Showing 1–50 of 126 results for author: Shen, H

Simultaneous Mars-orbit observations reveal Kelvin-Helmholtz instability-driven bulk atmospheric ion escape

Authors: Chi Zhang, Chuanfei Dong, Gangkai Poh, Jasper Halekas, Xuanye Ma, Ruhunusiri Suranga, Kathleen G. Hanley, Han-Wen Shen, Hongyang Zhou, Xinmin Li, Liang Wang, Jiawei Gao, Shannon Curry, Christian Mazelle

Abstract: Atmospheric ion escape driven by the solar wind is a key process controlling the long-term loss of the Martian atmosphere. Localized plasma clouds can carry substantial fluxes of planetary ions away from Mars, representing episodes of bulk escape. However, their origin has remained unclear due to the absence of simultaneous upstream measurements. Using joint observations from the MAVEN and Tianwen… ▽ More Atmospheric ion escape driven by the solar wind is a key process controlling the long-term loss of the Martian atmosphere. Localized plasma clouds can carry substantial fluxes of planetary ions away from Mars, representing episodes of bulk escape. However, their origin has remained unclear due to the absence of simultaneous upstream measurements. Using joint observations from the MAVEN and Tianwen-1 missions, which provide real-time upstream monitoring, we present direct evidence that these plasma clouds are nonlinear wave packets generated by the Kelvin-Helmholtz instability (KHI). The spatial scale of KH waves is constrained for the first time via two-point measurements. Ion fluxes within plasma clouds are one to two orders of magnitude higher than those in typical steady-state escape channels. Our results indicate that KHI is an important process for solar wind coupling to planetary upper atmospheres and plays a crucial role in shaping atmospheric ion escape for unmagnetized planets. △ Less

Submitted 4 August, 2026; originally announced August 2026.

Network-Based Subbasin-Scale Mapping of Streamflow Alteration in Ontario, Canada

Authors: Hongren Shen, Bryan A. Tolson, James R. Craig, Robert A. Metcalfe, Jonathan Romero-Cuellar, James J. Luce

Abstract: Dams, reservoirs, and waterpower facilities support regional water management but can alter streamflow far downstream through connected river networks, complicating hydrologic modeling and aquatic ecosystem assessment. Existing indicators typically quantify alteration only at discrete locations, limiting spatially continuous mapping of potential infrastructure influence. We propose the Streamflow… ▽ More Dams, reservoirs, and waterpower facilities support regional water management but can alter streamflow far downstream through connected river networks, complicating hydrologic modeling and aquatic ecosystem assessment. Existing indicators typically quantify alteration only at discrete locations, limiting spatially continuous mapping of potential infrastructure influence. We propose the Streamflow Alteration Index (SAI), a network-based screening metric that propagates point-based alteration signals downstream through a routing network. The framework includes paired indices, SAI_I and SAI_II (0-100%), representing influence from confirmed (Level I) and potential (Level II) alteration sources. We implemented SAI for Ontario, Canada, using the Ontario Lake and River Routing Product Version 2 (OLRRP v2) and an inventory of 643 alteration signal sources compiled from provincial datasets. The resulting SAI v1.0 database provides seamless, high-resolution, subbasin-scale mapping and estimates at gauged and ungauged network nodes. We validated SAI by classifying gauged subbasins as natural, conditional, or altered and comparing these classes with two independent references: Reference Hydrometric Basin Network gauges and Water Survey of Canada (WSC) Natural and Regulated labels. SAI classified 86% of RHBN natural gauges and 86% of WSC-natural gauges as natural. Among WSC-regulated gauges, 74% were classified as conditional or natural. SAI v1.0 therefore provides an objective screening product for large-domain hydrologic and aquatic applications without requiring detailed dam operating information and offers a scalable basis for national- to global-scale mapping of potential streamflow alteration. △ Less

Submitted 3 August, 2026; originally announced August 2026.

Comments: This manuscript is also available as a discussion preprint in Earth System Science Data Discussions, https://doi.org/10.5194/essd-2026-286

In-Situ Polarimetry in Collimated Magneto-Infrared Spectroscopy System

Authors: Zeping Shi, Wenbin Wu, Zhiwei Zhang, Yuhan Du, Chenyao Xu, Congming Hao, Xiangyu Jiang, Xin Chen, Guangyi Wang, Mingsen Zhou, Chunhui Pan, Wei Lu, Hao Shen, Haifeng Pan, Zhenrong Sun, Junhao Chu, Xiang Yuan

Abstract: Magneto-infrared spectroscopy under strong magnetic fields provides a powerful probe of Landau quantization and field-induced collective excitations, yet its full potential has long been constrained by the lack of in-situ polarization control, because the highly divergent infrared beam propagating through narrow light tubes undergoes multiple wall reflections, leading to severe polarization degrad… ▽ More Magneto-infrared spectroscopy under strong magnetic fields provides a powerful probe of Landau quantization and field-induced collective excitations, yet its full potential has long been constrained by the lack of in-situ polarization control, because the highly divergent infrared beam propagating through narrow light tubes undergoes multiple wall reflections, leading to severe polarization degradation. Here we report a collimated magneto-infrared spectroscopy system that integrates continuous in-situ polarimetry. The system employs incident and exit collimation chambers forming a Kepler type optical architecture, which converts the large-aperture FTIR output into a low-divergence beam and strongly suppresses multi-reflection trajectories inside long gold-plated light tubes, thereby enhancing both optical throughput and polarization fidelity. A remotely controlled polarization module, consisting of an automated linear polarizer and a switchable Fresnel rhomb positioned entirely outside the high-field region, enables continuous in-situ tuning between linear, circular, and arbitrary elliptical polarization states without thermal cycling, manual realignment, or breaking vacuum. Interchangeable compact focusing modules further support Faraday and Voigt geometries in both transmission and reflection experiments within a 50 mm magnet bore, providing efficient beam focusing and signal collection while maintaining polarization fidelity. The setup achieves a minimum root-mean-square noise of 0.0033%, an average noise of 0.0082%, and a linear polarization extinction ratio up to 40:1. We demonstrate the capability through continuous in-situ linear polarimetry and broadband circular polarimetry in the magneto-infrared spectroscopy of various single crystals. This platform establishes a robust experimental framework for in-situ polarization-resolved magneto-infrared spectroscopy. △ Less

Submitted 1 July, 2026; originally announced July 2026.

Journal ref: Advanced Science Instruments,1(1),100005.(2026)

Direct Observations of Magnetic Reconnection in the Solar Wind Current Sheets near Mars

Authors: Chi Zhang, Chuanfei Dong, Xinmin Li, Han-Wen Shen, Jasper Halekas, Tai Phan, Christian Mazelle, Yuki Harada, Hongyang Zhou, Jiawei Gao, Liang Wang, Shannon Curry, David L. Mitchell

Abstract: Magnetic reconnection is a fundamental and ubiquitous process in astrophysical plasmas that converts magnetic energy into plasma kinetic and thermal energy. Throughout the heliosphere, the solar wind is permeated with current sheets (CSs), providing a natural laboratory for investigating this process. Using measurements from NASA's Mars Atmosphere and Volatile EvolutioN (MAVEN) spacecraft, we repo… ▽ More Magnetic reconnection is a fundamental and ubiquitous process in astrophysical plasmas that converts magnetic energy into plasma kinetic and thermal energy. Throughout the heliosphere, the solar wind is permeated with current sheets (CSs), providing a natural laboratory for investigating this process. Using measurements from NASA's Mars Atmosphere and Volatile EvolutioN (MAVEN) spacecraft, we report the first direct observations of magnetic reconnection occurring within the solar wind CSs near Mars. Specifically, MAVEN observed the classic Petschek-type reconnection exhaust regions, evidenced by bifurcated magnetic field signatures and Alfvenic ion outflows. Notably, the observed exhaust region appears to be large-scale, significantly exceeding the typical thickness of solar wind CSs near Mars. This suggests that magnetic reconnection may significantly broaden the CS. Our results underscore the ubiquity of magnetic reconnection across heliocentric distances and may provide new insights into the large-scale evolution of the solar wind and the development of turbulence within it. △ Less

Submitted 14 June, 2026; originally announced June 2026.

Journal ref: The Astrophysical Journal Letters, Vol. 1004, L45 (2026)

Amplification of Weak Forces via Parametric Interactions and Non-Markovian Effects in Cavity Optomechanics

Authors: Y. F. Li, Ze Wang, W. Y. Hu, Yan-Hui Zhou, Cheng Shang, and H. Z. Shen

Abstract: Weak force amplification describes the process of amplifying a faint low-frequency signal by means of an additional high-frequency modulation, which plays a vital role in quantum sensing and high-precision measurement. However, the potential enhancement of weak-force amplification in non-Markovian environments has received little attention. In this paper, we firstly study the amplification of weak… ▽ More Weak force amplification describes the process of amplifying a faint low-frequency signal by means of an additional high-frequency modulation, which plays a vital role in quantum sensing and high-precision measurement. However, the potential enhancement of weak-force amplification in non-Markovian environments has received little attention. In this paper, we firstly study the amplification of weak forces within cavity-optomechanical systems incorporating a degenerate optical parametric amplifier (DOPA) under the Markovian assumption, which can be amplified via using two high-frequency signals via vibrational resonance through adjusting the strength and phase of the DOPA with different pumping frequencies. Moreover, we extend the study of the amplification of the weak force to the non-Markovian environment composed of an ensemble of infinite oscillators. We reveal that the amplification exhibits a conversion from the non-Markovian regime to Markovian regime by controlling environmental spectral width. Such a transition facilitates a remarkable improvement in amplification, and this enhancement originates from the excitation backflow generated via the interplay between the cavity and the non-Markovian environment. By controlling DOPA to amplify weak forces, the study achieves amplification in the non-Markovian regime, offering new directions for quantum optics research. △ Less

Submitted 17 May, 2026; originally announced May 2026.

Topological Anderson Random Laser

Authors: Hang-Zheng Shen, Xian-Hao Wei, Xi-Wang Luo, Zheng-Wei Zhou

Abstract: Topological lasers and random lasers embody two contrasting strategies for disorder management in photonics: the former suppresses disorder via protected edge transport, while the latter exploits multiple scattering for feedback. Here, we theoretically demonstrate that these seemingly incompatible paradigms can be unified through a topological Anderson random laser (TARL), where disorder itself in… ▽ More Topological lasers and random lasers embody two contrasting strategies for disorder management in photonics: the former suppresses disorder via protected edge transport, while the latter exploits multiple scattering for feedback. Here, we theoretically demonstrate that these seemingly incompatible paradigms can be unified through a topological Anderson random laser (TARL), where disorder itself induces a topological phase that enables robust lasing. Starting from a trivial photonic lattice, we show that engineered disorder drives the system into a topological Anderson insulator regime, generating emergent chiral edge states that serve as boundary-selective lasing channels. Remarkably, the TARL exhibits rapid mode selection toward a single edge state, producing an ultranarrow emission spectrum and enhanced slope efficiency optimized near disorder strength with maximal topological mobility gap. Furthermore, they exhibit single-mode-like coherence properties, deviating from Kardar-Parisi-Zhang behavior in conventional chiral topological lasers, while remaining significantly more robust against local perturbations than conventional random lasers. Our findings establish a disorder-enabled flexible route to topologically protected single-mode lasing and introduce a fundamentally new design principle for robust, high-coherence photonic light sources. △ Less

Submitted 22 March, 2026; originally announced April 2026.

Comments: 7 pages, 6 figures, with 5 page supplementary information

30-meter Land Surface Temperature from Landsat via Progressive Self-Training Downscaling

Authors: Huanfeng Shen, Chan Li, Menghui Jiang, Penghai Wu, Guanhao Zhang, Tian Xie

Abstract: Land surface temperature (LST) is a critical parameter for characterizing surface energy balance and hydrothermal processes. While Landsat provides invaluable LST observations at medium spatial resolution for over 40 years, its native spatial resolution of thermal bands (e.g., 100 m) remains insufficient compared to its 30 m optical bands, failing to meet the demands of fine-scale studies. To addr… ▽ More Land surface temperature (LST) is a critical parameter for characterizing surface energy balance and hydrothermal processes. While Landsat provides invaluable LST observations at medium spatial resolution for over 40 years, its native spatial resolution of thermal bands (e.g., 100 m) remains insufficient compared to its 30 m optical bands, failing to meet the demands of fine-scale studies. To address this issues, this study proposes a progressive self-training framework for downscaling Landsat LST to 30 m without relying on fine-scale ground truth, while maintaining minimal data dependence. The framework progressively optimizes a cross-modal fusion network to refine thermal details in a coarse-to-fine manner, characterized by one pre-training and two fine-tuning stages. Spatial validation against SDGSAT-1 30 m LST and temporal validation using in situ measurements confirm its reliability and accuracy, with both station-averaged MAE and RMSE outperforming the official cubic product by approximately 0.4 K. Further performance comparison experiments demonstrate that the proposed framework consistently reconstructs coherent fine-scale thermal patterns while preserving spatial heterogeneity. Multi spatial resolution evaluations and ablation studies verify the effectiveness of the proposed strategy and network design. Overall, the framework provides a stable pathway for enhancing the spatial resolution of Landsat LST, providing fine-resolution data support for fine-scale surface process studies and localized environmental monitoring. △ Less

Submitted 31 March, 2026; originally announced March 2026.

A Deep-Learning-Boosted Framework for Quantum Sensing with Nitrogen-Vacancy Centers in Diamond

Authors: Changyu Yao, Haochen Shen, Zhongyuan Liu, Ruotian Gong, Md Shakil Bin Kashem, Stella Varnum, Liangyu Li, Hangyue Li, Yue Yu, Yizhou Wang, Xiaoshui Lin, Jonathan Brestoff, Chenyang Lu, Shankar Mukherji, Chuanwei Zhang, Chong Zu

Abstract: Nitrogen-vacancy (NV) centers in diamond are a versatile quantum sensing platform for high sensitivity measurements of magnetic fields, temperature and strain with nanoscale spatial resolution. A common bottleneck is the analysis of optically detected magnetic resonance (ODMR) spectra, where target quantities are encoded in resonance features. Conventional nonlinear fitting is often computationall… ▽ More Nitrogen-vacancy (NV) centers in diamond are a versatile quantum sensing platform for high sensitivity measurements of magnetic fields, temperature and strain with nanoscale spatial resolution. A common bottleneck is the analysis of optically detected magnetic resonance (ODMR) spectra, where target quantities are encoded in resonance features. Conventional nonlinear fitting is often computationally expensive, sensitive to initialization, and prone to failure at low signal-to-noise ratio (SNR). Here we introduce a robust, efficient machine learning (ML) framework for real-time ODMR analysis based on a one-dimensional convolutional neural network (1D-CNN). The model performs direct parameter inference without initial guesses or iterative optimization, and is naturally parallelizable on graphics processing units (GPU) for high-throughput processing. We validate the approach on both synthetic and experimental datasets, showing improved throughput, accuracy and robustness than standard nonlinear fitting, with the largest gains in the low-SNR regime. We further validate our methods in two representative sensing applications: diagnosing intracellular temperature changes using nanodiamond probes and widefield magnetic imaging of superconducting vortices in a high-temperature superconductor. This deep-learning inference framework enables fast and reliable extraction of physical parameters from complex ODMR data and provides a scalable route to real-time quantum sensing and imaging. △ Less

Submitted 15 March, 2026; originally announced March 2026.

Comments: Main text contains: 9 pages, 4 figures. Includes supplementary material

Polarization-Multiplexed Chaotic LiDAR Based on a VCSEL with Delayed Orthogonal Feedback

Authors: T. Wang, Z. Li, H. Shen, Y. Ma, Y. Li, S. Xiang, S. Baland, Y. Hao

Abstract: Light detection and ranging (LiDAR) systems are pivotal for precise distance and velocity measurement, yet widespread deployment requires solutions that balance their performance, robustness, and simplicity. Here, we propose a novel chaotic LiDAR system based on a semiconductor vertical-cavity surface-emitting laser (VCSEL) with delayed orthogonal polarization feedback. By exploiting the intrinsic… ▽ More Light detection and ranging (LiDAR) systems are pivotal for precise distance and velocity measurement, yet widespread deployment requires solutions that balance their performance, robustness, and simplicity. Here, we propose a novel chaotic LiDAR system based on a semiconductor vertical-cavity surface-emitting laser (VCSEL) with delayed orthogonal polarization feedback. By exploiting the intrinsic competition between the transverse electric (TE) and transverse magnetic (TM) modes, the system generates a polarization-multiplexed dynamics: a chaotic TM mode serves as the reference, while a feedback-modulated TE mode probes the target. This all-in-one source eliminates the need for external optical modulators or complex coherent detection. The system's dynamics is finely tunable via a half-wave ($λ$/2) plate in the feedback loop and the laser injection current, enabling real-time optimization of the cross-correlation signal-to-noise ratio. Experimental results demonstrate precise linear ranging with a resolution of approximately 1.2 cm. Furthermore, the system exhibits strong inherent resistance to external optical interference, maintaining accurate ranging even in the presence of a secondary laser source. This compact, tunable, and interference-resilient platform offers a promising pathway toward low-cost, high-performance LiDAR for applications in autonomous navigation, robotics, and industrial metrology. △ Less

Submitted 14 February, 2026; originally announced February 2026.

Inverse Design of Tunable Infrared Metasurface Absorbers via a Conditional Wasserstein Generative Adversarial Network

Authors: H. Shen, T. Wang, X. Yao, O. Wu, C. Xie, C. Qian, H. Chen, T. Wang

Abstract: Narrowband perfect absorbers are interesting for spectrum sensing, molecular detection, and infrared imaging. However, their design remains constrained by intuitive, iterative methods that lack flexibility, while also facing challenges in multi-objective optimization. Here, we introduce a deep learning-enabled inverse-design framework that overcomes these limitations through a conditional Wasserst… ▽ More Narrowband perfect absorbers are interesting for spectrum sensing, molecular detection, and infrared imaging. However, their design remains constrained by intuitive, iterative methods that lack flexibility, while also facing challenges in multi-objective optimization. Here, we introduce a deep learning-enabled inverse-design framework that overcomes these limitations through a conditional Wasserstein Generative Adversarial Network (WGAN). The main contribution of this work is a dual-channel image encoding scheme that jointly represents the geometry and thickness of a Si$_3$N$_4$ meta-layer, facilitating the network to learn the distribution of viable structures for a target optical response. This approach naturally solves the inherent ``one-to-many'' design issue, giving a diverse portfolio of functional candidates from a single input spectrum. The designed absorbers achieve exceptional spectral fidelity, with resonance peak errors below 5 nm, a mean squared error (MSE) on the order of $10^{-3}$, and the capacity to produce over 10 distinct, high-performance designs per target. Furthermore, we demonstrate the model's robustness under oblique illumination, showing that it can be efficiently fine-tuned to maintain spectral accuracy across incidence angles from $10^\circ$ to $40^\circ$ by transfer learning, thus extending its practical utility to non-normal operating conditions. Full-wave simulations confirm that the generated geometries support a hybrid plasmonic-dielectric resonance, leading to near-perfect absorption and strong near-field enhancement. Our study provides a robust, physics-aware design paradigm that moves beyond conventional parametric optimization. The introduced framework establishes a versatile platform for the on-demand inverse design of advanced photonic devices for sensing, spectroscopy, and optical signal processing. △ Less

Submitted 2 February, 2026; originally announced February 2026.

AI-Accelerated Qubit Readout at the Single-Photon Level for Scalable Atomic Quantum Processors

Authors: Yaoting Zhou, Weisen Wang, Zhuangzhuang Tian, Bin Huang, Huancheng Chen, Donghao Li, Zhongxiao Xu, Li Chen, Heng Shen

Abstract: Quantum state readout with minimal resources is crucial for scalable quantum information processing. As a leading platform, neutral atom arrays rely on atomic fluorescence imaging for qubit readout, requiring short exposure, low photon count schemes to mitigate heating and atom loss while enabling mid-circuit feedback. However, a fundamental challenge arises in the single-photon regime where sever… ▽ More Quantum state readout with minimal resources is crucial for scalable quantum information processing. As a leading platform, neutral atom arrays rely on atomic fluorescence imaging for qubit readout, requiring short exposure, low photon count schemes to mitigate heating and atom loss while enabling mid-circuit feedback. However, a fundamental challenge arises in the single-photon regime where severe overlap in state distributions causes conventional threshold discrimination to fail. Here, we report an AI-accelerated Bayesian inference method for fluorescence readout in neutral atom arrays. Our approach leverages Bayesian inference to achieve reliable state detection at the single-photon level under short exposure. Specifically, we introduce a weakly anchored Bayesian scheme that requires calibration of only one state, addressing asymmetric calibration challenges common across quantum platforms. Furthermore, acceleration is achieved via a permutation-invariant neural network, which yields a 100-fold speedup by compressing iterative inference into a single forward pass. The approach achieves relative readout fidelity above 99% and 98% for histogram overlaps of 61% and 72%, respectively, enabling reliable extraction of Rabi oscillations and Ramsey interference results unattainable with conventional threshold based methods. This framework supports scalable, real-time readout of large atom arrays and paves the way toward AI-enhanced quantum technology in computation and sensing. △ Less

Submitted 23 December, 2025; originally announced December 2025.

A High-Flux and High-Efficiency Setup for Magneto-Infrared Spectroscopy

Authors: Zeping Shi, Wenbin Wu, Zhiwei Zhang, Yuhan Du, Chenyao Xu, Guangyi Wang, Mingsen Zhou, Congming Hao, Xianghao Meng, Xiangyu Jiang, Chunhui Pan, Wei Lu, Hao Shen, Haifeng Pan, Zhenrong Sun, Junhao Chu, Xiang Yuan

Abstract: We report the design and implementation of a high-flux, high-efficiency magneto-infrared spectroscopy system optimized for broadband measurements in high magnetic fields. The setup integrates a Fourier transform infrared spectrometer, a 12 T cryogen-free superconducting magnet, precision-polished and gold-plated light tubes, custom-designed reflective focusing modules for Faraday and Voigt geometr… ▽ More We report the design and implementation of a high-flux, high-efficiency magneto-infrared spectroscopy system optimized for broadband measurements in high magnetic fields. The setup integrates a Fourier transform infrared spectrometer, a 12 T cryogen-free superconducting magnet, precision-polished and gold-plated light tubes, custom-designed reflective focusing modules for Faraday and Voigt geometries, and an external multi-detector chamber with motorized selection. Optical throughput is maximized by reducing light tube loss from 65.5%/m to 22.0%/m via abrasive flow and mechanical polishing followed by gold electroplating, and by adopting a single-on-axis parabolic-mirror Faraday module that increases the effective numerical aperture from 0.14 to 0.36, enhancing collection efficiency by nearly an order of magnitude. An eight-position motorized sample stage and fully automated control over magnetic field, temperature, optical path, and detector choice enable high-throughput measurements without repeated warm-ups. The optimized configuration achieves a root-mean-square noise level of 0.0061% in a 2-minute integration for a 40% reflectivity sample, corresponding to a signal-to-noise ratio exceeding 16000. System capabilities are demonstrated by resolving weak replica bands in EuCd2As2 and faint Landau level transitions in LaAlSi. △ Less

Submitted 16 December, 2025; originally announced December 2025.

Journal ref: Rev. Sci. Instrum. 96, 113902 (2025)

PF-DAformer: Proximal Femur Segmentation via Domain Adaptive Transformer for Dual-Center QCT

Authors: Rochak Dhakal, Chen Zhao, Zixin Shi, Joyce H. Keyak, Tadashi S. Kaneko, Kuan-Jui Su, Hui Shen, Hong-Wen Deng, Weihua Zhou

Abstract: Quantitative computed tomography (QCT) plays a crucial role in assessing bone strength and fracture risk by enabling volumetric analysis of bone density distribution in the proximal femur. However, deploying automated segmentation models in practice remains difficult because deep networks trained on one dataset often fail when applied to another. This failure stems from domain shift, where scanner… ▽ More Quantitative computed tomography (QCT) plays a crucial role in assessing bone strength and fracture risk by enabling volumetric analysis of bone density distribution in the proximal femur. However, deploying automated segmentation models in practice remains difficult because deep networks trained on one dataset often fail when applied to another. This failure stems from domain shift, where scanners, reconstruction settings, and patient demographics vary across institutions, leading to unstable predictions and unreliable quantitative metrics. Overcoming this barrier is essential for multi-center osteoporosis research and for ensuring that radiomics and structural finite element analysis results remain reproducible across sites. In this work, we developed a domain-adaptive transformer segmentation framework tailored for multi-institutional QCT. Our model is trained and validated on one of the largest hip fracture related research cohorts to date, comprising 1,024 QCT images scans from Tulane University and 384 scans from Rochester, Minnesota for proximal femur segmentation. To address domain shift, we integrate two complementary strategies within a 3D TransUNet backbone: adversarial alignment via Gradient Reversal Layer (GRL), which discourages the network from encoding site-specific cues, and statistical alignment via Maximum Mean Discrepancy (MMD), which explicitly reduces distributional mismatches between institutions. This dual mechanism balances invariance and fine-grained alignment, enabling scanner-agnostic feature learning while preserving anatomical detail. △ Less

Submitted 30 October, 2025; originally announced October 2025.

Comments: 22 Pages, 5 Tables, 10 Figures. The combination of GRL and MMD achieved the most balanced performance, reducing contour deviations and enhancing surface smoothness

An Advanced Two-Stage Model with High Sensitivity and Generalizability for Prediction of Hip Fracture Risk Using Multiple Datasets

Authors: Shuo Sun, Meiling Zhou, Chen Zhao, Joyce H. Keyak, Nancy E. Lane, Jeffrey D. Deng, Kuan-Jui Su, Hui Shen, Hong-Wen Deng, Kui Zhang, Weihua Zhou

Abstract: Hip fractures are a major cause of disability, mortality, and healthcare burden in older adults, underscoring the need for early risk assessment. However, commonly used tools such as the DXA T-score and FRAX often lack sensitivity and miss individuals at high risk, particularly those without prior fractures or with osteopenia. To address this limitation, we propose a sequential two-stage model tha… ▽ More Hip fractures are a major cause of disability, mortality, and healthcare burden in older adults, underscoring the need for early risk assessment. However, commonly used tools such as the DXA T-score and FRAX often lack sensitivity and miss individuals at high risk, particularly those without prior fractures or with osteopenia. To address this limitation, we propose a sequential two-stage model that integrates clinical and imaging information to improve prediction accuracy. Using data from the Osteoporotic Fractures in Men Study (MrOS), the Study of Osteoporotic Fractures (SOF), and the UK Biobank, Stage 1 (Screening) employs clinical, demographic, and functional variables to estimate baseline risk, while Stage 2 (Imaging) incorporates DXA-derived features for refinement. The model was rigorously validated through internal and external testing, showing consistent performance and adaptability across cohorts. Compared to T-score and FRAX, the two-stage framework achieved higher sensitivity and reduced missed cases, offering a cost-effective and personalized approach for early hip fracture risk assessment. Keywords: Hip Fracture, Two-Stage Model, Risk Prediction, Sensitivity, DXA, FRAX △ Less

Submitted 16 October, 2025; originally announced October 2025.

Comments: 38 pages, 3 figures, 8 tables. This is a preprint version of the manuscript titled "An Advanced Two-Stage Model with High Sensitivity and Generalizability for Prediction of Hip Fracture Risk Using Multiple Datasets." The paper is currently under journal submission

Fully automated inverse co-optimization of templates and block copolymer blending recipes for DSA lithography

Authors: Yuhao Zhou, Huangyan Shen, Qingliang Song, Qingshu Dong, Jianfeng Li, Weihua Li

Abstract: The directed self-assembly (DSA) of block copolymers (BCPs) offers a highly promising approach for the fabrication of contact holes or vertical interconnect access at sub-7nm technology nodes. To fabricate circular holes with precisely controlled size and positions, the self-assembly of block copolymers requires guidance from a properly designed template. Effectively parameterizing the template sh… ▽ More The directed self-assembly (DSA) of block copolymers (BCPs) offers a highly promising approach for the fabrication of contact holes or vertical interconnect access at sub-7nm technology nodes. To fabricate circular holes with precisely controlled size and positions, the self-assembly of block copolymers requires guidance from a properly designed template. Effectively parameterizing the template shape to enable efficient optimization remains a critical yet challenging problem. Moreover, the optimized template must possess excellent manufacturability for practical applications. In this work, we propose a Gaussian descriptor for characterizing the template shape with only two parameters. We further propose to use AB/AB binary blends instead of pure diblock copolymer to improve the adaptability of the block copolymer system to the template shape. The Bayesian optimization (BO) is applied to co-optimize the binary blend and the template shape. Our results demonstrate that BO based on the Gaussian descriptor can efficiently yield the optimal templates for diverse multi-hole patterns, all leading to highly matched self-assembled morphologies. Moreover, by imposing constraints on the variation of curvature of the template during optimization, superior manufacturability is ensured for each optimized template. It is noteworthy that each key parameter of the blend exhibits a relatively wide tunable window under the requirement of rather high precision. Our work provides valuable insights for advancing DSA technology, and thus potentially propels its practical applications forward. △ Less

Submitted 3 October, 2025; originally announced October 2025.

A Mechanism-Coupled Split Window Network for Medium- to High-Resolution Land Surface Temperature Retrieval

Authors: Tian Xie, Menghui Jiang, Chao Zeng, Huifang Li, Guanhao Zhang, Chan Li, Huanfeng Shen

Abstract: Land surface temperature (LST) is a fundamental physical variable in land-atmosphere interactions, surface energy budgets, and climate processes. LST derived from medium- to high-resolution thermal infrared (TIR) observations effectively reveals thermal environmental disparities across distinct landscape units. However, achieving accurate, robust, and globally generalizable LST retrieval remains c… ▽ More Land surface temperature (LST) is a fundamental physical variable in land-atmosphere interactions, surface energy budgets, and climate processes. LST derived from medium- to high-resolution thermal infrared (TIR) observations effectively reveals thermal environmental disparities across distinct landscape units. However, achieving accurate, robust, and globally generalizable LST retrieval remains challenging under complex atmospheric conditions and diverse land cover types. Traditional split window (SW) algorithms heavily rely on empirical parameterizations, whose fixed coefficients fail to adapt to complex scenarios such as high surface temperatures and high atmospheric water vapor content. Concurrently, conventional data-driven models exhibit limited generalizability to out-of-distribution (OOD) samples due to the absence of explicit physical structure constraints. To address these issues, this study proposes a Parallel Component Decoupled Neural Network (PCD-Net) framework, which reformulates SW retrieval as a dynamic learning problem of physical component coefficients. Using the SW equation as the physical backbone, the framework constructs parallel subnetworks to adaptively learn the dynamic coefficients corresponding to the constant, first-order, and second-order brightness temperature difference terms; meanwhile, a residual branch is incorporated to supplement the nonlinear coupling corrections induced by the joint effects of surface emissivity and atmospheric water vapor. Through this component-level decoupled modeling, PCD-Net explicitly characterizes the dynamic response relationships between land surface emissivity, atmospheric water vapor content, and different SW physical components. △ Less

Submitted 4 June, 2026; v1 submitted 5 September, 2025; originally announced September 2025.

Manifold Optics

Authors: Hongming Shen, Wen Xiao, Fei Fang Chuang, Huanyang Chen

Abstract: Transformation optics establishes an equivalence relationship between gradient media and curved space, unveiling intrinsic geometric properties of gradient media. However, this approach based on curved spaces is concentrated on two-dimensional manifolds, namely curved surfaces. In this Letter, we establish an intrinsic connection between three-dimensional manifolds and three-dimensional gradient m… ▽ More Transformation optics establishes an equivalence relationship between gradient media and curved space, unveiling intrinsic geometric properties of gradient media. However, this approach based on curved spaces is concentrated on two-dimensional manifolds, namely curved surfaces. In this Letter, we establish an intrinsic connection between three-dimensional manifolds and three-dimensional gradient media in transformation optics by leveraging the Yamabe problem and Ricci scalar curvature, a measure of spatial curvature in manifolds. The invariance of the Ricci scalar under conformal mappings is proven. Our framework is validated through the analysis of representative conformal optical lenses. △ Less

Submitted 23 July, 2025; originally announced July 2025.

Comments: 1 figure

Simultaneous Determination of Local Magnetic Fields and Sensor Orientation with Nitrogen-Vacancy Centers in Nanodiamond

Authors: Yizhou Wang, Haochen Shen, Zhongyuan Liu, Yue Yu, Shengwang Du, Chong Zu, Chuanwei Zhang

Abstract: Nitrogen-vacancy (NV) centers in nanodiamonds have emerged as a promising quantum sensing platform for biomedical imaging applications, yet random orientations of individual particles present significant challenges in large-scale sensor calibration. In this study, we demonstrate a novel approach to simultaneously determine each particle's crystallographic axes and the surrounding local vector magn… ▽ More Nitrogen-vacancy (NV) centers in nanodiamonds have emerged as a promising quantum sensing platform for biomedical imaging applications, yet random orientations of individual particles present significant challenges in large-scale sensor calibration. In this study, we demonstrate a novel approach to simultaneously determine each particle's crystallographic axes and the surrounding local vector magnetic field. Specifically, a minimum of four distinct bias fields is required to unambiguously extract both the orientation and the local field. We validate our method experimentally using NV centers in two scenarios: (1) in a bulk diamond with known crystal orientation as a proof of concept, and (2) on various single nanodiamonds to mimic real-world applications. Our work represents a crucial step towards unlocking the full potential of nanodiamonds for advanced applications such as in-situ biomedical imaging and nanoscale sensing in complex environments. △ Less

Submitted 7 July, 2025; originally announced July 2025.

Comments: Main text with 8 pages and 4 figures. Supplementary consists of 9 pages and 4 figures

Graphics4Science: Computer Graphics for Scientific Impacts

Authors: Peter Yichen Chen, Minghao Guo, Hanspeter Pfister, Ming Lin, William Freeman, Qixing Huang, Han-Wei Shen, Wojciech Matusik

Abstract: Computer graphics, often associated with films, games, and visual effects, has long been a powerful tool for addressing scientific challenges--from its origins in 3D visualization for medical imaging to its role in modern computational modeling and simulation. This course explores the deep and evolving relationship between computer graphics and science, highlighting past achievements, ongoing cont… ▽ More Computer graphics, often associated with films, games, and visual effects, has long been a powerful tool for addressing scientific challenges--from its origins in 3D visualization for medical imaging to its role in modern computational modeling and simulation. This course explores the deep and evolving relationship between computer graphics and science, highlighting past achievements, ongoing contributions, and open questions that remain. We show how core methods, such as geometric reasoning and physical modeling, provide inductive biases that help address challenges in both fields, especially in data-scarce settings. To that end, we aim to reframe graphics as a modeling language for science by bridging vocabulary gaps between the two communities. Designed for both newcomers and experts, Graphics4Science invites the graphics community to engage with science, tackle high-impact problems where graphics expertise can make a difference, and contribute to the future of scientific discovery. Additional details are available on the course website: https://graphics4science.github.io △ Less

Submitted 18 June, 2025; originally announced June 2025.

Reconstruction-free magnetic control of DIII-D plasma with deep reinforcement learning

Authors: G. F. Subbotin, D. I. Sorokin, M. R. Nurgaliev, A. A. Granovskiy, I. P. Kharitonov, E. V. Adishchev, E. N. Khairutdinov, R. Clark, H. Shen, W. Choi, J. Barr, D. M. Orlov

Abstract: Precise control of plasma shape and position is essential for stable tokamak operation and achieving commercial fusion energy. Traditional control methods rely on equilibrium reconstruction and linearized models, limiting adaptability and real-time performance. Here,the first application of deep reinforcement learning (RL) for magnetic plasma control on the mid-size DIII-D tokamak is presented, de… ▽ More Precise control of plasma shape and position is essential for stable tokamak operation and achieving commercial fusion energy. Traditional control methods rely on equilibrium reconstruction and linearized models, limiting adaptability and real-time performance. Here,the first application of deep reinforcement learning (RL) for magnetic plasma control on the mid-size DIII-D tokamak is presented, demonstrating a nonlinear approach that improves robustness and flexibility across plasma scenarios. Using the Soft Actor-Critic algorithm, this method eliminates the need for equilibrium reconstruction, enabling high-speed control execution and scalability on larger fusion devices. NSFsim, a 2D Grad-Shafranov equilibration solver with a circuit equation and a 1D transport solver, is used to train the agent. Its capability of reproducing the kinetic parameter evolution alongside magnetic equilibria evolution appears to be an essential factor significantly affecting control quality. RL-based controllers demonstrated robust magnetic control in experimental application at DIII-D, preserving control performance in transient events during plasma discharges, and reaching target parameters from the first discharge without additional tuning or modifications. The approach itself has significant generalization potential across devices and targets. This work represents a step toward AI-driven, real-time plasma control, advancing the feasibility of next-generation fusion reactors. △ Less

Submitted 16 June, 2025; originally announced June 2025.

Comments: 19 pages, 9 figures

Vertical Profile Corrected Satellite NH3 Retrievals Enable Accurate Agricultural Emission Characterization in China

Authors: Qiming Liu, Yilin Chen, Peng Xu, Huizhong Shen, Zelin Mai, Ruixin Zhang, Peng Guo, Zhiyu Zheng, Tiancheng Luan, Shu Tao

Abstract: Ammonia (NH3) emissions significantly contribute to atmospheric pollution, yet discrepancies exist between bottom-up inventories and satellite-constrained top-down estimates, with the latter typically one-third higher. This study quantifies how assumptions about NH3 vertical distribution in satellite retrievals contribute to this gap. By implementing spatially and temporally resolved vertical prof… ▽ More Ammonia (NH3) emissions significantly contribute to atmospheric pollution, yet discrepancies exist between bottom-up inventories and satellite-constrained top-down estimates, with the latter typically one-third higher. This study quantifies how assumptions about NH3 vertical distribution in satellite retrievals contribute to this gap. By implementing spatially and temporally resolved vertical profiles from the Community Multiscale Air Quality model to replace steep gradients in Infrared Atmospheric Sounding Interferometer (IASI) retrievals, we reduced satellite-model column discrepancies from 71% to 18%. We subsequently constrained NH3 emissions across China using a hybrid inversion framework combining iterative mass balance and four-dimensional variational methods. Our posterior emissions showed agreement with the a priori inventory (7.9% lower), suggesting that discrepancies between inventory approaches were amplified by overestimation of near-surface NH3 in baseline satellite retrievals, potentially causing a 43% overestimation of growing season emissions. Evaluation against ground-based measurements confirmed improved model performance, with normalized root-mean-square error reductions of 1-27% across six months. These findings demonstrate that accurate representation of vertical profiles in satellite retrievals is critical for robust NH3 emission estimates and can reconcile the long-standing discrepancy between bottom-up and top-down approaches. Our hybrid inversion methodology, leveraging profile-corrected satellite data, reveals that China's NH3 emissions exhibit greater spatial concentration than previously recognized, reflecting agricultural intensification. This advancement enables timely and accurate characterization of rapidly changing agricultural emission patterns, critical for implementing effective nitrogen pollution control measures. △ Less

Submitted 26 May, 2025; originally announced May 2025.

Comments: 44 pages, 14 figures, 1 table. The main text spans pages 1-28 and includes 5 figures. The supplementary information (SI) spans pages 29-44, containing 9 figures and 1 table

Non-Markovian dynamics with a driven three-level giant atom in a semi-infinite photonic waveguide

Authors: S. J. Sun, Z. Y. Li, C. Cui, Shuang Xu, H. Z. Shen

Abstract: The non-Markovian effects of open quantum systems subjected to external environments are deemed to be valuable resources in quantum optics and quantum information processing. In this work, we investigate the non-Markovian dynamics of a three-level giant atom coupling with a semi-infinite photonic waveguide through multiple coupling points and driven by a classical driving field. We derive the anal… ▽ More The non-Markovian effects of open quantum systems subjected to external environments are deemed to be valuable resources in quantum optics and quantum information processing. In this work, we investigate the non-Markovian dynamics of a three-level giant atom coupling with a semi-infinite photonic waveguide through multiple coupling points and driven by a classical driving field. We derive the analytical expressions for the probability amplitudes of the driven three-level giant atom and obtain two independent conditions. We find two different types of bound states (including the static bound states and the periodic equal-amplitude oscillating bound states) and discuss the physical origins of the bound states formation. Moreover, we discuss the case of the driven three-level giant atom interacting with the infinite photonic waveguide, where there is only one purely imaginary solution (i.e., only one bound state condition exists) for its complex frequency (coming from the absence of mirror at one end of the waveguide) compared to that of a driven three-level giant atom coupling with a semi-infinite photonic waveguide. With this, we also find two different types of bound states, including the static bound state and the periodic equal-amplitude oscillating bound states. Finally, the above results are generalized to a more general model involving a semi-infinite photonic waveguide coupling with an arbitrary number of noninteracting three-level giant atoms driven by the driving fields. The proposed protocol could provide a pathway to precisely elucidate the non-Markovian dynamics of driven, multi-level giant atoms coupled to semi-infinite or infinite photonic waveguides. △ Less

Submitted 15 May, 2025; originally announced May 2025.

Comments: 23 pages, 15 figures

Journal ref: Phys. Rev. A 112, 063704 (2025)

Simultaneous nonreciprocal unconventional photon blockade via two degenerate optical parametric amplifiers in spinning resonators

Authors: J. X. Yang, Cheng Shang, Yan-Hui Zhou, H. Z. Shen

Abstract: We propose a scheme to achieving simultaneous nonreciprocal unconventional photon blockade in a system of two coupled spining resonators marked by modes a and b, each incorporating an degenerate optical parametric amplifier (DOPA). By rotating the resonators, input light from opposite directions induces opposite Sagnac-Fizeau shifts. These shifts result in the emergence or absence of quantum destr… ▽ More We propose a scheme to achieving simultaneous nonreciprocal unconventional photon blockade in a system of two coupled spining resonators marked by modes a and b, each incorporating an degenerate optical parametric amplifier (DOPA). By rotating the resonators, input light from opposite directions induces opposite Sagnac-Fizeau shifts. These shifts result in the emergence or absence of quantum destructive interference in two-photon excitation processes. Specifically, when destructive quantum interference occurs, photons from one input direction are simultaneously blocked in both resonators, whereas the absence of complete destructive quantum interference causes the blockade effect to vanish for inputs from the opposite direction. We analytically give the optimal parameter conditions to achieve simultaneous strong photon blockade with the parametric amplification. By adjusting the Sagnac-Fizeau shifts, we can make mode a nonreciprocal photon blockade, while mode b exhibits photon blockade in both directions. This work lays a theoretical foundation for the development of multimode simultaneous nonreciprocal unconventional single-photon devices, which hold promising potential in multichannel topological optics and chiral quantum technologies. △ Less

Submitted 15 May, 2025; originally announced May 2025.

Comments: 12 pages, 13 figures

Frequency conversion between optical and microwave photons in non-Markovian environments

Authors: Jia Tang, H. Z. Shen

Abstract: In this paper, we propose a scheme for frequency conversion between optical photons and microwave photons in non-Markovian environments using both magnetic and mechanical excitations as intermediate media. When the frequencies of optical photons, magnons, phonons, and microwave photons resonance, the conversion efficiency can be made close to reach 98.76$\%$ by adjusting the defined complex cooper… ▽ More In this paper, we propose a scheme for frequency conversion between optical photons and microwave photons in non-Markovian environments using both magnetic and mechanical excitations as intermediate media. When the frequencies of optical photons, magnons, phonons, and microwave photons resonance, the conversion efficiency can be made close to reach 98.76$\%$ by adjusting the defined complex cooperativities, while in the case of Markovian, the conversion efficiency is 90.44$\%$. By controlling the environmental spectral widths, the efficiency of frequency conversion exhibits a transition from Markovian regimes to non-Markovian regimes. This transformation simultaneously improves frequency conversion efficiency and conversion bandwidth, which is due to the excitation backflow generated by the interaction between the system and the non-Markovian environments. In the case, when the optical pump power in the non-Markovian regimes are of a large order of magnitude, the conversion bandwidth can be increased, but at the cost of reduced conversion efficiency. Our scheme improves the frequency conversion efficiency and bandwidth between optical photons and microwave photons, breaking the limitations of frequency conversion in Markovian environments and providing a new approach for long-distance quantum communication research of other non-Markovian quantum systems in quantum optics. △ Less

Submitted 15 May, 2025; originally announced May 2025.

Comments: 17 pages, 6 figures

Journal ref: Phys. Rev. A 110, 043706 (2024)

Realizing exceptional points by Floquet dissipative couplings in thermal atoms

Authors: Zimo Zhang, Fengbo Zhang, Zhongxiao Xu, Ying Hu, Han Bao, Heng Shen

Abstract: Exceptional degeneracies and generically complex spectra of non-Hermitian systems are at the heart of numerous phenomena absent in the Hermitian realm. Recently, it was suggested that Floquet dissipative coupling in the space-time domain may provide a novel mechanism to drive intriguing spectral topology with no static analogues, though its experimental investigation in quantum systems remains elu… ▽ More Exceptional degeneracies and generically complex spectra of non-Hermitian systems are at the heart of numerous phenomena absent in the Hermitian realm. Recently, it was suggested that Floquet dissipative coupling in the space-time domain may provide a novel mechanism to drive intriguing spectral topology with no static analogues, though its experimental investigation in quantum systems remains elusive. We demonstrate such Floquet dissipative coupling in an ensemble of thermal atoms interacting with two spatially separated optical beams, and observe an anomalous anti-parity-time symmetry phase transition at an exception point far from the phase-transition threshold of the static counterpart. Our protocol sets the stage for Floquet engineering of non-Hermitian topological spectra, and for engineering new quantum phases that cannot exist in static systems. △ Less

Submitted 18 April, 2025; originally announced April 2025.

Comments: 6 pages, 4 figures

Journal ref: Phys. Rev. Lett. 133, 133601 (2024)

Chirality-induced quantum nonreciprocity

Authors: Zimo Zhang, Zhongxiao Xu, Ran Huang, Xingda Lu, Fengbo Zhang, Donghao Li, Şahin K. Özdemir, Franco Nori, Han Bao, Yanhong Xiao, Bing Chen, Hui Jing, Heng Shen

Abstract: Chirality, nonreciprocity, and quantum correlations are at the center of a wide range of intriguing effects and applications across natural sciences and emerging quantum technologies. However, the direct link combining these three essential concepts has remained unknown till now. Here, we establish a chiral non-Hermitian platform with flying atoms and demonstrate chirality-induced nonreciprocal bi… ▽ More Chirality, nonreciprocity, and quantum correlations are at the center of a wide range of intriguing effects and applications across natural sciences and emerging quantum technologies. However, the direct link combining these three essential concepts has remained unknown till now. Here, we establish a chiral non-Hermitian platform with flying atoms and demonstrate chirality-induced nonreciprocal bipartite quantum correlations between two channels: Quantum correlation emerges when two spatially separated light beams of the same polarization propagate in opposite directions in the atomic cloud, and it becomes zero when they travel in the same direction. Thus, just by flipping the propagation direction of one of the beams while keeping its polarization the same as the other beam, we can create or annihilate quantum correlations between two channels. We also show that this nonreciprocal quantum correlation can be extended to multi-color sidebands with Floquet engineering. Our findings may pave the road for realizing one-way quantum effects, such as nonreciprocal squeezing or entanglement, with a variety of chiral devices, for the emerging applications of e.g., directional quantum network or nonreciprocal quantum metrology. △ Less

Submitted 21 April, 2025; v1 submitted 17 April, 2025; originally announced April 2025.

Comments: To be published

Can Charge Transfer Across C-H...O Hydrogen Bonds Stabilize Oil Droplets in Water?

Authors: Ruoqi Zhao, Hengyuan Shen, R. Allen LaCour, Joseph P. Heindel, Martin Head-Gordon, Teresa Head-Gordon

Abstract: Oil-water emulsions resist aggregation due to the presence of negative charges at their surface that leads to mutual repulsion between droplets, but the molecular origin of oil charge is currently under debate. While much evidence has suggested that ionic species must accumulate at the interface, an alternative perspective attributes the negative charge on the oil droplet to charge transfer of ele… ▽ More Oil-water emulsions resist aggregation due to the presence of negative charges at their surface that leads to mutual repulsion between droplets, but the molecular origin of oil charge is currently under debate. While much evidence has suggested that ionic species must accumulate at the interface, an alternative perspective attributes the negative charge on the oil droplet to charge transfer of electron density from water to oil molecules. While the charge transfer mechanism is consistent with the correct sign of oil charge, it is just as important to provide good estimates of the charge magnitude to explain emulsion stability and electrophoresis experiments. Here we show using energy decomposition analysis that the amount of net flow of charge from water to oil is negligibly small due to nearly equal forward and backward charge transfer through weak oil-water interactions, such that oil droplets would be unstable and coalesce, contrary to experiment. The lack of charge transfer also explains why vibrational sum frequency scattering reports a blue shift in the oil C-H frequency when forming emulsions with water, which arises from Pauli repulsion due to localized confinement at the interface. Finally, unlike ions, neither charge transfer nor dynamic polarization can produce a finite conductivity needed to couple to electric fields that would explain electrophoretic mobility. △ Less

Submitted 11 November, 2025; v1 submitted 15 April, 2025; originally announced April 2025.

Dressed bound states and non-Markovian dynamics with a whispering-gallery-mode microcavity coupled to a two-level atom and a semi-infinite photonic waveguide

Authors: J. Y. Sun, C. Cui, Y. F. Li, Shuang Xu, Cheng Shang, Yan-Hui Zhou, H. Z. Shen

Abstract: We investigate the dressed bound states (DBS) in an open cavity with a whispering-gallery-mode microring coupled to a two-level atom and a waveguide with a mirror at the right end. We demonstrate that the non-Hermiticity of an open cavity facilitates the formation of the DBS, which consists of the vacancy-like DBS and Friedrich-Wintgen DBS. By deriving analytical conditions for these DBS, we show… ▽ More We investigate the dressed bound states (DBS) in an open cavity with a whispering-gallery-mode microring coupled to a two-level atom and a waveguide with a mirror at the right end. We demonstrate that the non-Hermiticity of an open cavity facilitates the formation of the DBS, which consists of the vacancy-like DBS and Friedrich-Wintgen DBS. By deriving analytical conditions for these DBS, we show that when a two-level atom couples to the standing-wave mode that corresponds to a node of the photonic wave function the vacancy-like DBS occur, which are characterized by null spectral density at cavity resonance. Conversely, Friedrich-Wintgen DBS can be realized by continuously adjusting system parameters and indicated by the disappearance of the Rabi peak in the emission spectrum, which is a distinctive feature in the strong-coupling regime. Moreover, we extend our analysis to the non-Markovian regime and find that our results are consistent with those obtained under the Markovian approximation in the wideband limit. In the non-Markovian regime, we analyze DBS for both zero and non-zero accumulated phase factors. For zero accumulated phase factors, the non-Markovian regime exhibits higher peak values and longer relaxation times for vacancy-like DBS compared to the Markovian regime, where the Friedrich-Wintgen DBS are absent in the non-Markovian case. Finally, we establish the correspondence between the energy spectrum and bound state conditions for non-zero accumulated phase factors and analyze the influence of various parameters on non-Markovian bound states. Our work exhibits bound state manipulations through non-Markovian open quantum system, which holds great potential for building high-performance quantum devices for applications such as sensing, photon storage, and nonclassical light generation. △ Less

Submitted 13 April, 2025; originally announced April 2025.

Comments: 18 pages, 13 figures

Journal ref: Phys. Rev. A 113, 063713 (2026)

A quantum computing approach to beam angle optimization

Authors: Nimita Shinde, Ya-Nan Zhu, Haozheng Shen, Hao Gao

Abstract: Background: Beam angle optimization (BAO) is a critical component of radiation therapy (RT) treatment planning, where small changes in beam configuration can significantly impact treatment quality, especially for proton RT. Mathematically, BAO is a mixed integer programming (MIP) problem, which is NP-hard due to its exponential growing search space. Traditional optimization techniques often strugg… ▽ More Background: Beam angle optimization (BAO) is a critical component of radiation therapy (RT) treatment planning, where small changes in beam configuration can significantly impact treatment quality, especially for proton RT. Mathematically, BAO is a mixed integer programming (MIP) problem, which is NP-hard due to its exponential growing search space. Traditional optimization techniques often struggle with computational efficiency, necessitating the development of novel approaches. Purpose: This study introduces QC-BAO, a hybrid quantum-classical approach that leverages quantum computing to solve the MIP formulation of BAO. Methods: The proposed approach, QC-BAO, models BAO as an MIP problem, incorporating binary variables for beam angle selection and continuous variables for optimizing spot intensities for proton therapy. The proposed approach employs a hybrid quantum-classical framework, utilizing quantum computing to solve the binary decision component while integrating classical optimization techniques, including iterative convex relaxation and alternating direction method of multipliers. Results: Computational experiments were conducted on clinical test cases to evaluate QC-BAO's performance against clinically verified angles and a heuristic approach, GS-BAO. QC-BAO demonstrated improved treatment plan quality over both clinical and GS-BAO. The method consistently increased the conformity index (CI) for target coverage while reducing mean and maximum doses to organs-at-risk (OAR). Additionally, QC-BAO produced the lowest objective function value, confirming its superior optimization capability. Conclusions: The findings highlight the potential of quantum computing to enhance the solution to BAO problem by demonstrated improvement in plan quality using the proposed method, QC-BAO. This study paves the way for future clinical implementation of quantum-accelerated optimization in RT. △ Less

Submitted 5 September, 2025; v1 submitted 10 April, 2025; originally announced April 2025.

A Mechanism-Learning Deeply Coupled Model for Remote Sensing Retrieval of Global Land Surface Temperature

Authors: Tian Xie, Menghui Jiang, Huanfeng Shen, Huifang Li, Chao Zeng, Jun Ma, Guanhao Zhang, Liangpei Zhang

Abstract: Land surface temperature (LST) retrieval from remote sensing data is pivotal for analyzing climate processes and surface energy budgets. However, LST retrieval is an ill-posed inverse problem, which becomes particularly severe when only a single band is available. In this paper, we propose a deeply coupled framework integrating mechanistic modeling and machine learning to enhance the accuracy and… ▽ More Land surface temperature (LST) retrieval from remote sensing data is pivotal for analyzing climate processes and surface energy budgets. However, LST retrieval is an ill-posed inverse problem, which becomes particularly severe when only a single band is available. In this paper, we propose a deeply coupled framework integrating mechanistic modeling and machine learning to enhance the accuracy and generalizability of single-channel LST retrieval. Training samples are generated using a physically-based radiative transfer model and a global collection of 5810 atmospheric profiles. A physics-informed machine learning framework is proposed to systematically incorporate the first principles from classical physical inversion models into the learning workflow, with optimization constrained by radiative transfer equations. Global validation demonstrated a 30% reduction in root-mean-square error versus standalone methods. Under extreme humidity, the mean absolute error decreased from 4.87 K to 2.29 K (53% improvement). Continental-scale tests across five continents confirmed the superior generalizability of this model. △ Less

Submitted 22 April, 2025; v1 submitted 10 April, 2025; originally announced April 2025.

Higher-Order Exceptional Points Induced by Non-Markovian Environments

Authors: H. Z. Shen, X. C. Zhang, L. Y. Ning, Zhi-Guang Lu, Yan-Hui Zhou, Cheng Shang

Abstract: Exceptional points (EPs) are central to non-Hermitian physics because of their unique properties and broad application prospects. While extensively studied in parity-time ($\mathcal{P}\mathcal{T}$)-symmetric systems and under Markovian dynamics, their exploration in broader pseudo-Hermitian settings, particularly in those involving non-Markovian environments, remains largely unexplored. In this st… ▽ More Exceptional points (EPs) are central to non-Hermitian physics because of their unique properties and broad application prospects. While extensively studied in parity-time ($\mathcal{P}\mathcal{T}$)-symmetric systems and under Markovian dynamics, their exploration in broader pseudo-Hermitian settings, particularly in those involving non-Markovian environments, remains largely unexplored. In this study, we investigate a pseudo-Hermitian system consisting of three coupled optical cavities interacting with non-Markovian environments. Compared to the Markovian baseline, we demonstrate that the emergence of non-Markovian memory effects enlarges the dimensionality of the parameter space of the system, thereby giving rise to higher-order EPs. Furthermore, we show that these non-Markovianity-induced higher-order EPs admit a topological characterization as defects in the relevant pseudo-Hermitian parameter space, with quantized charges described by resultant winding numbers. Moreover, we observe that the pseudo-Hermitian system with an effective gain induced by coherent perfect absorption enables the higher-order EPs to be directly read out from the output spectrum. We also note that the non-Markovian mechanism for generating higher-order EPs is not restricted to pseudo-Hermitian systems, but can be extended to generic non-Hermitian quantum systems. Additionally, possible experimental implementations based on superconducting circuits are also discussed. △ Less

Submitted 19 July, 2026; v1 submitted 1 April, 2025; originally announced April 2025.

Comments: 21 pages, 7 figures, 2 table. This updated version is essentially identical to the version published in Laser & Photonics Reviews

Journal ref: Laser & Photonics Reviews, e71535 (2026)

Nonreciprocity and unidirectional invisibility in three optical modes with non-Markovian effects

Authors: H. Yi, T. Z. Luan, W. Y. Hu, Cheng Shang, Yan-Hui Zhou, Zhi-Cheng Shi, H. Z. Shen

Abstract: In this work, we construct three coupled optical modes systems to obtain effective Hamiltonian mediated by coherent dissipative coupling during adiabatic elimination of large dissipation mode. We investigate the cooperative effect of coherent and dissipative photon-photon couplings in an open cavity system, which leads to nonreciprocity with a considerably large isolation ratio and flexible contro… ▽ More In this work, we construct three coupled optical modes systems to obtain effective Hamiltonian mediated by coherent dissipative coupling during adiabatic elimination of large dissipation mode. We investigate the cooperative effect of coherent and dissipative photon-photon couplings in an open cavity system, which leads to nonreciprocity with a considerably large isolation ratio and flexible controllability. We discover unidirectional invisibility for electromagnetic wave propagation, which appears at the zero-damping condition (ZDC) for hybrid photon-photon modes and obtain transmission spectrum on the ZDC. We study the influences of the parameters on the nonreciprocal transmission of the system to capture the generic physics of the interference between coherent and dissipative couplings, which accurately reproduces the results of numerical simulation over a broad range of parameters. Moreover, we extend the study of nonreciprocal transmission with the Markovian approximation to the non-Markovian environments, which consist of a collection of oscillators (bosonic photonic modes) and give the adiabatic elimination method with non-Markovian effects. We illustrate that nonreciprocal transmission on ZDC exhibits a crossover from the non-Markovian to the Markovian regimes by controlling the environmental spectral width. This indicates a promising way to enhance or steer quantum nonreciprocal devices in optical cavities and provides potential applications for precision measurements and optical communications with non-Markovian effects. △ Less

Submitted 29 March, 2025; originally announced March 2025.

Comments: 20 pages, 11 figures

Emergent Non-Markovian Gain in Open Quantum Systems

Authors: H. Z. Shen, Cheng Shang, Yan-Hui Zhou, X. X. Yi

Abstract: Non-Markovian dynamics go beyond the Markovian approximation by capturing memory effects and information backflow in open quantum systems, which are crucial for describing realistic physical processes. In this work, we study the exact non-Markovian dynamics of a driven cavity coupled to an anisotropic three-dimensional photonic-crystal environment via counterrotating-wave interactions. We derive a… ▽ More Non-Markovian dynamics go beyond the Markovian approximation by capturing memory effects and information backflow in open quantum systems, which are crucial for describing realistic physical processes. In this work, we study the exact non-Markovian dynamics of a driven cavity coupled to an anisotropic three-dimensional photonic-crystal environment via counterrotating-wave interactions. We derive an exact analytical expression for the cavity amplitude satisfying the integro-differential equation, which includes the contributions of the bound states outside the continuum and the dissipative parts with the continuum spectrum. Based on the characteristic function method, we derive the exact non-Markovian master equation for the cavity, which contributes to the gain of the cavity. We give the physical origin of non-Markovian gain in the presence of bound states in the system consisting of cavity and environment, which has no Markovian counterparts due to the nonexponential gain in the non-Markovian structured environment. We find that three different types of bound states can be formed in the system, containing one bound state with no inversion of photon number, two bound states with the periodic equal-amplitude oscillation, and the gain with two complex roots without the bound states formation. We derive a current equation including the source from the driving field, the transient current induced by the change in the number of photons, and the two-photon current caused by the counterrotating-wave term. The results are compared with those given by the rotating-wave interactions and extended to a more general quantum network involving an arbitrary number of coupled cavities. Our findings may pave the way for a deeper understanding of non-Markovian dynamics with gain in quantum networks involving counterrotating-wave effects. △ Less

Submitted 27 March, 2025; originally announced March 2025.

Comments: 17 pages, 13 figures

Nonreciprocal quantum router with non-Markovian environments

Authors: T. Z. Luan, Cheng Shang, H. Yi, J. L. Li, Yan-Hui Zhou, Shuang Xu, H. Z. Shen

Abstract: Quantum routers are essential elements of quantum networks, enabling coherent information transfer between distant nodes. While their behavior has been extensively studied under Markovian approximations, investigations in non-Markovian regimes remain limited. In this paper, we study a nonreciprocal quantum router embedded in non-Markovian environments, enabling directional control of single photon… ▽ More Quantum routers are essential elements of quantum networks, enabling coherent information transfer between distant nodes. While their behavior has been extensively studied under Markovian approximations, investigations in non-Markovian regimes remain limited. In this paper, we study a nonreciprocal quantum router embedded in non-Markovian environments, enabling directional control of single photons, which allows transmission from one side while blocking it from the other. The cascade system under study consists of two quantum nodes: one comprising two coupled coplanar-waveguide resonators and the other featuring a superconducting ring resonator. Each node is respectively coupled to a single Yttrium iron garnet (YIG) disk, with nonreciprocity arising from the selective coupling between magnons and microwave photons in our model. We analytically derive the transmission and reflection spectra of the system when a photon is input respectively from the left and right sides of the transmission line in the non-Markovian regimes. Our results demonstrate that, with appropriate parameters, a single photon can be routed from a given input port to either of the two output ports, while being fully absorbed when incident from the opposite side. We further compare the scattering behavior in non-Markovian and Markovian regimes through numerical simulations. In the non-Markovian case, the transmission spectrum exhibits two unity peaks (two valleys with a minimum value of zero), whereas in the Markovian case, high transmission appears only within a narrow window near zero detuning when the photon is injected from the left. As the environmental bandwidth increases, non-Markovian results converge to the Markovian limit. This formalism may enable new applications in quantum information and communication exploiting non-Markovianity. △ Less

Submitted 24 March, 2025; originally announced March 2025.

Comments: 18 pages, 11 figures

Intelligent Adaptive Metasurface in Complex Wireless Environments

Authors: Han Qing Yang, Jun Yan Dai, Hui Dong Li, Lijie Wu, Meng Zhen Zhang, Zi Hang Shen, Si Ran Wang, Zheng Xing Wang, Wankai Tang, Shi Jin, Jun Wei Wu, Qiang Cheng, Tie Jun Cui

Abstract: The programmable metasurface is regarded as one of the most promising transformative technologies for next-generation wireless system applications. Due to the lack of effective perception ability of the external electromagnetic environment, there are numerous challenges in the intelligent regulation of wireless channels, and it still relies on external sensors to reshape electromagnetic environmen… ▽ More The programmable metasurface is regarded as one of the most promising transformative technologies for next-generation wireless system applications. Due to the lack of effective perception ability of the external electromagnetic environment, there are numerous challenges in the intelligent regulation of wireless channels, and it still relies on external sensors to reshape electromagnetic environment as desired. To address that problem, we propose an adaptive metasurface (AMS) which integrates the capabilities of acquiring wireless environment information and manipulating reflected electromagnetic (EM) waves in a programmable manner. The proposed design endows the metasurfaces with excellent capabilities to sense the complex electromagnetic field distributions around them and then dynamically manipulate the waves and signals in real time under the guidance of the sensed information, eliminating the need for prior knowledge or external inputs about the wireless environment. For verification, a prototype of the proposed AMS is constructed, and its dual capabilities of sensing and manipulation are experimentally validated. Additionally, different integrated sensing and communication (ISAC) scenarios with and without the aid of the AMS are established. The effectiveness of the AMS in enhancing communication quality is well demonstrated in complex electromagnetic environments, highlighting its beneficial application potential in future wireless systems. △ Less

Submitted 13 November, 2024; originally announced November 2024.

Many-body nonequilibrium dynamics in a self-induced Floquet system

Authors: Yuechun Jiao, Yu Zhang, Jingxu Bai, Suotang Jia, C. Stuart Adams, Zhengyang Bai, Heng Shen, Jianming Zhao

Abstract: Floquet systems are periodically driven systems. In this framework, the system Hamiltonian and associated spectra of interest are modified, giving rise to new quantum phases of matter and nonequilibrium dynamics without static counterparts. Here we experimentally demonstrate a self-induced Floquet system in the interacting Rydberg gas. This originates from the photoionization of thermal Rydberg ga… ▽ More Floquet systems are periodically driven systems. In this framework, the system Hamiltonian and associated spectra of interest are modified, giving rise to new quantum phases of matter and nonequilibrium dynamics without static counterparts. Here we experimentally demonstrate a self-induced Floquet system in the interacting Rydberg gas. This originates from the photoionization of thermal Rydberg gases in a static magnetic field. Importantly, by leveraging the Rydberg electromagnetically induced transparency spectrum, we probe the nonequilibrium dynamics in the bistable regime and identify the emergence of a discrete time crystalline phase. Our work fills the experimental gap in the understanding the relation of multistability and dissipative discrete time crystalline phase. In this regard, it constitutes a highly controlled platform for exploring exotic nonequilibrium physics in dissipative interacting systems. △ Less

Submitted 20 November, 2024; v1 submitted 7 November, 2024; originally announced November 2024.

Comments: 6 pages, 4 figures

Journal ref: Phys. Rev. Lett. 135, 163603 (2025)

Optomechanical sensor network with fiber Bragg gratings

Authors: Shiwei Yang, Qiang Zhang, Linrun Yang, Hanghua Liu, Quansen Wang, Pengfei Zhang, Heng Shen, Yongmin Li

Abstract: Cavity optomechanics offers a versatile platform for both fundamental physics and ultrasensitive sensing. Importantly, resonant enhancement in both optical and mechanical responses enables the highly sensitive optical detection of small forces, displacements, vibrations, and magnetic fields, enabling it a promising candidate of the next generation of ultrasensitive sensor networks. However, this i… ▽ More Cavity optomechanics offers a versatile platform for both fundamental physics and ultrasensitive sensing. Importantly, resonant enhancement in both optical and mechanical responses enables the highly sensitive optical detection of small forces, displacements, vibrations, and magnetic fields, enabling it a promising candidate of the next generation of ultrasensitive sensor networks. However, this is impeded by the fiber optic-incompatibility and intrinsic nature of existing optomechanical sensors. Here, we report the first demonstration of an optomechanical sensor network in terms of magnetic field detection, wherein multiple fiber-optic optomechanical sensors are connected into a standard single mode fiber. Building upon a commercially available fiber Bragg gratings, we realize a robust low-loss, low-noise, and polarization-insensitive coupling with light sources in a way compatible with fiber optics. This thus enables our optomechanical senor to fulfill the requirements for ultrasensitive sensor networks. Furthermore, in this sensor network we demonstrate the sensitivity of 8.73 pm/Gs for DC magnetic fields and 537 fT/Hz1/2 for AC magnetic fields in a magnetically unshielded environment with the ambient temperature and pressure, better than the reported values in previous optomechanical magnetometers. Our work sheds light on exploiting cavity optomechanics in the practical applications and ultrasensitive senor networks. △ Less

Submitted 10 September, 2024; originally announced September 2024.

Study of the decay and production properties of $D_{s1}(2536)$ and $D_{s2}^*(2573)$

Authors: M. Ablikim, M. N. Achasov, P. Adlarson, O. Afedulidis, X. C. Ai, R. Aliberti, A. Amoroso, Q. An, Y. Bai, O. Bakina, I. Balossino, Y. Ban, H. -R. Bao, V. Batozskaya, K. Begzsuren, N. Berger, M. Berlowski, M. Bertani, D. Bettoni, F. Bianchi, E. Bianco, A. Bortone, I. Boyko, R. A. Briere, A. Brueggemann , et al. (645 additional authors not shown)

Abstract: The $e^+e^-\rightarrow D_s^+D_{s1}(2536)^-$ and $e^+e^-\rightarrow D_s^+D^*_{s2}(2573)^-$ processes are studied using data samples collected with the BESIII detector at center-of-mass energies from 4.530 to 4.946~GeV. The absolute branching fractions of $D_{s1}(2536)^- \rightarrow \bar{D}^{*0}K^-$ and $D_{s2}^*(2573)^- \rightarrow \bar{D}^0K^-$ are measured for the first time to be… ▽ More The $e^+e^-\rightarrow D_s^+D_{s1}(2536)^-$ and $e^+e^-\rightarrow D_s^+D^*_{s2}(2573)^-$ processes are studied using data samples collected with the BESIII detector at center-of-mass energies from 4.530 to 4.946~GeV. The absolute branching fractions of $D_{s1}(2536)^- \rightarrow \bar{D}^{*0}K^-$ and $D_{s2}^*(2573)^- \rightarrow \bar{D}^0K^-$ are measured for the first time to be $(35.9\pm 4.8\pm 3.5)\%$ and $(37.4\pm 3.1\pm 4.6)\%$, respectively. The measurements are in tension with predictions based on the assumption that the $D_{s1}(2536)$ and $D_{s2}^*(2573)$ are dominated by a bare $c\bar{s}$ component. The $e^+e^-\rightarrow D_s^+D_{s1}(2536)^-$ and $e^+e^-\rightarrow D_s^+D^*_{s2}(2573)^-$ cross sections are measured, and a resonant structure at around 4.6~GeV with a width of 50~MeV is observed for the first time with a statistical significance of $15σ$ in the $e^+e^-\rightarrow D_s^+D^*_{s2}(2573)^-$ process. It could be the $Y(4626)$ found by the Belle collaboration in the $D_s^+D_{s1}(2536)^{-}$ final state, since they have similar masses and widths. There is also evidence for a structure at around 4.75~GeV in both processes. △ Less

Submitted 10 July, 2024; originally announced July 2024.

In vacuum metasurface for optical microtrap array

Authors: Donghao Li, Qiming Liao, Beining Xu, Thomas Zentgraf, Emmanuel Narvaez Castaneda, Yaoting Zhou, Keyu Qin, Zhongxiao Xu, Heng Shen, Lingling Huang

Abstract: Optical tweezer arrays of laser-cooled and individual controlled particles have revolutionized the atomic, molecular and optical physics, and they afford exquisite capabilities for applications in quantum simulation of many-body physics, quantum computation and quantum sensing. Underlying this development is the technical maturity of generating scalable optical beams, enabled by active components… ▽ More Optical tweezer arrays of laser-cooled and individual controlled particles have revolutionized the atomic, molecular and optical physics, and they afford exquisite capabilities for applications in quantum simulation of many-body physics, quantum computation and quantum sensing. Underlying this development is the technical maturity of generating scalable optical beams, enabled by active components and high numerical aperture objective. However, such a complex combination of bulk optics outside the vacuum chamber is very sensitive to any vibration and drift. Here we demonstrate the generation of 3*3 static tweezer array with a single chip-scale multifunctional metasurface element in vacuum, replacing the meter-long free space optics. Fluorescence counts on the camera validates the successfully trapping of the atomic ensemble array. Further, we discuss the strategy to achieve low scattering and crosstalk, where a metasurface design featuring dual-wavelength independent control is included. Our results, together with other recent development in integrated photonics for cold atoms, could pave the way for compact and portable quantum sensors and simulators in platforms of neutral atom arrays. △ Less

Submitted 22 May, 2025; v1 submitted 8 July, 2024; originally announced July 2024.

A Staged Approach using Machine Learning and Uncertainty Quantification to Predict the Risk of Hip Fracture

Authors: Anjum Shaik, Kristoffer Larsen, Nancy E. Lane, Chen Zhao, Kuan-Jui Su, Joyce H. Keyak, Qing Tian, Qiuying Sha, Hui Shen, Hong-Wen Deng, Weihua Zhou

Abstract: Despite advancements in medical care, hip fractures impose a significant burden on individuals and healthcare systems. This paper focuses on the prediction of hip fracture risk in older and middle-aged adults, where falls and compromised bone quality are predominant factors. We propose a novel staged model that combines advanced imaging and clinical data to improve predictive performance. By using… ▽ More Despite advancements in medical care, hip fractures impose a significant burden on individuals and healthcare systems. This paper focuses on the prediction of hip fracture risk in older and middle-aged adults, where falls and compromised bone quality are predominant factors. We propose a novel staged model that combines advanced imaging and clinical data to improve predictive performance. By using CNNs to extract features from hip DXA images, along with clinical variables, shape measurements, and texture features, our method provides a comprehensive framework for assessing fracture risk. A staged machine learning-based model was developed using two ensemble models: Ensemble 1 (clinical variables only) and Ensemble 2 (clinical variables and DXA imaging features). This staged approach used uncertainty quantification from Ensemble 1 to decide if DXA features are necessary for further prediction. Ensemble 2 exhibited the highest performance, achieving an AUC of 0.9541, an accuracy of 0.9195, a sensitivity of 0.8078, and a specificity of 0.9427. The staged model also performed well, with an AUC of 0.8486, an accuracy of 0.8611, a sensitivity of 0.5578, and a specificity of 0.9249, outperforming Ensemble 1, which had an AUC of 0.5549, an accuracy of 0.7239, a sensitivity of 0.1956, and a specificity of 0.8343. Furthermore, the staged model suggested that 54.49% of patients did not require DXA scanning. It effectively balanced accuracy and specificity, offering a robust solution when DXA data acquisition is not always feasible. Statistical tests confirmed significant differences between the models, highlighting the advantages of the advanced modeling strategies. Our staged approach could identify individuals at risk with a high accuracy but reduce the unnecessary DXA scanning. It has great promise to guide interventions to prevent hip fractures with reduced cost and radiation. △ Less

Submitted 30 May, 2024; originally announced May 2024.

Comments: 29 pages, 5 figures, 6 tables

Design of Targeted Community-Based Resource Allocation in the Presence of Vaccine Hesitancy via a Data-Driven Compartmental Stochastic Optimization Model

Authors: Hieu Bui, Sandra Eksioglu, Ruben Proano, Haoming Shen

Abstract: Vaccines have proven effective in mitigating the threat of severe infections and deaths during outbreaks of infectious diseases. However, vaccine hesitancy (VH) complicates disease spread prediction and healthcare resource assessment across regions and populations. We propose a modeling framework that integrates an epidemiological compartmental model that captures the spread of an infectious disea… ▽ More Vaccines have proven effective in mitigating the threat of severe infections and deaths during outbreaks of infectious diseases. However, vaccine hesitancy (VH) complicates disease spread prediction and healthcare resource assessment across regions and populations. We propose a modeling framework that integrates an epidemiological compartmental model that captures the spread of an infectious disease within a multi-stage stochastic program (MSP) that determines the allocation of critical resources under uncertainty. The proposed compartmental MSP model adaptively manages the allocation of resources to account for changes in population behavior toward vaccines (i.e., variability in VH), the unique patterns of disease spread, and the availability of healthcare resources over time and space. The compartmental MSP model allowed us to analyze the price of fairness in resource allocation. Using real COVID-19 vaccination and healthcare resource data from Arkansas, U.S. (January-May 2021), our findings include: (i) delaying the initial deployment of additional ventilators by one month could lead to an average increase in the expected number of deaths by 285.41/month, highlighting the importance of prompt action; (ii) each additional ventilator in the initial stockpile and in supply leads to a decrease in the expected number of deaths by 1.09/month and 0.962/month, respectively, emphasizing the importance of maintaining a large stockpile and scalable production response; (iii) the cost of ensuring equitable resource allocation varies over time and location, peaking during the peak of a disease outbreak and in densely populated areas. This study emphasizes the importance of flexible, informed public health decision-making and preparedness, providing a model for effective resource allocation in public health emergencies. △ Less

Submitted 8 May, 2024; originally announced May 2024.

The convolutional neural networks for analysing the micro-cavity array multi-mode quantum frequency comb spectrum features

Authors: H. Shen, C. Y. Zhao

Abstract: The research on sensing the sensitivity of the light field in the whispering gallery mode (WGM) to the micro-cavity environment has already appeared, which uses the frequency shift of the light field in the WGM or the sensitivity of the resonance peak frequency shift. Multi-mode comb teeth of optical frequency comb(OFC) generated by nonlinear micro-cavity have excellent sensitivity to micro-cavity… ▽ More The research on sensing the sensitivity of the light field in the whispering gallery mode (WGM) to the micro-cavity environment has already appeared, which uses the frequency shift of the light field in the WGM or the sensitivity of the resonance peak frequency shift. Multi-mode comb teeth of optical frequency comb(OFC) generated by nonlinear micro-cavity have excellent sensitivity to micro-cavity environment, and they have more sensitivity degrees of freedom compared with WGM light field (the strength of each comb tooth can be influenced by micro-cavity environment). The influence of different substances on the environmental parameters of micro-cavity is complex and nonlinear, so we use machine learning method to automatically extract the spectrum characteristics, the average accuracy of single-parameter identification attains to 99.5%, and the average accuracy of double parameter identification attains to 97.0%. Based on the integration of micro-cavity OFC and wave-guide coupling structure, we propose an set of fluid characteristics detection integrated device in theoretically. △ Less

Submitted 28 June, 2025; v1 submitted 15 April, 2024; originally announced April 2024.

Comments: 14pages,7figures,27references

Optomechanical second-order sidebands and group delays in a spinning resonator with parametric amplifier and non-Markovian effects

Authors: Wei Zhang, H. Z. Shen

Abstract: We investigate the generation of the frequency components at the second-order sidebands based on a spinning resonator containing a degenerate optical parametric amplifier (OPA). We show an OPA driven by different pumping frequencies inside a cavity can enhance and modulate the amplitude of the second-order sideband with different influences. We find that both the second-order sideband amplitude an… ▽ More We investigate the generation of the frequency components at the second-order sidebands based on a spinning resonator containing a degenerate optical parametric amplifier (OPA). We show an OPA driven by different pumping frequencies inside a cavity can enhance and modulate the amplitude of the second-order sideband with different influences. We find that both the second-order sideband amplitude and its associated group delay sensitively depend on the nonlinear gain of the OPA, the phase of the field driving the OPA, the rotation speed of the resonator, and the incident direction of the input fields. Tuning the pumping frequency of the OPA can remain the localization of the maximum value of the sideband efficiency and nonreciprocal behavior due to the optical Sagnac effect, which also can adjust the linewidth of the suppressive window of the second-order sideband. Furthermore, we extend the study of second-order sideband to the non-Markovian bath which consists of a collection of infinite oscillators (bosonic photonic modes). We illustrate the second-order sidebands in a spinning resonator exhibit a transition from the non-Markovian to Markovian regime by controlling environmental spectral width. \textbf{We also study the influences of the decay from the non-Markovian environment coupling to an external reservoir on the efficiency of second-order upper sidebands.} This indicates a promising new way to enhance or steer optomechanically induced transparency devices in nonlinear optical cavities and provides potential applications for precision measurement, optical communications, and quantum sensing. △ Less

Submitted 11 April, 2024; originally announced April 2024.

Comments: 24 pages, 17 figures

Journal ref: Phys. Rev. A 109, 033701 (2024)

Effect of Substitution Group on Intramolecular Hydrogen Bond of Amino Alcohols from Raman spectroscopy

Authors: Honghui Zhao, Hongyuan Shen, Ao You, Yuanqin Yu

Abstract: Due to the simultaneous presence of two polar functional groups and flexible spatial structure, Aminoethanol (AE) is a model system for investigating the relationship between intramolecular hydrogen bonding and conformational equlibrium. In addition, Aminoethanol and their derivatives exhibit remarkable efficacy in the reversible capture of carbon dioxide. The intramoleculr hydrogen bond of 2-AE i… ▽ More Due to the simultaneous presence of two polar functional groups and flexible spatial structure, Aminoethanol (AE) is a model system for investigating the relationship between intramolecular hydrogen bonding and conformational equlibrium. In addition, Aminoethanol and their derivatives exhibit remarkable efficacy in the reversible capture of carbon dioxide. The intramoleculr hydrogen bond of 2-AE is determined by a subtle balance between electrostatic interactions, Van der Waals interactions, and steric effects. Changing the polarity of functional groups can regulate the strength of intramolecular hydrogen bonds. In this work, using spontaneous Raman spectroscopy combined with theoretical calculations, we investigated the effect of N-terminated substitution group on intramolecular hydrogen bond. When the H atom of NH2 functional group is replaced by electron-donating groups such as methyl and ethyl, it was observed experimentally that the red-shift of OH stretching vibration frequency caused by O-H... N intramolecular hydrogen bonding increases significantly and then the corresponding peak intensity increases. This indicates that with the introduction of substitutions on the N atom, the O-H... N intramolecular hydrogen bond in 2-AE is enhanced and the corresponding conformational population increases. The results of AIM and NCI analysis are consistent with experimental observations. These results provide insights for regulating the strength of intramolecular hydrogen bonds and also contribute to the strategy of CO2 capture. △ Less

Submitted 21 March, 2024; originally announced March 2024.

Observation of multiple time crystals in a driven-dissipative system with Rydberg gas

Authors: Yuechun Jiao, Weilun Jiang, Yu Zhang, Jingxu Bai, Yunhui He, Heng Shen, Jianming Zhao, Suotang Jia

Abstract: Time crystals, as temporal analogs of space crystals, manifest as stable and periodic behavior that breaks time translation symmetry. In an open quantum system, many-body interaction subjected to dissipation allows one to develop the time crystalline order in an unprecedented way, as refer to dissipative time crystals. Here we report the observation of multiple time crystals in the continuously dr… ▽ More Time crystals, as temporal analogs of space crystals, manifest as stable and periodic behavior that breaks time translation symmetry. In an open quantum system, many-body interaction subjected to dissipation allows one to develop the time crystalline order in an unprecedented way, as refer to dissipative time crystals. Here we report the observation of multiple time crystals in the continuously driven-dissipative and strongly interacting Rydberg thermal gases, in which continuous time crystals, sub-harmonic time crystals, and high-harmonic time crystals are observed in the same system by manipulating the Rydberg excitation. Our work provides new ways to explore the nonequilibrium phases of matter in open systems. Such time crystals with persistent oscillation rooted in emergent quantum correlations, may emerge as a ubiquitous tool in quantum metrology, for instance, continuous sensing and parameter estimation surpassing the standard quantum limit. △ Less

Submitted 7 October, 2025; v1 submitted 20 February, 2024; originally announced February 2024.

Comments: 9 pages, 3 figures

Journal ref: Nature Communications, 16, 8491 (2025)

Giant magnetocaloric effect and hysteresis loss in Mn$_x$Fe$_{2-x}$P$_{0.5}$Si$_{0.5}$ ($x$ = 0.7-1.2) microwires at ambient temperatures

Authors: Lin Luo, Hongxian Shen, Lunyong Zhang, Yongjiang Huang, Jianfei Sun, Manh-Huong Phan

Abstract: Magnetocaloric microwires are very promising for energy-efficient magnetic refrigeration in micro electromechanical systems (MEMS) and nano electromechanical systems (NEMS). Creating microwires that exhibit large magnetocaloric effects around room temperature represents an important but challenging task. Here, we report a tunable giant magnetocaloric effect around room temperature in Mn$_x$Fe… ▽ More Magnetocaloric microwires are very promising for energy-efficient magnetic refrigeration in micro electromechanical systems (MEMS) and nano electromechanical systems (NEMS). Creating microwires that exhibit large magnetocaloric effects around room temperature represents an important but challenging task. Here, we report a tunable giant magnetocaloric effect around room temperature in Mn$_x$Fe$_{2-x}$P$_{0.5}$Si$_{0.5}$ ($x$ = 0.7-1.2) microwires by utilizing a melt-extraction technique paired with thermal treatment and chemical engineering. The isothermal magnetic entropy change DeltaSiso and Curie temperature (TC) can be tuned by adjusting the Mn/Fe ratio. The TC varies from 351 to 190 K as x increases from 0.8 to 1.2. Among the compositions investigated, the x = 0.9 sample shows the largest value of DeltaSiso = 18.3 J kg$^{-1}$ K$^{-1}$ for a field change of 5 T around 300 K. After subtracting magnetic hysteresis loss, a large refrigerant capacity of ~284.6 J kg$^{-1}$ is achieved. Our study paves a new pathway for the design of novel magnetocaloric microwires for active magnetic refrigeration at ambient temperatures. △ Less

Submitted 14 December, 2023; originally announced December 2023.

Advanced magnetocaloric microwires: What does the future hold?

Authors: Hongxian Shen, Nguyen Thi My Duc, Hillary Belliveau, Lin Luo, Yunfei Wang, Jianfei Sun, Faxiang Qin, Manh-Huong Phan

Abstract: Magnetic refrigeration (MR) based on the magnetocaloric effect (MCE) is a promising alternative to conventional vapor compression refrigeration techniques. The cooling efficiency of a magnetic refrigerator depends on its refrigeration capacity and operation frequency. Existing refrigerators possess limited cooling efficiency due to the low operating frequency (around tens of Hz). Theory predicts t… ▽ More Magnetic refrigeration (MR) based on the magnetocaloric effect (MCE) is a promising alternative to conventional vapor compression refrigeration techniques. The cooling efficiency of a magnetic refrigerator depends on its refrigeration capacity and operation frequency. Existing refrigerators possess limited cooling efficiency due to the low operating frequency (around tens of Hz). Theory predicts that reducing geometrical effects can increase the operation frequency by reducing the relaxation time of a magnetic material. As compared to other shapes, magnetocaloric wires transfer heat most effectively to a surrounding environment, due to their enhanced surface area. The wire shape also yields a good mechanical response, reducing the relaxation time and consequently increasing the operation frequency of the cooling device. Experiments have validated the theoretical predictions. By assembling microwires with different magnetocaloric properties and Curie temperatures into a laminate structure, a table-like magnetocaloric bed can be created and used as an active cooling device for micro-electro-mechanical system (MEMS) and nano-electro-mechanical system (NEMS). This paper assesses recent progress in the development of magnetocaloric microwires and sheds light on the important factors affecting the magnetocaloric behavior and cooling efficiency in microwire systems. Challenges, opportunities, and strategies regarding the development of advanced magnetocaloric microwires are also discussed. △ Less

Submitted 14 December, 2023; originally announced December 2023.

Journal ref: Vietnam Journal of Science, Technology and Engineering, 2023

A method to determine formation position of comb teeth of Kerr micro-comb under the influence of and nonlinearity

Authors: Hang Shen, Chaoying Zhaoa

Abstract: The Kerr microcomb has a huge potential advantage as a quantum computing platform because of its large-scale and globally coherent optical modes. The micro-comb has always faced a primary problem is how to increase the controllability of frequency domain modes. In this work, based on the pump thresholds of different side modes, we establish a set of method for determining the formation position of… ▽ More The Kerr microcomb has a huge potential advantage as a quantum computing platform because of its large-scale and globally coherent optical modes. The micro-comb has always faced a primary problem is how to increase the controllability of frequency domain modes. In this work, based on the pump thresholds of different side modes, we establish a set of method for determining the formation position of side mode comb teeth in a micro-ring cavity with second-order ( ) and third-order ( ) nonlinearity. Based on the second-order autocorrelation function spectrum simulation, our quantum dynamical explanation has a good agreement with the experimental results. △ Less

Submitted 31 July, 2023; originally announced August 2023.

Comments: 5figures. arXiv admin note: text overlap with arXiv:2001.02356 by other authors

A physics-constrained machine learning method for mapping gapless land surface temperature

Authors: Jun Ma, Huanfeng Shen, Menghui Jiang, Liupeng Lin, Chunlei Meng, Chao Zeng, Huifang Li, Penghai Wu

Abstract: More accurate, spatio-temporally, and physically consistent LST estimation has been a main interest in Earth system research. Developing physics-driven mechanism models and data-driven machine learning (ML) models are two major paradigms for gapless LST estimation, which have their respective advantages and disadvantages. In this paper, a physics-constrained ML model, which combines the strengths… ▽ More More accurate, spatio-temporally, and physically consistent LST estimation has been a main interest in Earth system research. Developing physics-driven mechanism models and data-driven machine learning (ML) models are two major paradigms for gapless LST estimation, which have their respective advantages and disadvantages. In this paper, a physics-constrained ML model, which combines the strengths in the mechanism model and ML model, is proposed to generate gapless LST with physical meanings and high accuracy. The hybrid model employs ML as the primary architecture, under which the input variable physical constraints are incorporated to enhance the interpretability and extrapolation ability of the model. Specifically, the light gradient-boosting machine (LGBM) model, which uses only remote sensing data as input, serves as the pure ML model. Physical constraints (PCs) are coupled by further incorporating key Community Land Model (CLM) forcing data (cause) and CLM simulation data (effect) as inputs into the LGBM model. This integration forms the PC-LGBM model, which incorporates surface energy balance (SEB) constraints underlying the data in CLM-LST modeling within a biophysical framework. Compared with a pure physical method and pure ML methods, the PC-LGBM model improves the prediction accuracy and physical interpretability of LST. It also demonstrates a good extrapolation ability for the responses to extreme weather cases, suggesting that the PC-LGBM model enables not only empirical learning from data but also rationally derived from theory. The proposed method represents an innovative way to map accurate and physically interpretable gapless LST, and could provide insights to accelerate knowledge discovery in land surface processes and data mining in geographical parameter estimation. △ Less

Submitted 2 July, 2023; originally announced July 2023.

Giant room-temperature nonlinearities from a monolayer Janus topological semiconductor

Authors: Jiaojian Shi, Haowei Xu, Christian Heide, Changan HuangFu, Chenyi Xia, Felipe de Quesada, Hongzhi Shen, Tianyi Zhang, Leo Yu, Amalya Johnson, Fang Liu, Enzheng Shi, Liying Jiao, Tony Heinz, Shambhu Ghimire, Ju Li, Jing Kong, Yunfan Guo, Aaron M. Lindenberg

Abstract: Nonlinear optical materials possess wide applications, ranging from terahertz and mid-infrared detection to energy harvesting. Recently, the correlations between nonlinear optical responses and topological properties, such as Berry curvature and the quantum metric tensor, have stimulated great interest. Here, we report giant room-temperature nonlinearities in an emergent non-centrosymmetric two-di… ▽ More Nonlinear optical materials possess wide applications, ranging from terahertz and mid-infrared detection to energy harvesting. Recently, the correlations between nonlinear optical responses and topological properties, such as Berry curvature and the quantum metric tensor, have stimulated great interest. Here, we report giant room-temperature nonlinearities in an emergent non-centrosymmetric two-dimensional topological material, the Janus transition metal dichalcogenides in the 1T' phase, which are synthesized by an advanced atomic-layer substitution method. High harmonic generation, terahertz emission spectroscopy, and second harmonic generation measurements consistently reveal orders-of-the-magnitude enhancement in terahertz-frequency nonlinearities of 1T' MoSSe (e.g., > 50 times higher than 2H MoS$_2$ for 18th order harmonic generation; > 20 times higher than 2H MoS$_2$ for terahertz emission). It is elucidated that such colossal nonlinear optical responses come from topological band mixing and strong inversion symmetry breaking due to the Janus structure. Our work defines general protocols for designing materials with large nonlinearities and preludes the applications of topological materials in optoelectronics down to the monolayer limit. This two-dimensional form of topological materials also constitute a unique platform for examining origin of the anomalous high-harmonic generation, with potential applications as building blocks for scalable attosecond sources. △ Less

Submitted 3 April, 2023; originally announced April 2023.

Comments: 22 pages, 4 figures