is implemented as a raster scanning chemical imaging modality. The fully-integrated and cost-effective optical instrument is based on a single supercontinuum laser source (emission spectrum spanning from 1.1 μm to 4.4 μm). Capabilities of the in-situ correlative measurements are experimentally demonstrated by obtaining complex multidimensional material data, comprising morphological and chemical information, from a multi-layered composite ceramic-polymer specimen. △ Less

Submitted 5 June, 2020; originally announced June 2020.

Comments: 12 pages, 9 figures

Observation of Exciton Polariton Condensation in a Perovskite Lattice at Room Temperature

Authors: Rui Su, Sanjib Ghosh, Sheng Liu, Carole Diederichs, Timothy C. H. Liew, Qihua Xiong

Abstract: Bose-Einstein condensation in strongly correlated lattices provides the possibility to coherently generate macroscopic quantum states, which have attracted tremendous attention as ideal platforms for quantum simulation. Ultracold atoms in optical lattices are one of such promising systems, where their realizations of different phases of matter exhibit promising applications in condensed matter phy… ▽ More Bose-Einstein condensation in strongly correlated lattices provides the possibility to coherently generate macroscopic quantum states, which have attracted tremendous attention as ideal platforms for quantum simulation. Ultracold atoms in optical lattices are one of such promising systems, where their realizations of different phases of matter exhibit promising applications in condensed matter physics, chemistry, and cosmology. Nevertheless, this is only accessible with ultralow temperatures in the nano to micro Kelvin scale set by the typical inverse mass of an atom. Alternative systems such as lattices of trapped ions and superconducting circuit arrays also rely on ultracold temperatures. Exciton polaritons with extremely light effective mass, are regarded as promising alternatives to realize Bose-Einstein condensation in lattices at higher temperatures. Along with the condensation, an efficient exciton polariton quantum simulator would require a strong lattice with robust trapping at each lattice site as well as strong inter-site coupling to allow coherent quantum motion of polaritons within the lattice. However, exciton polaritons in a strong lattice have only been shown to condense at liquid helium temperatures. Here, we report the observation of exciton polariton condensation in a one-dimensional strong lead halide perovskite lattice at room temperature. Modulated by deep periodic potentials, the strong lead halide perovskite lattice exhibits a large forbidden bandgap opening up to 13.3 meV and a lattice band up to 8.5 meV wide, which are at least 10 times larger than previous systems. Above a critical density, we observe exciton polariton condensation into py orbital states with long-range spatial coherence at room temperature. Our result opens the route to the implementation of polariton condensates in quantum simulators at room temperature. △ Less

Submitted 27 June, 2019; originally announced June 2019.

A Multi-Modal Miniature Surface Forces Apparatus (uSFA) for Interfacial Science Measurements

Authors: Kai Kristiansen, Stephen H. Donaldson Jr., Zachariah J. Berkson, Jeffrey Scott, Rongxin Su, Xavier Banquy, Dong Woog Lee, Hilton B. de Aguiar, Joshua D. McGraw, George D. Degen, Jacob N. Israelachvili

Abstract: Advances in the research of intermolecular and surface interactions result from the development of new and improved measurement techniques and combinations of existing techniques. Here, we present a new miniature version of the Surface Force Apparatus (the uSFA) that has been designed for ease of use and multi-modal capabilities with retention of the capabilities of other SFA models including accu… ▽ More Advances in the research of intermolecular and surface interactions result from the development of new and improved measurement techniques and combinations of existing techniques. Here, we present a new miniature version of the Surface Force Apparatus (the uSFA) that has been designed for ease of use and multi-modal capabilities with retention of the capabilities of other SFA models including accurate measurement of surface separation distance and physical characterization of dynamic and static physical forces (i.e., normal, shear, and friction) and interactions (e.g., van der Waals, electrostatic, hydrophobic, steric, biospecific). The small physical size of the uSFA, compared to previous SFA models, makes it portable and suitable for integration into commercially available optical and fluorescence light microscopes, as demonstrated here. The large optical path entry and exit ports make it ideal for concurrent force measurements and spectroscopy studies. Examples of the use of the uSFA in combination with surface plasmon resonance (SPR) and Raman spectroscopy measurements are presented. Due to the short working distance constraints associated with Raman spectroscopy, an interferometric technique was developed and applied for calculating the inter-surface separation distance based on Newtons rings. The introduction of the \muSFA will mark a transition in SFA usage from primarily physical characterization to concurrent physical characterization with in situ chemical and biological characterization to study interfacial phenomena, including (but not limited to) molecular adsorption, fluid flow dynamics, determination of surface species and morphology, and (bio) molecular binding kinetics. △ Less

Submitted 14 June, 2019; originally announced June 2019.

Comments: 38 pages, 11 figures

Deep learning-based phase control method for coherent beam combining and its application in generating orbital angular momentum beams

Authors: Tianyue Hou, Yi An, Qi Chang, Pengfei Ma, Jun Li, Liangjin Huang, Dong Zhi, Jian Wu, Rongtao Su, Yanxing Ma, Pu Zhou

Abstract: We incorporate deep learning (DL) into coherent beam combining (CBC) systems for the first time, to the best of our knowledge. Using a well-trained convolutional neural network DL model, the phase error in CBC systems could be accurately estimated and preliminarily compensated. Then, the residual phase error is further compensated by stochastic parallel gradient descent (SPGD) algorithms. The two-… ▽ More We incorporate deep learning (DL) into coherent beam combining (CBC) systems for the first time, to the best of our knowledge. Using a well-trained convolutional neural network DL model, the phase error in CBC systems could be accurately estimated and preliminarily compensated. Then, the residual phase error is further compensated by stochastic parallel gradient descent (SPGD) algorithms. The two-stage phase control strategy combined with DL and SPGD algorithms is validated to be a feasible and promising technique to alleviate the long-standing problem that the phase control bandwidth decreases as the number of array elements expands. Further investigation denotes that the proposed phase control technique could be employed to generate orbital angular momentum (OAM) beams with different orders by distinguishing the OAM beams of conjugated phase distributions. △ Less

Submitted 10 March, 2019; originally announced March 2019.

Enhanced Emission from WSe2 Monolayers Coupled to Circular Bragg Gratings

Authors: Ngoc My Hanh Duong, Zai-Quan Xu, Mehran Kianinia, Rongbin Su, Zhuojun Liu, Sejeong Kim, Carlo Bradac, Lain-Jong Li, Alexander Solntsev, Jin Liu, Igor Aharonovich

Abstract: Two-dimensional transition-metal dichalcogenides (TMDC) are of great interest for on-chip nanophotonics due to their unique optoelectronic properties. Here, we propose and realize coupling of tungsten diselenide (WSe2) monolayers to circular Bragg grating structures to achieve enhanced emission. The interaction between WSe2 and the resonant mode of the structure results in Purcell-enhanced emissio… ▽ More Two-dimensional transition-metal dichalcogenides (TMDC) are of great interest for on-chip nanophotonics due to their unique optoelectronic properties. Here, we propose and realize coupling of tungsten diselenide (WSe2) monolayers to circular Bragg grating structures to achieve enhanced emission. The interaction between WSe2 and the resonant mode of the structure results in Purcell-enhanced emission, while the symmetric geometrical structure improves the directionality of the out-coupling stream of emitted photons. Furthermore, this hybrid structure produces a record high contrast of the spin valley readout (> 40%) revealed by the polarization resolved photoluminescence (PL) measurements. Our results are promising for on-chip integration of TMDC monolayers with optical resonators for nanophotonic circuits. △ Less

Submitted 18 June, 2018; originally announced June 2018.

Highly efficient visible colloidal lead-halide perovskite nanocrystal light-emitting diodes

Authors: Fei Yan, Jun Xing, Guichuan Xing, Lina Quan, Swee Tiam Tan, Jiaxin Zhao, Rui Su, Lulu Zhang, Shi Chen, Yawen Zhao, Alfred Huan, Edward H. Sargent, Qihua Xiong, Hilmi Volkan Demir

Abstract: Lead-halide perovskites have been attracting attention for potential use in solid-state lighting. Following the footsteps of solar cells, the field of perovskite light-emitting diodes (PeLEDs) has been growing rapidly. Their application prospects in lighting, however, remain still uncertain due to a variety of shortcomings in device performance including their limited levels of luminous efficiency… ▽ More Lead-halide perovskites have been attracting attention for potential use in solid-state lighting. Following the footsteps of solar cells, the field of perovskite light-emitting diodes (PeLEDs) has been growing rapidly. Their application prospects in lighting, however, remain still uncertain due to a variety of shortcomings in device performance including their limited levels of luminous efficiency achievable thus far. Here we show high-efficiency PeLEDs based on colloidal perovskite nanocrystals (PeNCs) synthesized at room temperature possessing dominant first-order excitonic radiation (enabling a photoluminescence quantum yield of 71% in solid film), unlike in the case of bulk perovskites with slow electron-hole bimolecular radiative recombination (a second-order process). In these PeLEDs, by reaching charge balance in the recombination zone, we find that the Auger nonradiative recombination, with its significant role in emission quenching, is effectively suppressed in low driving current density range. In consequence, these devices reach a record high maximum external quantum efficiency of 12.9% reported to date and an unprecedentedly high power efficiency of 30.3 lm W-1 at luminance levels above 1000 cd m-2 as required for various applications. These findings suggest that, with feasible levels of device performance, the PeNCs hold great promise for their use in LED lighting and displays. △ Less

Submitted 31 January, 2018; originally announced January 2018.

Optical positioning of single quantum dots in micropillar with >65% extraction efficiency for on-demand quantum light sources

Authors: Shun-Fa Liu, Yu-Ming Wei, Rong-Ling Su, Rong-Bin Su, Ben Ma, Ze-Sheng Chen, Hai-Qiao Ni, Zhi-Chuan Niu, Ying Yu, Yu-Jia Wei, Xue-hua Wang, Si-yuan Yu

Abstract: We report optical positioning single quantum dots (QDs) in planar cavity with an average position uncertainty $<$20 nm using an optimized two-color photoluminescence imaging technique. We create single-photon sources based on these QDs in determined micropillar cavities. The brightness of the QD fluorescence is greatly enhanced on resonance with the fundamental mode of the cavity, leading to an hi… ▽ More We report optical positioning single quantum dots (QDs) in planar cavity with an average position uncertainty $<$20 nm using an optimized two-color photoluminescence imaging technique. We create single-photon sources based on these QDs in determined micropillar cavities. The brightness of the QD fluorescence is greatly enhanced on resonance with the fundamental mode of the cavity, leading to an high extraction efficiency of 68%$\pm$6% into a lens with numerical aperture of 0.65, and simultaneously exhibiting low multi-photon probability ($g^{2}(0)$=0.144$\pm$0.012) at this collection efficiency. △ Less

Submitted 10 February, 2017; v1 submitted 24 December, 2016; originally announced December 2016.

Comments: 11 pages, 4 figures

Efficient silicon metasurfaces for visible light

Authors: Zhenpeng Zhou, Juntao Li, Rongbin Su, Beimeng Yao, Hanlin Fang, Kezheng Li, Lidan Zhou, Jin Liu, Daan Stellinga, Christopher P Reardon, Thomas F Krauss, Xuehua Wang

Abstract: Dielectric metasurfaces require high refractive index contrast materials for optimum performance. This requirement imposes a severe restraint; devices have either been demonstrated at wavelengths of 700nm and above using high-index semiconductors such as silicon, or they use lower index dielectric materials such as TiO$_{2}$ or Si$_{3}$N$_{4}$ and operate in the visible wavelength regime. Here, we… ▽ More Dielectric metasurfaces require high refractive index contrast materials for optimum performance. This requirement imposes a severe restraint; devices have either been demonstrated at wavelengths of 700nm and above using high-index semiconductors such as silicon, or they use lower index dielectric materials such as TiO$_{2}$ or Si$_{3}$N$_{4}$ and operate in the visible wavelength regime. Here, we show that the high refractive index of silicon can be exploited at wavelengths as short as 532 nm by demonstrating a silicon metasurface with a transmission efficiency of 47% at this wavelength. The metasurface consists of a graded array of silicon posts arranged in a square lattice on a quartz substrate. We show full 2π phase control and we experimentally demonstrate polarization-independent beam deflection at 532nm wavelength. The crystalline silicon is placed on a quartz substrate by a bespoke layer transfer technique and we note that an efficiency >70% may be achieved for a further optimized structure in the same material. Our results open a new way for realizing efficient metasurfaces based on silicon in the visible wavelength regime. △ Less

Submitted 20 September, 2016; originally announced September 2016.

Comments: 16 pages, 6 figures, 2 tables

Controlling herding in minority game systems

Authors: Ji-Qiang Zhang, Zi-Gang Huang, Zhi-Xi Wu, Riqi Su, Ying-Cheng Lai

Abstract: Resource allocation takes place in various types of real-world complex systems such as urban traf- fic, social services institutions, economical and ecosystems. Mathematically, the dynamical process of complex resource allocation can be modeled as minority games in which the number of resources is limited and agents tend to choose the less used resource based on available information. Spontaneous… ▽ More Resource allocation takes place in various types of real-world complex systems such as urban traf- fic, social services institutions, economical and ecosystems. Mathematically, the dynamical process of complex resource allocation can be modeled as minority games in which the number of resources is limited and agents tend to choose the less used resource based on available information. Spontaneous evolution of the resource allocation dynamics, however, often leads to a harmful herding behavior accompanied by strong fluctuations in which a large majority of agents crowd temporarily for a few resources, leaving many others unused. Developing effective control strategies to suppress and elim- inate herding is an important but open problem. Here we develop a pinning control method. That the fluctuations of the system consist of intrinsic and systematic components allows us to design a control scheme with separated control variables. A striking finding is the universal existence of an optimal pinning fraction to minimize the variance of the system, regardless of the pinning patterns and the network topology. We carry out a detailed theoretical analysis to understand the emergence of optimal pinning and to predict the dependence of the optimal pinning fraction on the network topol- ogy. Our theory is generally applicable to systems with heterogeneous resource capacities as well as varying control and network topological parameters such as the average degree and the degree dis- tribution exponent. Our work represents a general framework to deal with the broader problem of controlling collective dynamics in complex systems with potential applications in social, economical and political systems. △ Less

Submitted 3 November, 2015; originally announced November 2015.

Comments: 18 pages, 8 figures

Control and controllability of nonlinear dynamical networks: a geometrical approach

Authors: Le-Zhi Wang, Ri-Qi Su, Zi-Gang Huang, Xiao Wang, Wenxu Wang, Celso Grebogi, Ying-Cheng Lai

Abstract: In spite of the recent interest and advances in linear controllability of complex networks, controlling nonlinear network dynamics remains to be an outstanding problem. We develop an experimentally feasible control framework for nonlinear dynamical networks that exhibit multistability (multiple coexisting final states or attractors), which are representative of, e.g., gene regulatory networks (GRN… ▽ More In spite of the recent interest and advances in linear controllability of complex networks, controlling nonlinear network dynamics remains to be an outstanding problem. We develop an experimentally feasible control framework for nonlinear dynamical networks that exhibit multistability (multiple coexisting final states or attractors), which are representative of, e.g., gene regulatory networks (GRNs). The control objective is to apply parameter perturbation to drive the system from one attractor to another, assuming that the former is undesired and the latter is desired. To make our framework practically useful, we consider RESTRICTED parameter perturbation by imposing the following two constraints: (a) it must be experimentally realizable and (b) it is applied only temporarily. We introduce the concept of ATTRACTOR NETWORK, in which the nodes are the distinct attractors of the system, and there is a directional link from one attractor to another if the system can be driven from the former to the latter using restricted control perturbation. Introduction of the attractor network allows us to formulate a controllability framework for nonlinear dynamical networks: a network is more controllable if the underlying attractor network is more strongly connected, which can be quantified. We demonstrate our control framework using examples from various models of experimental GRNs. A finding is that, due to nonlinearity, noise can counter-intuitively facilitate control of the network dynamics. △ Less

Submitted 23 September, 2015; originally announced September 2015.

Comments: 22 pages, 8 figures

Discrete Imaging Models for Three-Dimensional Optoacoustic Tomography using Radially Symmetric Expansion Functions

Authors: Kun Wang, Robert W Schoonover, Richard Su, Alexander Oraevsky, Mark A Anastasio

Abstract: Optoacoustic tomography (OAT), also known as photoacoustic tomography, is an emerging computed biomedical imaging modality that exploits optical contrast and ultrasonic detection principles. Iterative image reconstruction algorithms that are based on discrete imaging models are actively being developed for OAT due to their ability to improve image quality by incorporating accurate models of the im… ▽ More Optoacoustic tomography (OAT), also known as photoacoustic tomography, is an emerging computed biomedical imaging modality that exploits optical contrast and ultrasonic detection principles. Iterative image reconstruction algorithms that are based on discrete imaging models are actively being developed for OAT due to their ability to improve image quality by incorporating accurate models of the imaging physics, instrument response, and measurement noise. In this work, we investigate the use of discrete imaging models based on Kaiser-Bessel window functions for iterative image reconstruction in OAT. A closed-form expression for the pressure produced by a Kaiser-Bessel function is calculated, which facilitates accurate computation of the system matrix. Computer-simulation and experimental studies are employed to demonstrate the potential advantages of Kaiser-Bessel function-based iterative image reconstruction in OAT. △ Less

Submitted 8 May, 2014; v1 submitted 3 October, 2013; originally announced October 2013.

Journal ref: Medical Imaging, IEEE Transactions on , vol.33, no.5, pp.1180,1193, May 2014

Investigation of iterative image reconstruction in three-dimensional optoacoustic tomography

Authors: Kun wang, Richard Su, Alexander A. Oraevsky, Mark A. Anastasio

Abstract: Iterative image reconstruction algorithms for optoacoustic tomography (OAT), also known as photoacoustic tomography, have the ability to improve image quality over analytic algorithms due to their ability to incorporate accurate models of the imaging physics, instrument response, and measurement noise. However, to date, there have been few reported attempts to employ advanced iterative image recon… ▽ More Iterative image reconstruction algorithms for optoacoustic tomography (OAT), also known as photoacoustic tomography, have the ability to improve image quality over analytic algorithms due to their ability to incorporate accurate models of the imaging physics, instrument response, and measurement noise. However, to date, there have been few reported attempts to employ advanced iterative image reconstruction algorithms for improving image quality in three-dimensional (3D) OAT. In this work, we implement and investigate two iterative image reconstruction methods for use with a 3D OAT small animal imager: namely, a penalized least-squares (PLS) method employing a quadratic smoothness penalty and a PLS method employing a total variation norm penalty. The reconstruction algorithms employ accurate models of the ultrasonic transducer impulse responses. Experimental data sets are employed to compare the performances of the iterative reconstruction algorithms to that of a 3D filtered backprojection (FBP) algorithm. By use of quantitative measures of image quality, we demonstrate that the iterative reconstruction algorithms can mitigate image artifacts and preserve spatial resolution more effectively than FBP algorithms. These features suggest that the use of advanced image reconstruction algorithms can improve the effectiveness of 3D OAT while reducing the amount of data required for biomedical applications. △ Less

Submitted 15 July, 2012; v1 submitted 4 July, 2012; originally announced July 2012.

Journal ref: Phys. Med. Biol. 57 (2012) 5399-5423

Ultra accurate personalized recommendation via eliminating redundant correlations

Authors: Tao Zhou, Riqi Su, Runran Liu, Luoluo Jiang, Bing-Hong Wang, Yi-Cheng Zhang

Abstract: In this paper, based on a weighted projection of bipartite user-object network, we introduce a personalized recommendation algorithm, called the \emph{network-based inference} (NBI), which has higher accuracy than the classical algorithm, namely \emph{collaborative filtering}. In the NBI, the correlation resulting from a specific attribute may be repeatedly counted in the cumulative recommendati… ▽ More In this paper, based on a weighted projection of bipartite user-object network, we introduce a personalized recommendation algorithm, called the \emph{network-based inference} (NBI), which has higher accuracy than the classical algorithm, namely \emph{collaborative filtering}. In the NBI, the correlation resulting from a specific attribute may be repeatedly counted in the cumulative recommendations from different objects. By considering the higher order correlations, we design an improved algorithm that can, to some extent, eliminate the redundant correlations. We test our algorithm on two benchmark data sets, \emph{MovieLens} and \emph{Netflix}. Compared with the NBI, the algorithmic accuracy, measured by the ranking score, can be further improved by 23% for \emph{MovieLens} and 22% for \emph{Netflix}, respectively. The present algorithm can even outperform the \emph{Latent Dirichlet Allocation} algorithm, which requires much longer computational time. Furthermore, most of the previous studies considered the algorithmic accuracy only, in this paper, we argue that the diversity and popularity, as two significant criteria of algorithmic performance, should also be taken into account. With more or less the same accuracy, an algorithm giving higher diversity and lower popularity is more favorable. Numerical results show that the present algorithm can outperform the standard one simultaneously in all five adopted metrics: lower ranking score and higher precision for accuracy, larger Hamming distance and lower intra-similarity for diversity, as well as smaller average degree for popularity. △ Less

Submitted 12 June, 2009; v1 submitted 27 May, 2008; originally announced May 2008.

Comments: 20 pages, 10 figures, 2 tables

Journal ref: New Journal of Physics 11 (2009) 123008

Effect of initial configuration on network-based recommendation

Authors: Tao Zhou, Luo-Luo Jiang, Ri-Qi Su, Yi-Cheng Zhang

Abstract: In this paper, based on a weighted object network, we propose a recommendation algorithm, which is sensitive to the configuration of initial resource distribution. Even under the simplest case with binary resource, the current algorithm has remarkably higher accuracy than the widely applied global ranking method and collaborative filtering. Furthermore, we introduce a free parameter $β$ to regul… ▽ More In this paper, based on a weighted object network, we propose a recommendation algorithm, which is sensitive to the configuration of initial resource distribution. Even under the simplest case with binary resource, the current algorithm has remarkably higher accuracy than the widely applied global ranking method and collaborative filtering. Furthermore, we introduce a free parameter $β$ to regulate the initial configuration of resource. The numerical results indicate that decreasing the initial resource located on popular objects can further improve the algorithmic accuracy. More significantly, we argue that a better algorithm should simultaneously have higher accuracy and be more personal. According to a newly proposed measure about the degree of personalization, we demonstrate that a degree-dependent initial configuration can outperform the uniform case for both accuracy and personalization strength. △ Less

Submitted 15 November, 2007; originally announced November 2007.

Comments: 4 pages and 3 figures

Journal ref: EPL 81, 58004 (2008)