Showing 1–50 of 176 results for author: Huang, Q

Bell nonlocality with directly generated telecom-band spin-photon entanglement

Authors: Dong-Yu Huang, Jian Wang, Xiao-Long Zhou, Ze-Min Shen, Si-Jian He, Qi-Yang Huang, Yi-Jia Liu, Yu-Shu Chen, Quan Jiang, Chuan-Feng Li, Guang-Can Guo

Abstract: Quantum nonlocality, typically revealed through entanglement distribution across quantum networks, is a cornerstone of quantum information science. Long-distance distribution of entanglement requires the information carrier, i.e. flying photons, to operate in the minimum-loss telecom band of optical fiber. While extensive efforts have been devoted to the direct generation of entanglement between C… ▽ More Quantum nonlocality, typically revealed through entanglement distribution across quantum networks, is a cornerstone of quantum information science. Long-distance distribution of entanglement requires the information carrier, i.e. flying photons, to operate in the minimum-loss telecom band of optical fiber. While extensive efforts have been devoted to the direct generation of entanglement between C-band telecom photons and various stationary spins, the verification of quantum nonlocality remains an outstanding challenge. Here, utilizing a dipole transition in rubidium atoms with a wavelength of 1530 nm and a cavity-assisted protocol, we achieve resonant excitation and direct emission of C-band telecom photons from a single atom, generating spin-photon entanglement with a measured Bell state fidelity exceeding 91.4%. We then verify Bell nonlocality by observing a Bell inequality violation of 2.455(77) > 2 using this high-quality entangled pair. These results extend the wavelength of a single-atom quantum emitter to the telecom C-band, achieving sufficiently high-fidelity spin-photon entanglement to finally verify Bell nonlocality. This work thereby provides a promising building block for a large-scale atom-based quantum network capable of distributed quantum metrology and long-distance quantum communication. △ Less

Submitted 8 August, 2026; originally announced August 2026.

Comments: 13 pages, 4+5 figures, 1 table

Steering Tropical Cyclones Using Small Perturbations in an AI Weather Model

Authors: Qin Huang, Moyan Liu, Yeongbin Kwon, Upmanu Lall

Abstract: Tropical cyclone (TC) trajectories are governed by large-scale steering flows and exhibit sensitive dependence on atmospheric initial conditions. Using Hurricane Sandy (2012) in the Aurora AI weather model, we investigate whether targeted thermodynamic perturbations can induce meaningful track deviations. Two distinct perturbation regimes emerge. In the Caribbean, forward finite-time Lyapunov expo… ▽ More Tropical cyclone (TC) trajectories are governed by large-scale steering flows and exhibit sensitive dependence on atmospheric initial conditions. Using Hurricane Sandy (2012) in the Aurora AI weather model, we investigate whether targeted thermodynamic perturbations can induce meaningful track deviations. Two distinct perturbation regimes emerge. In the Caribbean, forward finite-time Lyapunov exponent (FTLE) diagnostics identify dynamically sensitive regions within Sandy's steering flow, where perturbations produce substantially larger responses than random placement. In the Pacific, a preferred corridor near 165W influences Sandy through Rossby wave teleconnections, confirmed using Takaya-Nakamura wave activity flux diagnostics. Despite their different physical pathways, both regimes share a common amplification mechanism: small initial perturbations generate modest trajectory offsets that are rapidly amplified when Sandy enters the highly sensitive recurvature region. The largest experiments produce track deviations exceeding 500 km after seven days. These results provide a proof-of-concept demonstration of the Weather Jiu-Jitsu framework, illustrating how targeted perturbations can be amplified through atmospheric dynamics in an AI weather model. Because the required perturbations exceed current operational cloud-seeding capabilities, the experiments should be interpreted as a theoretical sensitivity analysis rather than an operational weather modification strategy. △ Less

Submitted 10 June, 2026; v1 submitted 27 May, 2026; originally announced May 2026.

A Simulation Methodology Testbed for Typhoon Sensitivity Analysis: Framework Development and Perturbation-Response Experiments with the Pangu Weather Model

Authors: Yuehua Peng, Yuchen Zhang, Qin Huang, Chengzhi Ye, Jingsong Yang

Abstract: Understanding how typhoons respond to localized perturbations in their environmental fields is fundamental to assessing the limits of predictability and exploring the potential for track or intensity intervention. This study develops a dedicated simulation methodology testbed for typhoon sensitivity analysis by integrating the Pangu weather model, a high-precision AI forecasting system, with Propo… ▽ More Understanding how typhoons respond to localized perturbations in their environmental fields is fundamental to assessing the limits of predictability and exploring the potential for track or intensity intervention. This study develops a dedicated simulation methodology testbed for typhoon sensitivity analysis by integrating the Pangu weather model, a high-precision AI forecasting system, with Proportional-Integral-Derivative (PID) closed-loop techniques. The testbed is constructed with modular functional blocks including a meteorological prediction module, an artificial perturbation input interface, a typhoon quantitative modeling module, and a PID closed-loop test module, implemented via a cross-platform MATLAB/ONNX technical framework. A Single-Input Single-Output (SISO) test system was built, with velocity and thermal perturbations set as the core inputs and typhoon track and intensity as the key output targets, to perform controlled perturbation-response experiments. The experiments reveal the feasible perturbation-response range, the parameter tuning behavior of the PID module, and the energy-scale response characteristics under different perturbation modes, and quantify the input-output coupling relationships of the test system. By constructing this testbed on an operational AI weather forecasting model, this study provides a framework that goes beyond idealized sensitivity studies typically validated only on low-order dynamical models. The testbed offers an expandable platform for investigating typhoon sensitivity to artificial environmental perturbations and provides a foundation for subsequent expansion toward multi-input multi-output architectures and advanced analysis strategies such as nonlinear PID or model predictive control. △ Less

Submitted 20 May, 2026; originally announced May 2026.

Scalable native signed optical computing enabled by dual-wavelength incoherent multiplexing

Authors: Yuan Ren, Yong Zheng, Ruixue Liu, Yunpeng Song, Qinfen Huang, Min Wang, Ya Cheng

Abstract: Incoherent photonic neural networks (PNNs) provide a robust platform for analog optical computing, yet efficient implementation of native signed operations remains challenging. Existing incoherent PNNs approaches often require additional spatial channels or temporal encoding steps to represent bipolar input signals, resulting in hardware overhead that scales with system size. Here, we demonstrate… ▽ More Incoherent photonic neural networks (PNNs) provide a robust platform for analog optical computing, yet efficient implementation of native signed operations remains challenging. Existing incoherent PNNs approaches often require additional spatial channels or temporal encoding steps to represent bipolar input signals, resulting in hardware overhead that scales with system size. Here, we demonstrate a dual-wavelength incoherent photonic architecture that natively supports both signed inputs and signed weights on a thin-film lithium niobate platform. By encoding complementary signal components onto two wavelength channels and performing computation within a shared physical path, the proposed scheme eliminates duplicated weighting units. As a result, the additional hardware overhead associated with signed computation remains constant per multiply accumulate operation, independent of matrix size. The fabricated device exhibits a modulation bandwidth exceeding 40 GHz and achieves four-quadrant optical multiplication with a standard deviation error of 1.27%. System-level functionality is validated through neural-network classification, achieving 95.1% accuracy on the Moons dataset and 91.63% on MNIST. These results establish a practical route toward scalable incoherent photonic computing systems with native bipolar processing capability. △ Less

Submitted 20 May, 2026; originally announced May 2026.

Comments: 13 pages, 4 figures

Observational Constraints and Cosmological Dynamics of Interacting Fractional Holographic Dark Energy in Light of DESI DR2

Authors: Qihong Huang, Hao Chen, Qingdong Wu

Abstract: Based on the fractional entropy originating from fractional quantum mechanics, the fractional holographic dark energy (FHDE) model has been proposed. In this paper, we consider an interaction between the pressureless matter and FHDE and analyze three different interacting FHDE models. Combining the latest observational data including SNIa, OHD, BAO, and CMB, we estimate the model parameters and fi… ▽ More Based on the fractional entropy originating from fractional quantum mechanics, the fractional holographic dark energy (FHDE) model has been proposed. In this paper, we consider an interaction between the pressureless matter and FHDE and analyze three different interacting FHDE models. Combining the latest observational data including SNIa, OHD, BAO, and CMB, we estimate the model parameters and find that the interaction forms $Q=γH ρ_{de}$ and $Q=βH ρ_{m}+γH ρ_{de}$ show some preference from the observational data. Using phase space analysis, we further find that only interacting FHDE model with $Q=βH ρ_{m}+γH ρ_{de}$ can describe the full evolutionary history of the universe. The statefinder diagnostic pair reveals that this model deviates from the $Λ$CDM model but converges to the $Λ$CDM fixed point and the de Sitter expansion fixed point in the future. Finally, we analyze the evolution of cosmological parameters and demonstrate that this model can drive the late time acceleration of the universe. △ Less

Submitted 16 June, 2026; v1 submitted 5 May, 2026; originally announced May 2026.

Journal ref: Universe 12, 134 (2026)

Generation of period-tunable MeV few-attosecond electron pulse trains via counter-propagating lasers

Authors: Qi Huang, Qing Jia, Zhongxuan Wang, Jian Zheng

Abstract: Attosecond electron pulses permit real-time probing of ultrafast material dynamics. However, generating few-attosecond electron pulses with MeV energies and low energy spread remains an enduring challenge for conventional beam-modulation techniques. Here we propose a compact dual-laser scheme to modulate readily accessible electron beams into few-attosecond pulse trains, leveraging a stable parame… ▽ More Attosecond electron pulses permit real-time probing of ultrafast material dynamics. However, generating few-attosecond electron pulses with MeV energies and low energy spread remains an enduring challenge for conventional beam-modulation techniques. Here we propose a compact dual-laser scheme to modulate readily accessible electron beams into few-attosecond pulse trains, leveraging a stable parametric-resonance regime coupled with direct laser acceleration. An accompanying theoretical framework is developed, yielding closed-form expressions for the tunable pulse period, duration, energy modulation and formation time, enabling flexible customization of the produced attosecond pulse trains. Consistent with these theoretical predictions, simulations verify the generation of ~ 1 as pulses with a Lorentz factor up to 15 and a relative energy spread below 0.02%. This work offers an experimentally feasible pathway toward high-quality, tunable MeV few-attosecond electron pulses. △ Less

Submitted 1 August, 2026; v1 submitted 14 May, 2026; originally announced May 2026.

Spiral metasurface enables tunable directional edge enhancement

Authors: Wenli Wang, Yao Hu, Qiusheng Huang, Dan Chen, Qun Hao

Abstract: Tunable directional edge enhancement facilitates the acquisition of distinct morphological features from objects, a capability that plays a vital role in enhancing the reliability and safety of autonomous driving systems. However, building a simple, miniature, and switchable directional edge enhancement system remains an urgent challenge. To address this, we propose a compact spiral metasurface ca… ▽ More Tunable directional edge enhancement facilitates the acquisition of distinct morphological features from objects, a capability that plays a vital role in enhancing the reliability and safety of autonomous driving systems. However, building a simple, miniature, and switchable directional edge enhancement system remains an urgent challenge. To address this, we propose a compact spiral metasurface capable of achieving tunable vertical and horizontal edge enhancement imaging without requiring a conventional 4f system, relying instead on a single integrated device. This functionality is realized by engineering the metasurface's spiral phase profile and its polarization-dependent response, where the edge enhancement direction is controlled by varying the incident beam's polarization, enabling switching between vertical and horizontal enhancement modes. Simulations demonstrate the metasurface's capability for switchable edge detection of lane markings and barrier contours. Broadband operation is also confirmed through simulation results. Owing to its compactness, switchable functionality, and broadband performance, the proposed spiral metasurface shows significant potential for applications in optical analog computing and autonomous driving. △ Less

Submitted 6 May, 2026; originally announced May 2026.

Instability-Aware Steering of an Extreme Atmospheric River in an AI Weather Foundation Model

Authors: Moyan Liu, Qin Huang, Upmanu Lall

Abstract: Advances in deep learning methods for weather forecasting are creating opportunities to computationally explore the potential for steering or control of extreme weather trajectories for societal risk reduction. We present initial investigations into the feasibility of redirecting extreme atmospheric rivers (ARs) through small, instability-aware perturbations. Using the Aurora AI weather foundation… ▽ More Advances in deep learning methods for weather forecasting are creating opportunities to computationally explore the potential for steering or control of extreme weather trajectories for societal risk reduction. We present initial investigations into the feasibility of redirecting extreme atmospheric rivers (ARs) through small, instability-aware perturbations. Using the Aurora AI weather foundation model, we identify sensitive upstream locations using finite-time Lyapunov exponents and jet-eddy interaction criteria. We apply an idealized cloud-seeding operator that mimics latent heat release to assess whether these Lyapunov-guided interventions can influence downstream evolution. In a case study of a severe California AR, perturbations induce coherent downstream shifts in moisture transport, reducing intensity at landfall under favorable kinematic conditions. The response is nonlinear and contingent on the local flow geometry. These initial results suggest that the atmosphere's intrinsic chaotic sensitivity could be leveraged for dynamical control, offering a new research direction for extreme event risk mitigation. △ Less

Submitted 20 April, 2026; originally announced April 2026.

A data-driven approach for 2D vorticity PDF equations by a new conditional average estimation

Authors: Qian Huang, Simon Görtz, Paul Hollmann, Johannes Conrad, Christian Rohde, Martin Oberlack

Abstract: We consider the statistics for the vorticity field in two-dimensional homogeneous isotropic turbulence (HIT). First, we exploit the invariance properties to derive dimensionally reduced governing equations for the one-point and two-point probability density functions (PDFs). These take the form of linear kinetic transport equations, but with an unclosed operator in terms of a conditional average.… ▽ More We consider the statistics for the vorticity field in two-dimensional homogeneous isotropic turbulence (HIT). First, we exploit the invariance properties to derive dimensionally reduced governing equations for the one-point and two-point probability density functions (PDFs). These take the form of linear kinetic transport equations, but with an unclosed operator in terms of a conditional average. To solve the PDF equation numerically we suggest a hybrid data-driven method that relies on carefully selected samples of DNS data and a sampling estimator for the conditional average. The method is applied to DNS data for both decaying and forced HIT, demonstrating good agreement with the direct evaluation of the PDFs using the DNS data. △ Less

Submitted 16 April, 2026; originally announced April 2026.

Pushing the Limits of Pulse Shape Discrimination in a Large Liquid Xenon Detector

Authors: D. S. Akerib, A. K. Al Musalhi, F. Alder, B. J. Almquist, C. S. Amarasinghe, A. Ames, T. J. Anderson, N. Angelides, H. M. Araújo, J. E. Armstrong, M. Arthurs, A. Baker, S. Balashov, J. Bang, J. W. Bargemann, E. E. Barillier, K. Beattie, A. Bhatti, T. P. Biesiadzinski, H. J. Birch, E. Bishop, G. M. Blockinger, C. A. J. Brew, P. Brás, S. Burdin , et al. (186 additional authors not shown)

Abstract: The LUX-ZEPLIN (LZ) experiment is a direct-detection dark matter experiment, optimized to search for weakly interacting massive particles (WIMPs) through WIMP-nucleon interactions. The main challenge in dark matter detection is differentiating between WIMP signals and background events. In LZ, the ratio of ionization to scintillation signals (charge-to-light) is the primary method for rejecting el… ▽ More The LUX-ZEPLIN (LZ) experiment is a direct-detection dark matter experiment, optimized to search for weakly interacting massive particles (WIMPs) through WIMP-nucleon interactions. The main challenge in dark matter detection is differentiating between WIMP signals and background events. In LZ, the ratio of ionization to scintillation signals (charge-to-light) is the primary method for rejecting electronic recoil (ER) background. Pulse shape discrimination (PSD) offers a method for additional ER backgrounds rejection in liquid xenon detectors. In this paper, the discrimination power of PSD with the LZ experiment is discussed. To precisely characterize the scintillation pulse shape, an analysis framework is developed to reconstruct the detection time of individual photons. Using LZ calibration data, the photon-timing prompt fraction discriminator is optimized and achieves ER leakage as low as $15\%$. For specific background processes such as $^{124}$Xe double electron capture, the leakage is reduced further to about $5\%$. PSD is combined with charge-to-light to form two-factor discrimination (TFD). The optimized TFD performance is compared with the performance of the charge-to-light method, with the corresponding false positive rate reduced by up to a factor of two for large scintillation pulses. Finally, PSD and TFD are applied to data from LZ's WS2024 run and their performance is summarized. △ Less

Submitted 27 March, 2026; originally announced March 2026.

Comments: 16 pages, 14 figures

Data-driven ensemble prediction of the global ocean

Authors: Qiusheng Huang, Xiaohui Zhong, Anboyu Guo, Ziyi Peng, Lei Chen, Hao Li

Abstract: Data-driven models have advanced deterministic ocean forecasting, but extending machine learning to probabilistic global ocean prediction remains an open challenge. Here we introduce FuXi-ONS, the first machine-learning ensemble forecasting system for the global ocean, providing 5-day forecasts on a global 1° grid up to 365 days for sea-surface temperature, sea-surface height, subsurface temperatu… ▽ More Data-driven models have advanced deterministic ocean forecasting, but extending machine learning to probabilistic global ocean prediction remains an open challenge. Here we introduce FuXi-ONS, the first machine-learning ensemble forecasting system for the global ocean, providing 5-day forecasts on a global 1° grid up to 365 days for sea-surface temperature, sea-surface height, subsurface temperature, salinity and ocean currents. Rather than relying on repeated integration of computationally expensive numerical models, FuXi-ONS learns physically structured perturbations and incorporates an atmospheric encoding module to stabilize long-range forecasts. Evaluated against GLORYS12 reanalysis, FuXi-ONS improves both ensemble-mean skill and probabilistic forecast quality relative to deterministic and noise-perturbed baselines, and shows competitive performance against established seasonal forecast references for SST and Niño3.4 variability, while running orders of magnitude faster than conventional ensemble systems. These results provide a strong example of machine learning advancing a core problem in ocean science, and establish a practical path toward efficient probabilistic ocean forecasting and climate risk assessment. △ Less

Submitted 19 March, 2026; originally announced March 2026.

Spatial resolution improvement of PICOSEC Micromegas precise timing detectors

Authors: F. M. Brunbauer, R. Aleksan, Y. Angelis, S. Aune, J. Bortfeldt, M. Brunoldi, J. Datta, D. Desforge, G. Fanourakis, D. Fiorina, K. J. Floethner, M. Gallinaro, F. Garcia, I. Giomataris, K. Gnanvo, Q. Huang, F. J. Iguaz, D. Janssens, A. Kallitsopoulou, I. Karakoulias, M. Kovacic, P. Legou, M. Lisowska, J. Liu, M. Lupberger , et al. (25 additional authors not shown)

Abstract: The combination of a Cherenkov radiator with a semi-transparent photocathode and a Micromegas based amplification stage allows PICOSEC Micromegas detectors to achieve a time resolution of better than 15ps. While tileable prototypes with 10x10 channels feature 1x1 cm^2 readout pads, finer readout granularity can be used to improve the spatial resolution. We report on the study of high readout granu… ▽ More The combination of a Cherenkov radiator with a semi-transparent photocathode and a Micromegas based amplification stage allows PICOSEC Micromegas detectors to achieve a time resolution of better than 15ps. While tileable prototypes with 10x10 channels feature 1x1 cm^2 readout pads, finer readout granularity can be used to improve the spatial resolution. We report on the study of high readout granularity PICOSEC Micromegas prototypes which achieve around 0.5mm spatial resolution with 3.5mm large pads. No significant improvement was found when readout pad size was further reduced to 2.2mm. The timing resolution of the leading pad was found to be slightly degraded but remained better than 20ps for a medium granularity prototype. The achieved spatial resolution can enable PICOSEC Micromegas to be used as precise timing and moderate resolution tracking detector simultaneously. △ Less

Submitted 19 March, 2026; originally announced March 2026.

Evaluating the Predictability of Selected Weather Extremes with Aurora, an AI Weather Forecast Model

Authors: Qin Huang, Moyan Liu, Yeongbin Kwon, Upmanu Lall

Abstract: AI weather foundation models now achieve forecast skill comparable to numerical weather prediction at far lower computational cost, yet their predictability for high-impact extremes across dynamical regimes remains uncertain. We evaluate Aurora using an event-based framework spanning tropical cyclones, freezes, heatwaves, atmospheric rivers, and extreme precipitation at lead times from 1 to 21 day… ▽ More AI weather foundation models now achieve forecast skill comparable to numerical weather prediction at far lower computational cost, yet their predictability for high-impact extremes across dynamical regimes remains uncertain. We evaluate Aurora using an event-based framework spanning tropical cyclones, freezes, heatwaves, atmospheric rivers, and extreme precipitation at lead times from 1 to 21 days. Aurora demonstrates strong short-range (1-7 day) skill across event types, including competitive tropical cyclone track accuracy and high spatial agreement for temperature and moisture extremes. However, a consistent subseasonal failure mode emerges: while large-scale circulation patterns remain moderately skillful at 14-21 day leads, threshold-based extreme intensity collapses as fields regress toward climatology. This divergence indicates that Aurora retains synoptic-scale dynamical structure but loses surface-impact amplitude beyond 7-10 days. The practical predictability horizon for deterministic AI extreme-event forecasting therefore remains constrained by intrinsic atmospheric dynamics. △ Less

Submitted 6 March, 2026; originally announced March 2026.

Low-Energy Radon Backgrounds from Electrode Grids in Dual-Phase Xenon TPCs

Authors: D. S. Akerib, A. K. Al Musalhi, F. Alder, B. J. Almquist, S. Alsum, C. S. Amarasinghe, A. Ames, T. J. Anderson, N. Angelides, H. M. Araújo, J. E. Armstrong, M. Arthurs, X. Bai, A. Baker, J. Balajthy, S. Balashov, J. Bang, J. W. Bargemann, E. E. Barillier, A. Baxter, K. Beattie, T. Benson, E. P. Bernard, A. Bernstein, A. Bhatti , et al. (242 additional authors not shown)

Abstract: The dual-phase xenon time projection chamber (TPC) is a powerful technology to detect rare interactions such as scatters of dark matter particles on nuclei. In particular, the built-in gain of ionization signals in a dual-phase TPC makes it sensitive to events in the few-electron regime, as expected from low-mass dark matter interactions. The pursuit of this low-energy sensitivity through ionizati… ▽ More The dual-phase xenon time projection chamber (TPC) is a powerful technology to detect rare interactions such as scatters of dark matter particles on nuclei. In particular, the built-in gain of ionization signals in a dual-phase TPC makes it sensitive to events in the few-electron regime, as expected from low-mass dark matter interactions. The pursuit of this low-energy sensitivity through ionization-only signal detection has so far been hindered by excessive electron backgrounds observed across experiments. Much of this background is attributed to the plate-out of $^{222}$Rn decay chain isotopes on the high voltage electrode grid surfaces that span the full cross section of the TPC. This work presents a first-principle model constructed for this background, the predictions of which are consistent with data from the LZ and LUX experiments. We then discuss mitigation strategies of this background in future dual-phase TPCs and the possibility of applying this grid background model to ionization-only dark matter searches. △ Less

Submitted 24 February, 2026; originally announced February 2026.

Comments: 16 pages main text, 22 pages overall, 10 figures

HybridOM: Hybrid Physics-Based and Data-Driven Global Ocean Modeling with Efficient Spatial Downscaling

Authors: Ruiqi Shu, Xiaohui Zhong, Qiusheng Huang, Ruijian Gou, Tianrun Gao, Hao Li, Xiaomeng Huang

Abstract: Global ocean modeling is vital for climate science but struggles to balance computational efficiency with accuracy. Traditional numerical solvers are accurate but computationally expensive, while pure deep learning approaches, though fast, often lack physical consistency and long-term stability. To address this, we introduce HybridOM, a framework integrating a lightweight, differentiable numerical… ▽ More Global ocean modeling is vital for climate science but struggles to balance computational efficiency with accuracy. Traditional numerical solvers are accurate but computationally expensive, while pure deep learning approaches, though fast, often lack physical consistency and long-term stability. To address this, we introduce HybridOM, a framework integrating a lightweight, differentiable numerical solver as a skeleton to enforce physical laws, with a neural network as the flesh to correct subgrid-scale dynamics. To enable efficient high-resolution modeling, we further introduce a physics-informed regional downscaling mechanism based on flux gating. This design achieves the inference efficiency of AI-based methods while preserving the accuracy and robustness of physical models. Extensive experiments on the GLORYS12V1 and OceanBench dataset validate HybridOM's performance in two distinct regimes: long-term subseasonal-to-seasonal simulation and short-term operational forecasting coupled with the FuXi-2.0 weather model. Results demonstrate that HybridOM achieves state-of-the-art accuracy while strictly maintaining physical consistency, offering a robust solution for next-generation ocean digital twins. Our source code is available at https://github.com/ChiyodaMomo01/HybridOM. △ Less

Submitted 27 May, 2026; v1 submitted 31 January, 2026; originally announced February 2026.

Hierarchical self-organization of highly-ordered granular ensemble of optical solitons through collective motions

Authors: Xiaocong Wang, Benhai Wang, Haochen Lin, Wenbin He, Yu Jiang, Qi Huang, Xintong Zhang, Long Zhang, Meng Pang

Abstract: Self-organizations of ordered patterns in far-from-equilibrium many-body systems host fundamental importance in many disciplines. Meanwhile, complex systems often feature hierarchical structures with distinct scales for different layers, enabling high-level effective dynamics without exhaustive tracking of all possible degrees of freedoms. In this work, we report a study of the self-organization d… ▽ More Self-organizations of ordered patterns in far-from-equilibrium many-body systems host fundamental importance in many disciplines. Meanwhile, complex systems often feature hierarchical structures with distinct scales for different layers, enabling high-level effective dynamics without exhaustive tracking of all possible degrees of freedoms. In this work, we report a study of the self-organization dynamics of highly-ordered soliton ensembles in a high-harmonic mode-locked fiber lasers through collective motions driven by nonlocal optomechanical interactions and local collisions, which exhibit a series of universal characteristics reminiscent of phase transitions. Moreover, the multi-soliton laser-field can be coarsely grained as a granular ensemble of limit-cycle oscillators with simple interaction rules derived from fine-scale physics. The self-organization of the multitude of solitons in the mode-locked laser cavity can then be mapped into a low-dimensional dynamic model that essentially reproduced the emergent process. Our work affords a conceptual framework for understanding the complex structure formation in nonlinear laser systems, and may help to design ultrafast lasers by exploiting universal principles of collective motions. △ Less

Submitted 26 January, 2026; originally announced January 2026.

Lattice Boltzmann methods for simulating non-Newtonian fluids: A comprehensive review

Authors: Vedad Dzanic, Qiuxiang Huang, Christopher S. From, Emilie Sauret

Abstract: Non-Newtonian fluids encompass a large family of fluids with additional nonlinear material properties, contributing to non-trivial flow behaviour that cannot be captured through a single constant viscosity term. Common non-Newtonian characteristics include shear-thinning, shear-thickening, viscoplasticity, and viscoelasticity, commonly encountered in everyday fluids, such as ketchup, blood, toothp… ▽ More Non-Newtonian fluids encompass a large family of fluids with additional nonlinear material properties, contributing to non-trivial flow behaviour that cannot be captured through a single constant viscosity term. Common non-Newtonian characteristics include shear-thinning, shear-thickening, viscoplasticity, and viscoelasticity, commonly encountered in everyday fluids, such as ketchup, blood, toothpaste, mud, etc., as well as practical applications involving porous media, cosmetics, food processing, and pharmaceuticals. Due to the complex nature of these fluids, accurate computational fluid dynamics simulations are essential for predicting their behaviour under various flow conditions. Recent advancements have highlighted the growing trend of using the lattice Boltzmann method to solve such complex flows, owing to its ability to handle intricate boundary conditions, ease of including additional multiphysics, and providing computationally efficient parallel simulations. Since the initial review over a decade ago [Phillips & Roberts, IMA J. Appl. Math. 76, 790-816 (2011)], significant advancements have been made to the lattice Boltzmann method to simulate non-Newtonian fluids. Here, we present a comprehensive review of different lattice Boltzmann techniques used to solve non-Newtonian fluid systems, specifically dealing with shear-dependent viscosity, viscoplasticity, and viscoelasticity. In addition, we discuss various benchmark cases that validate these approaches and highlight their growing application to realistic and challenging complex flow problems. We further address outstanding issues in current lattice Boltzmann models, as well as future directions for numerical advancement and application. △ Less

Submitted 12 January, 2026; originally announced January 2026.

Initial performance results of the JUNO detector

Authors: Angel Abusleme, Thomas Adam, Kai Adamowicz, David Adey, Shakeel Ahmad, Rizwan Ahmed, Timo Ahola, Sebastiano Aiello, Fengpeng An, Guangpeng An, Costas Andreopoulos, Giuseppe Andronico, João Pedro Athayde Marcondes de André, Nikolay Anfimov, Vito Antonelli, Tatiana Antoshkina, Burin Asavapibhop, Didier Auguste, Margherita Buizza Avanzini, Andrej Babic, Jingzhi Bai, Weidong Bai, Nikita Balashov, Roberto Barbera, Andrea Barresi , et al. (1114 additional authors not shown)

Abstract: The Jiangmen Underground Neutrino Observatory (JUNO) started physics data taking on 26 August 2025. JUNO consists of a 20-kton liquid scintillator central detector, surrounded by a 35 kton water pool serving as a Cherenkov veto, and almost 1000 m$^2$ of plastic scintillator veto on top. The detector is located in a shallow underground laboratory with an overburden of 1800 m.w.e. This paper present… ▽ More The Jiangmen Underground Neutrino Observatory (JUNO) started physics data taking on 26 August 2025. JUNO consists of a 20-kton liquid scintillator central detector, surrounded by a 35 kton water pool serving as a Cherenkov veto, and almost 1000 m$^2$ of plastic scintillator veto on top. The detector is located in a shallow underground laboratory with an overburden of 1800 m.w.e. This paper presents the performance results of the detector, extensively studied during the commissioning of the water phase, the subsequent liquid scintillator filling phase, and the first physics runs. The liquid scintillator achieved an attenuation length of 20.6 m at 430 nm, while the high coverage PMT system and scintillator together yielded about 1785 photoelectrons per MeV of energy deposit at the detector centre, measured using the 2.223 MeV $γ$ from neutron captures on hydrogen with an Am-C calibration source. The reconstructed energy resolution is 3.4% for two 0.511 MeV $γ$ at the detector centre and 2.9% for the 0.93 MeV quenched Po-214 alpha decays from natural radioactive sources. The energy nonlinearity is calibrated to better than 1%. Intrinsic contaminations of U-238 and Th-232 in the liquid scintillator are below 10$^{-16}$ g/g, assuming secular equilibrium. The water Cherenkov detector achieves a muon detection efficiency better than 99.9% for muons traversing the liquid scintillator volume. During the initial science runs, the data acquisition duty cycle exceeded 97.8%, demonstrating the excellent stability and readiness of JUNO for high-precision neutrino physics. △ Less

Submitted 18 November, 2025; originally announced November 2025.

Comments: 38 pages, 23 figures

Effect of Concentration Fluctuations on Material Properties of Disordered Alloys

Authors: Han-Pu Liang, Chuan-Nan Li, Xin-Ru Tang, Xun Xu, Chen Qiu, Qiu-Shi Huang, Su-Huai Wei

Abstract: Alloying compound AX with another compound BX is widely used to tune material properties. For disordered alloys, due to the lack of periodicity, it has been challenging to calculate and study their material properties. Special quasi-random structure (SQS) method has been developed and widely used to treat this issue by matching averaged atomic correlation functions to those of ideal random alloys,… ▽ More Alloying compound AX with another compound BX is widely used to tune material properties. For disordered alloys, due to the lack of periodicity, it has been challenging to calculate and study their material properties. Special quasi-random structure (SQS) method has been developed and widely used to treat this issue by matching averaged atomic correlation functions to those of ideal random alloys, enabling accurate predictions of macroscopic material properties such as total energy and volume. However, in AxB1-x alloys, statistically allowed local concentration fluctuations can give rise to defect-like minority configurations, such as bulk-like AX or BX regions in the extreme, which could strongly affect calculation of some of the material properties such as semiconductor bandgap, if it is not defined properly, leading to significant discrepancies between theory and experiment. In this work, taking the bandgap as an example, we demonstrate that the calculated alloy bandgap can be significantly underestimated in standard SQS calculations when the SQS cell size is increased to improve the structural model and the bandgap is defined conventionally as the energy difference between the lowest unoccupied state and the highest occupied state, because the rare event motifs can lead to wavefunction localization and become the dominant factor in determining the "bandgap", contrary to experiment. To be consistent with experiment, we show that the bandgap of the alloy should be extracted from the majority configurations using a density-of-states fitting (DOSF) method. This DOSF approach resolves the long-standing issue of calculating electronic structure of disordered semiconductor alloys. Similar approaches should also be developed to treat material properties that depends on localized alloy wavefunctions. △ Less

Submitted 13 November, 2025; originally announced November 2025.

Journal ref: Sci. China-Phys. Mech. Astron. 69, 247311 (2026)

3D printed microfiber waveguide in C-shaped fiber for temperature and air pressure measurement

Authors: Qipeng Huang, Shanmei Zeng, Jingxian Cui, Lin Htein, Hwa-Yaw Tam, Xuehao Hu, Hang Qu

Abstract: In this study, we propose a microfiber waveguide for temperature and air pressure measurement. To improve mechanical strength of the sensor, a C-shaped fiber is sandwiches between two single mode fibers (SMFs) by fusion splice. The microfiber waveguide is 3D printed between two SMFs to connect two fiber cores by two-photon polymerization technology. Due to multimode property of this printed wavegu… ▽ More In this study, we propose a microfiber waveguide for temperature and air pressure measurement. To improve mechanical strength of the sensor, a C-shaped fiber is sandwiches between two single mode fibers (SMFs) by fusion splice. The microfiber waveguide is 3D printed between two SMFs to connect two fiber cores by two-photon polymerization technology. Due to multimode property of this printed waveguide, a Mach-Zehnder interferometer (MZI) is obtained. This sensor exhibits a high temperature sensitivity of 361 pm/°C at 25°C to 45°C and a high air pressure sensitivity of 55 pm/kPa from 300hpa to 1000hpa. The MZI sensor features significant advantages such as small size, high stability, and easy fabrication, without the need for complex post-processing, showing great potential and broad application prospects in many sensing applications. △ Less

Submitted 30 November, 2025; v1 submitted 12 November, 2025; originally announced November 2025.

Height-Dependent Rotor Noise and Thrust in Urban Air Mobility: An Experimental Study

Authors: Qiyu Huang, Jingwen Deng, Zishuo Lin, Mahdi Azarpeyvand

Abstract: The present study investigates the aerodynamic and aeroacoustic characteristics of a propeller operating under varying rotational speeds (RPM) and heights ("H" ), with a particular focus on the effects of upstream obstruction modelled as a tall building. Unlike previous studies that primarily examined rotor noise under axial inflow conditions, this work explores how vortex shedding and flow ingest… ▽ More The present study investigates the aerodynamic and aeroacoustic characteristics of a propeller operating under varying rotational speeds (RPM) and heights ("H" ), with a particular focus on the effects of upstream obstruction modelled as a tall building. Unlike previous studies that primarily examined rotor noise under axial inflow conditions, this work explores how vortex shedding and flow ingestion from different elevations influence rotor performance and noise emissions. Experiments were carried out in an anechoic wind tunnel, where a tall cylinder was positioned above the propeller to replicate real-world obstruction scenarios. Results revealed that lower propeller heights led to increased broadband noise due to intensified turbulence interactions and reduced aerodynamic efficiency, while higher positions improved thrust performance and mitigated noise effects under certain conditions. The findings contribute to understanding noise sources in eVTOL propulsion systems and provide insights for optimizing propeller placement to enhance aerodynamic efficiency and noise reduction in urban environments △ Less

Submitted 30 October, 2025; originally announced October 2025.

Comments: 32 pages, 7 figures

Study of few-electron backgrounds in the LUX-ZEPLIN detector

Authors: D. S. Akerib, A. K. Al Musalhi, F. Alder, B. J. Almquist, C. S. Amarasinghe, A. Ames, T. J. Anderson, N. Angelides, H. M. Araújo, J. E. Armstrong, M. Arthurs, A. Baker, S. Balashov, J. Bang, J. W. Bargemann, E. E. Barillier, K. Beattie, T. Benson, A. Bhatti, T. P. Biesiadzinski, H. J. Birch, E. Bishop, G. M. Blockinger, B. Boxer, C. A. J. Brew , et al. (182 additional authors not shown)

Abstract: The LUX-ZEPLIN (LZ) experiment aims to detect rare interactions between dark matter particles and xenon. Although the detector is designed to be the most sensitive to GeV/$c^2$--TeV/$c^2$ Weakly Interacting Massive Particles (WIMPs), it is also capable of measuring low-energy ionization signals down to a single electron that may be produced by scatters of sub-GeV/$c^2$ dark matter. The major chall… ▽ More The LUX-ZEPLIN (LZ) experiment aims to detect rare interactions between dark matter particles and xenon. Although the detector is designed to be the most sensitive to GeV/$c^2$--TeV/$c^2$ Weakly Interacting Massive Particles (WIMPs), it is also capable of measuring low-energy ionization signals down to a single electron that may be produced by scatters of sub-GeV/$c^2$ dark matter. The major challenge in exploiting this sensitivity is to understand and suppress the ionization background in the few-electron regime. We report a characterization of the delayed electron backgrounds following energy depositions in the LZ detector under different detector conditions. In addition, we quantify the probability for photons to be emitted in coincidence with electron emission from the high voltage grids. We then demonstrate that spontaneous grid electron emission can be identified and rejected with a high efficiency using a coincident photon tag, which provides a tool to improve the sensitivity of future dark matter searches. △ Less

Submitted 18 March, 2026; v1 submitted 7 October, 2025; originally announced October 2025.

Comments: 13 pages, 9 figures

50 mm $\times$ 50 mm Cesium Atomic Vapor Cell for Terahertz Imaging: Implementation and Application

Authors: Bin Zhang, Jun Wan, Tao Li, Xian-Zhe Li, Yu Wu, Qi-Rong Huang, Xin-Yu Yang, Wei Huang, Kai-Qing Zhang, Hai-Xiao Deng

Abstract: Rydberg atomic sensors offer transformative potential for high-speed, high-sensitivity terahertz (THz) imaging. However, previous systems are hindered by restricted imaging areas, largely due to the compact dimension of atomic vapor cells and inefficient beam-shaping methodologies. We present a THz imaging system with a 50 mm $\times$ 50 mm area, enabled by a custom-engineered scaled-up atomic vap… ▽ More Rydberg atomic sensors offer transformative potential for high-speed, high-sensitivity terahertz (THz) imaging. However, previous systems are hindered by restricted imaging areas, largely due to the compact dimension of atomic vapor cells and inefficient beam-shaping methodologies. We present a THz imaging system with a 50 mm $\times$ 50 mm area, enabled by a custom-engineered scaled-up atomic vapor cell and an optimized beam-shaping optical architecture. Experimental validation confirms that this system achieves near-diffraction-limited, high resolution THz imaging at 0.55 THz under ambient conditions. Furthermore, its capabilities are demonstrated through real-time visualization of the diffusion dynamics of a deionized water droplet in anhydrous ethanol. This work not only expands the boundaries of Rydberg atomic sensors but also establishes a critical foundation for advancing THz imaging technologies toward into real-world, large-scale applications. △ Less

Submitted 26 September, 2025; originally announced September 2025.

A data-driven global ocean forecasting model with sub-daily and eddy-resolving resolution

Authors: Yuan Niu, Qiusheng Huang, Xiaohui Zhong, Anboyu Guo, Lei Chen, Xiaoyan Jia, Jiawei Qi, Dianjun Zhang, Hao Li, Xuefeng Zhang

Abstract: High-fidelity ocean forecasting at high spatial and temporal resolution is essential for capturing fine-scale dynamical features, with profound implications for hazard prediction, maritime navigation, and sustainable ocean management. While conventional numerical models can generate sub-daily, eddy-resolving forecasts, they demand substantial computational resources and often struggle to maintain… ▽ More High-fidelity ocean forecasting at high spatial and temporal resolution is essential for capturing fine-scale dynamical features, with profound implications for hazard prediction, maritime navigation, and sustainable ocean management. While conventional numerical models can generate sub-daily, eddy-resolving forecasts, they demand substantial computational resources and often struggle to maintain predictive skill at such fine scales. Data-driven models offer a promising alternative with significantly higher computational efficiency; however, most are constrained to daily outputs and show a rapid decay in accuracy when extended to sub-daily timescales. Here, we introduce TianHai, the first-of-its-kind global data-driven 6-hour forecasting model, which delivers predictions at 1/12° eddy-resolving resolution with a vertical extent down to 1,500 m. A key feature of TianHai is the integration of atmospheric forcings through FuXi-Atmosphere, a data-driven atmospheric forecasting system, which enables the explicit representation of air-sea coupling effects. Unlike conventional approaches, TianHai does not rely on numerical atmospheric models or external meteorological forecasts, making it a fully data-driven framework for coupled prediction. Benchmark experiments demonstrate that TianHai delivers state-of-the-art performance in forecasting temperature and salinity profiles, zonal and meridional currents, sea surface temperature, and sea level anomalies for lead times ranging from 1 to 10 days. △ Less

Submitted 26 September, 2025; v1 submitted 21 September, 2025; originally announced September 2025.

Comments: Due to numerous errors and academic issues in the article that cannot be fixed in a short period of time, and to avoid causing confusion for other researchers, we have decided to retract the paper first. We will consider resubmitting it after making improvements in the future

Low-energy nuclear recoil calibration of the LUX-ZEPLIN experiment with a photoneutron source

Authors: J. Aalbers, D. S. Akerib, A. K. Al Musalhi, F. Alder, C. S. Amarasinghe, A. Ames, T. J. Anderson, N. Angelides, H. M. Araújo, J. E. Armstrong, M. Arthurs, A. Baker, S. Balashov, J. Bang, J. W. Bargemann, E. E. Barillier, K. Beattie, T. Benson, A. Bhatti, T. P. Biesiadzinski, H. J. Birch, E. Bishop, G. M. Blockinger, B. Boxer, C. A. J. Brew , et al. (185 additional authors not shown)

Abstract: The LZ experiment is a liquid xenon time-projection chamber (TPC) searching for evidence of particle dark matter interactions. In the simplest assumption of elastic scattering, many dark matter models predict an energy spectrum which rises quasi-exponentially with decreasing energy transfer to a target atom. LZ expects to detect coherent neutrino-nucleus scattering of $^{8}$B solar neutrinos, the… ▽ More The LZ experiment is a liquid xenon time-projection chamber (TPC) searching for evidence of particle dark matter interactions. In the simplest assumption of elastic scattering, many dark matter models predict an energy spectrum which rises quasi-exponentially with decreasing energy transfer to a target atom. LZ expects to detect coherent neutrino-nucleus scattering of $^{8}$B solar neutrinos, the signal from which is very similar to a dark matter particle with mass of about 5.5 GeV/$c^{2}$, which result in typical nuclear recoil energies of $<$5 keV$_{\text{nr}}$. Therefore, it is of crucial importance to calibrate the response of recoiling xenon nuclei to keV-energy recoils. This analysis details the first in situ photoneutron calibration of the LZ detector and probes its response in this energy regime. △ Less

Submitted 18 September, 2025; originally announced September 2025.

Flow-dependent tagging of $^{214}$Pb decays in the LZ dark matter detector

Authors: J. Aalbers, D. S. Akerib, A. K. Al Musalhi, F. Alder, C. S. Amarasinghe, A. Ames, T. J. Anderson, N. Angelides, H. M. Araújo, J. E. Armstrong, M. Arthurs, A. Baker, S. Balashov, J. Bang, J. W. Bargemann, E. E. Barillier, K. Beattie, T. Benson, A. Bhatti, T. P. Biesiadzinski, H. J. Birch, E. Bishop, G. M. Blockinger, B. Boxer, C. A. J. Brew , et al. (183 additional authors not shown)

Abstract: The LUX-ZEPLIN (LZ) experiment is searching for dark matter interactions in a liquid xenon time projection chamber (LXe-TPC). This article demonstrates how control of the flow state in the LXe-TPC enables the identification of pairs of sequential alpha-decays, which are used to map fluid flow and ion drift in the liquid target. The resulting transport model is used to tag \UChPb~ beta-decays, a le… ▽ More The LUX-ZEPLIN (LZ) experiment is searching for dark matter interactions in a liquid xenon time projection chamber (LXe-TPC). This article demonstrates how control of the flow state in the LXe-TPC enables the identification of pairs of sequential alpha-decays, which are used to map fluid flow and ion drift in the liquid target. The resulting transport model is used to tag \UChPb~ beta-decays, a leading background to dark matter signals in LZ. Temporally evolving volume selections, at a cost of 9.0\% of exposure, target the decay of each \UChPb~ atom up to 81 minutes after production, resulting in (63~$\pm$~6$_{(\mathrm{stat})}$~$\pm$~7$_{(\mathrm{sys})}$)\% identification of \UChPb~decays to ground state. We also demonstrate how flow-based tagging techniques enable a novel calibration side band that is concurrent with science data. Finally we report updated estimates of radon-chain charge branching fractions in liquid xenon, finding branching to $^{218}$Po$^+$ at $0.49 \pm 0.01$, $^{214}$Pb$^+$ at $0.48 \pm 0.12$, and $^{214}$Bi$^+$ at $0.74 \pm 0.05$, with a mean charged ion lifetime in the LZ TPC of $49 \pm 4$ min. △ Less

Submitted 19 August, 2026; v1 submitted 26 August, 2025; originally announced August 2025.

Comments: 19 pages, 14 figures

LatentFlow: Cross-Frequency Experimental Flow Reconstruction from Sparse Pressure via Latent Mapping

Authors: Junle Liu, Chang Liu, Yanyu Ke, Qiuxiang Huang, Jiachen Zhao, Wenliang Chen, K. T. Tse, Gang Hu

Abstract: Acquiring temporally high-frequency and spatially high-resolution turbulent wake flow fields in particle image velocimetry (PIV) experiments remains a significant challenge due to hardware limitations and measurement noise. In contrast, temporal high-frequency measurements of spatially sparse wall pressure are more readily accessible in wind tunnel experiments. In this study, we propose a novel cr… ▽ More Acquiring temporally high-frequency and spatially high-resolution turbulent wake flow fields in particle image velocimetry (PIV) experiments remains a significant challenge due to hardware limitations and measurement noise. In contrast, temporal high-frequency measurements of spatially sparse wall pressure are more readily accessible in wind tunnel experiments. In this study, we propose a novel cross-modal temporal upscaling framework, LatentFlow, which reconstructs high-frequency (512 Hz) turbulent wake flow fields by fusing synchronized low-frequency (15 Hz) flow field and pressure data during training, and high-frequency wall pressure signals during inference. The first stage involves training a pressure-conditioned $β$-variation autoencoder ($p$C-$β$-VAE) to learn a compact latent representation that captures the intrinsic dynamics of the wake flow. A secondary network maps synchronized low-frequency wall pressure signals into the latent space, enabling reconstruction of the wake flow field solely from sparse wall pressure. Once trained, the model utilizes high-frequency, spatially sparse wall pressure inputs to generate corresponding high-frequency flow fields via the $p$C-$β$-VAE decoder. By decoupling the spatial encoding of flow dynamics from temporal pressure measurements, LatentFlow provides a scalable and robust solution for reconstructing high-frequency turbulent wake flows in data-constrained experimental settings. △ Less

Submitted 19 August, 2025; originally announced August 2025.

Comments: The paper is submitted to IAAI26. Total 9 pages with 8 figures

Weather Jiu-Jitsu: Climate Adaptation for the 21st Century

Authors: Qin Huang, Moyan Liu, Upmanu Lall

Abstract: Extreme climate events, e.g., droughts, floods, heat waves, and freezes, are becoming more frequent and intense with severe global socio-economic impacts. Growing populations and economic activity leads to increased exposure to these events. Scaling existing physical, financial, and social infrastructure to provide resilience against these extreme events is daunting, especially as one ponders proj… ▽ More Extreme climate events, e.g., droughts, floods, heat waves, and freezes, are becoming more frequent and intense with severe global socio-economic impacts. Growing populations and economic activity leads to increased exposure to these events. Scaling existing physical, financial, and social infrastructure to provide resilience against these extreme events is daunting, especially as one ponders projected climate changes. Climate extremes pose a challenge even if decarbonization and geoengineering are able to regulate Earth's radiation balance. We argue that there is an urgent need to explore a novel adaptive strategy that we call "Weather Jiu-Jitsu," which leverages the intrinsic chaotic dynamics of weather systems to subtly redirect or dissipate their destructive trajectories through precisely timed, small-energy interventions. By leveraging insights from adaptive chaos control, combined with improved observations, prediction and low-energy weather system interventions, humanity could develop a novel nature assisted global infrastructure to limit the impact of climate extremes in the 21st century. △ Less

Submitted 12 August, 2025; originally announced August 2025.

Topological quantum electrodynamics in synthetic non-Abelian gauge fields

Authors: Qinan Huang, Bengy T. T. Wong, Zehai Pang, Xudong Zhang, Zeling Chen, Yi Yang

Abstract: Quantum electrodynamics (QED), a cornerstone framework that describes light-matter interactions rooted in Abelian symmetries, renders the harnessing of synthetic non-Abelian gauge fields as a fundamental yet uncharted frontier. Here, we develop a general theory of light-matter interaction of quantum emitters embedded in non-Abelian photonic lattices. Based on analytical solutions to the non-Abelia… ▽ More Quantum electrodynamics (QED), a cornerstone framework that describes light-matter interactions rooted in Abelian symmetries, renders the harnessing of synthetic non-Abelian gauge fields as a fundamental yet uncharted frontier. Here, we develop a general theory of light-matter interaction of quantum emitters embedded in non-Abelian photonic lattices. Based on analytical solutions to the non-Abelian Landau dressed states beyond the continuum limit, we reveal chiral photon emission and vortices with emergent nonreciprocity enabled by selective coupling between emitters and spin-momentum-locked bands. When coexisting with Abelian and non-Abelian magnetic fields, emitters hybridize with Landau dressed orbits to form spin-polarized, squeezed Landau polaritons that carry quantized angular momenta, with Rabi frequencies tunable via Landau levels and pseudospin interactions. Multi-emitter dynamics further exhibit collective phenomena governed by real-space staggered phases induced by nonsymmorphic crystalline symmetry. These results bridge non-Abelian physics with quantum optics, and establish non-Abelian gauge fields as a versatile tool for synthesizing topological quantum optical states, angular momentum transfer, and controlling photon-mediated correlations in QED systems, relevant for applications in quantum simulations and chiral quantum optical networks. △ Less

Submitted 11 August, 2025; originally announced August 2025.

Comments: 9 pages, 5 figures

Nonlinear synchronization through vector subharmonic entrainment

Authors: Dmitrii Stoliarov, Sergey Sergeyev, Hani Kbashi, Fan Wu, Qianqian Huang, Chengbo Mou

Abstract: Synchronization is ubiquitous across a wide range of fields. Subharmonic entrainment (SHE) is a nonlinear synchronization phenomenon that results in a locking oscillator at a frequency of an external periodic forcing signal with a fraction of the oscillator frequency. Beyond the fundamentals of nonlinear dynamics, SHE has a range of practical applications from stabilizing ultrafast laser pulses to… ▽ More Synchronization is ubiquitous across a wide range of fields. Subharmonic entrainment (SHE) is a nonlinear synchronization phenomenon that results in a locking oscillator at a frequency of an external periodic forcing signal with a fraction of the oscillator frequency. Beyond the fundamentals of nonlinear dynamics, SHE has a range of practical applications from stabilizing ultrafast laser pulses to optimizing control in various engineering and natural systems. However, the vectorial nature of SHE remains elusive. Here, we present the results of a theoretical and experimental study of a vector type of subharmonic entrainment (VSHE) using a passively mode-locked fiber laser as a testbed. We unveil the mechanism of vectorial SHE, in which weak external signals can entrain internal laser dynamics through vectorial coupling. Vectorial SHE presents in the form of synchronization between the subharmonic of mode-locking-driven oscillations and continuous wave (CW) signal through an evolving state of polarization. This CW signal, driven by the internal dynamics of the injected signal, causes VSHE with the frequencies ratios of multiples of ten, resulting in a partially mode-locking regime operation. Our findings offer new control techniques over mode-locking and additional dimension such as polarization states. △ Less

Submitted 31 July, 2025; originally announced July 2025.

Programmable skyrmions for robust communication and intelligent sensing

Authors: Long Chen, Xin Yu Li, Yijie Shen, Ze Gu, Jian Lin Su, Qiang Xiao, Si Qi Huang, Shi Long Qin, Qian Ma, Jian Wei You, Tie Jun Cui

Abstract: The recently observed plasmonic skyrmions, as electromagnetic counterparts of topologically stable quasiparticles, hold significant promise as novel carriers for robust information transfer and manipulation of nontrivial light-matter interactions. However, their practical applications has been hindered by the lack of flexible tuning devices to encode these topological structures. Here, we present… ▽ More The recently observed plasmonic skyrmions, as electromagnetic counterparts of topologically stable quasiparticles, hold significant promise as novel carriers for robust information transfer and manipulation of nontrivial light-matter interactions. However, their practical applications has been hindered by the lack of flexible tuning devices to encode these topological structures. Here, we present a programmable plasmonic skyrmion platform capable of encoding diverse skyrmion topologies, including Neel-type skyrmions and merons. Based on unprecedented ultra-fast coding feature, we synthesize harmonic skyrmions in the temporal dimension and, for the first time, applied skyrmions in communication and sensing applications. Specifically, we achieved highly robust and multi-channel wireless communications by using programmable topological skyrmions, providing a promising platform for communication in turbulent noise channels and extreme conditions. Furthermore, we implemented intelligent sensing across twenty animal models on the same platform, achieving high recognition accuracy. This methodology offers programmable and temporal insights into the skyrmions for their practical applications in next-generation wireless communication and intelligent sensing. △ Less

Submitted 14 September, 2025; v1 submitted 8 July, 2025; originally announced July 2025.

High-Performance Contraction of Quantum Circuits for Riemannian Optimization

Authors: Fabian Putterer, Max M. Zumpe, Isabel Nha Minh Le, Qunsheng Huang, Christian B. Mendl

Abstract: This work focuses on optimizing the gates of a quantum circuit with a given topology to approximate the unitary time evolution governed by a Hamiltonian. Recognizing that unitary matrices form a mathematical manifold, we employ Riemannian optimization methods -- specifically the Riemannian trust-region algorithm -- which involves second derivative calculations with respect to the gates. Our key te… ▽ More This work focuses on optimizing the gates of a quantum circuit with a given topology to approximate the unitary time evolution governed by a Hamiltonian. Recognizing that unitary matrices form a mathematical manifold, we employ Riemannian optimization methods -- specifically the Riemannian trust-region algorithm -- which involves second derivative calculations with respect to the gates. Our key technical contribution is a matrix-free algorithmic framework that avoids the explicit construction and storage of large unitary matrices acting on the whole Hilbert space. Instead, we evaluate all quantities as sums over state vectors, assuming that these vectors can be stored in memory. We develop HPC-optimized kernels for applying gates to state vectors and for the gradient and Hessian computation. Further improvements are achieved by exploiting sparsity structures due to Hamiltonian conservation laws, such as parity conservation, and lattice translation invariance. We benchmark our implementation on the Fermi-Hubbard model with up to 16 sites, demonstrating a nearly linear parallelization speed-up with up to 112 CPU threads. Finally, we compare our implementation with an alternative matrix product operator-based approach. △ Less

Submitted 30 June, 2025; originally announced June 2025.

Comments: 15 pages, 18 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.

FuXi-Ocean: A Global Ocean Forecasting System with Sub-Daily Resolution

Authors: Qiusheng Huang, Yuan Niu, Xiaohui Zhong, Anboyu Guo, Lei Chen, Dianjun Zhang, Xuefeng Zhang, Hao Li

Abstract: Accurate, high-resolution ocean forecasting is crucial for maritime operations and environmental monitoring. While traditional numerical models are capable of producing sub-daily, eddy-resolving forecasts, they are computationally intensive and face challenges in maintaining accuracy at fine spatial and temporal scales. In contrast, recent data-driven approaches offer improved computational effici… ▽ More Accurate, high-resolution ocean forecasting is crucial for maritime operations and environmental monitoring. While traditional numerical models are capable of producing sub-daily, eddy-resolving forecasts, they are computationally intensive and face challenges in maintaining accuracy at fine spatial and temporal scales. In contrast, recent data-driven approaches offer improved computational efficiency and emerging potential, yet typically operate at daily resolution and struggle with sub-daily predictions due to error accumulation over time. We introduce FuXi-Ocean, the first data-driven global ocean forecasting model achieving six-hourly predictions at eddy-resolving 1/12° spatial resolution, reaching depths of up to 1500 meters. The model architecture integrates a context-aware feature extraction module with a predictive network employing stacked attention blocks. The core innovation is the Mixture-of-Time (MoT) module, which adaptively integrates predictions from multiple temporal contexts by learning variable-specific reliability , mitigating cumulative errors in sequential forecasting. Through comprehensive experimental evaluation, FuXi-Ocean demonstrates superior skill in predicting key variables, including temperature, salinity, and currents, across multiple depths. △ Less

Submitted 24 October, 2025; v1 submitted 2 June, 2025; originally announced June 2025.

Residual U-Net for accurate and efficient prediction of hemodynamics in two-dimensional asymmetric stenosis

Authors: Xintong Zou, Suiyang Tong, Wenhui Peng, Qiuxiang Huang, Jianchun Wang

Abstract: This study presents residual U-Net (U-ResNet), a deep learning surrogate model for predicting steady hemodynamic fields in two-dimensional asymmetric stenotic channels at Reynolds numbers ranging from 200 to 800. By integrating residual connections with multi-scale feature extraction, U-ResNet achieves exceptional accuracy while significantly reducing computational costs compared to computational… ▽ More This study presents residual U-Net (U-ResNet), a deep learning surrogate model for predicting steady hemodynamic fields in two-dimensional asymmetric stenotic channels at Reynolds numbers ranging from 200 to 800. By integrating residual connections with multi-scale feature extraction, U-ResNet achieves exceptional accuracy while significantly reducing computational costs compared to computational fluid dynamics (CFD) approaches. Comprehensive evaluation against U-Net, Fourier Neural Operator (FNO), and U-Net enhanced Fourier Neural Operator (UFNO) demonstrates U-ResNet superior performance in capturing sharp hemodynamic gradients and complex flow features. For pressure prediction, U-ResNet achieves a normalized mean absolute error (NMAE) of 1.10%. Similarly, the performance of U-ResNet for wall shear stress (NMAE: 0.56%), velocity (NMAE: 1.06%), and vorticity (NMAE: 0.69%) consistently surpasses alternative architectures. Notably, U-ResNet demonstrates robust generalization to interpolated Reynolds numbers without retraining - a capability rarely achieved in existing models. From a computational perspective, U-ResNet delivers a 180-fold acceleration over CFD, reducing simulation time from approximately 30 minutes to 10 seconds per case. The model with non-dimensional formulation ensures scalability across vessel sizes and anatomical locations, enhancing its applicability to diverse clinical scenarios. These advances position U-ResNet as a promising auxiliary tool to complement CFD simulations for real-time clinical decision support, treatment planning, and medical device optimization. Future work will focus on extending the framework to three-dimensional geometries and integrating it with patient-specific data. △ Less

Submitted 9 August, 2025; v1 submitted 8 April, 2025; originally announced April 2025.

Journal ref: Physics of Fluids, 37(7):071925, 07 2025

The 2D Materials Roadmap

Authors: Wencai Ren, Peter Bøggild, Joan Redwing, Kostya Novoselov, Luzhao Sun, Yue Qi, Kaicheng Jia, Zhongfan Liu, Oliver Burton, Jack Alexander-Webber, Stephan Hofmann, Yang Cao, Yu Long, Quan-Hong Yang, Dan Li, Soo Ho Choi, Ki Kang Kim, Young Hee Lee, Mian Li, Qing Huang, Yury Gogotsi, Nicholas Clark, Amy Carl, Roman Gorbachev, Thomas Olsen , et al. (48 additional authors not shown)

Abstract: Over the past two decades, 2D materials have rapidly evolved into a diverse and expanding family of material platforms. Many members of this materials class have demonstrated their potential to deliver transformative impact on fundamental research and technological applications across different fields. In this roadmap, we provide an overview of the key aspects of 2D material research and developme… ▽ More Over the past two decades, 2D materials have rapidly evolved into a diverse and expanding family of material platforms. Many members of this materials class have demonstrated their potential to deliver transformative impact on fundamental research and technological applications across different fields. In this roadmap, we provide an overview of the key aspects of 2D material research and development, spanning synthesis, properties and commercial applications. We specifically present roadmaps for high impact 2D materials, including graphene and its derivatives, transition metal dichalcogenides, MXenes as well as their heterostructures and moiré systems. The discussions are organized into thematic sections covering emerging research areas (e.g., twisted electronics, moiré nano-optoelectronics, polaritronics, quantum photonics, and neuromorphic computing), breakthrough applications in key technologies (e.g., 2D transistors, energy storage, electrocatalysis, filtration and separation, thermal management, flexible electronics, sensing, electromagnetic interference shielding, and composites) and other important topics (computational discovery of novel materials, commercialization and standardization). This roadmap focuses on the current research landscape, future challenges and scientific and technological advances required to address, with the intent to provide useful references for promoting the development of 2D materials. △ Less

Submitted 28 April, 2025; v1 submitted 28 March, 2025; originally announced March 2025.

Comments: 97 pages, to be published in 2D Materials

FuXi-RTM: A Physics-Guided Prediction Framework with Radiative Transfer Modeling

Authors: Qiusheng Huang, Xiaohui Zhong, Xu Fan, Lei Chen, Hao Li

Abstract: Similar to conventional video generation, current deep learning-based weather prediction frameworks often lack explicit physical constraints, leading to unphysical outputs that limit their reliability for operational forecasting. Among various physical processes requiring proper representation, radiation plays a fundamental role as it drives Earth's weather and climate systems. However, accurate s… ▽ More Similar to conventional video generation, current deep learning-based weather prediction frameworks often lack explicit physical constraints, leading to unphysical outputs that limit their reliability for operational forecasting. Among various physical processes requiring proper representation, radiation plays a fundamental role as it drives Earth's weather and climate systems. However, accurate simulation of radiative transfer processes remains challenging for traditional numerical weather prediction (NWP) models due to their inherent complexity and high computational costs. Here, we propose FuXi-RTM, a hybrid physics-guided deep learning framework designed to enhance weather forecast accuracy while enforcing physical consistency. FuXi-RTM integrates a primary forecasting model (FuXi) with a fixed deep learning-based radiative transfer model (DLRTM) surrogate that efficiently replaces conventional radiation parameterization schemes. This represents the first deep learning-based weather forecasting framework to explicitly incorporate physical process modeling. Evaluated over a comprehensive 5-year dataset, FuXi-RTM outperforms its unconstrained counterpart in 88.51% of 3320 variable and lead time combinations, with improvements in radiative flux predictions. By incorporating additional physical processes, FuXi-RTM paves the way for next-generation weather forecasting systems that are both accurate and physically consistent. △ Less

Submitted 25 March, 2025; originally announced March 2025.

Proper Characterization of Heat-to-Electric Conversion Efficiency of Liquid Thermogalvanic Cells

Authors: Qiangqiang Huang, Yuchi Chen, Ronggui Yang, Xin Qian

Abstract: Liquid thermogalvanic cells (LTCs) have emerged as a promising technology for harvesting low-grade heat due to their low cost, compact design, and high thermopower. However, discrepancies exist in quantifying their output power and efficiency. The commonly used figure of merit, ZT = S^2σT/k, is based on electrolyte properties but fails to account for electrochemical reaction kinetics at the electr… ▽ More Liquid thermogalvanic cells (LTCs) have emerged as a promising technology for harvesting low-grade heat due to their low cost, compact design, and high thermopower. However, discrepancies exist in quantifying their output power and efficiency. The commonly used figure of merit, ZT = S^2σT/k, is based on electrolyte properties but fails to account for electrochemical reaction kinetics at the electrode interface that significantly impact performance and losses. This work establishes an experimental protocol for accurately characterizing LTC efficiency. We propose a device-level figure of merit, ZT = S^2T/RK , where R and K represent total internal resistance and thermal conductance. This formulation, derived by linearizing the Butler-Volmer relation, incorporates irreversible losses such as mass transfer and activation overpotential. Different methods for assessing LTC output power are examined, including linear sweeping voltammetry (LSV), constant resistance discharging, and constant current step discharging. LSV tends to overestimate power due to transient effects, while the latter two methods provide more accurate steady-state measurements. Additionally, heat conduction across LTCs is carefully analyzed, highlighting the significant impact of natural convection within electrolytes. Through rigorous experimental characterization, we demonstrate that the modified figure of merit is a proper efficiency indicator at the steady-state. △ Less

Submitted 30 March, 2025; v1 submitted 9 March, 2025; originally announced March 2025.

Evaluation of tetracycline photocatalytic degradation using NiFe2O4/CeO2/GO nanocomposite for environmental remediation: In silico molecular docking, Antibacterial performance, degradation pathways, and DFT calculations

Authors: Misbah latif, Raziq Nawaz, Muhammad Hammad Aziz, Muhammad Asif, Fatima Noor, Amil Aligayev, Syed Mansoor Ali, Manawwer Alam, Stefanos Papanikolaou, Qing Huang

Abstract: Graphene-based nanostructures with distinct structural and physicochemical characteristics may be able to photodegrade antibiotics effectively. Herein, this study reports the successful synthesis of NiFe2O4/CeO2/GO nanocomposite (NC) by anchoring NiFe2O4/CeO2 to the surface of GO (Graphene oxide). All state-of-the-art characterization techniques investigated the nanostructure, crystallinity, phono… ▽ More Graphene-based nanostructures with distinct structural and physicochemical characteristics may be able to photodegrade antibiotics effectively. Herein, this study reports the successful synthesis of NiFe2O4/CeO2/GO nanocomposite (NC) by anchoring NiFe2O4/CeO2 to the surface of GO (Graphene oxide). All state-of-the-art characterization techniques investigated the nanostructure, crystallinity, phonon modes, chemical composition analysis, elemental composition, surface area, magnetic properties, and optical band gap. Hydrothermal approach assisted NiFe2O4/CeO2/GO catalyst showed better charge carrier separation and prompted the tetracycline (TC-HCl) photocatalytic degradation under visible light. Following 90 minutes of exposure to visible light, NiFe2O4/CeO2/GO nanocomposite demonstrated superior photocatalytic activity, with a TC-HCl degradation rate of 95%. Reasonable mechanisms of tetracycline degradation were proposed where the OH and O played a leading role based on identified intermediates. Moreover, tetracycline photodegradation intermediates and the optimal pathway were identified using LC-MS spectrometry. This study also performed Density Functional Theory (DFT) calculations for the prepared materials to validate the experimental data. In vitro, antibacterial studies were consistent with the molecular docking investigations of the NiFe2O4/CeO2/GO nanocomposite against DNA gyrase and FabI from Escherichia coli (E. coli) and Staphylococcus aureus (S.aureus). Lastly, the outcomes revealed a new potential for NiFe2O4/CeO2/GO nanocomposite for improved photocatalytic performance, making it a promising photocatalyst for wastewater treatment. △ Less

Submitted 21 February, 2025; originally announced March 2025.

Using Label-Free Raman Spectroscopy Integrated with Microfluidic Chips to Probe Ferroptosis Networks in Cells

Authors: Muhammad Muhammad, Chang-Sheng Shao, Raziq Nawaz, Amil Aligayev, Muhammad Hassan, Mona Alrasheed Bashir, Jamshed Iqbal, Jie Zhan, Qing Huang

Abstract: Ferroptosis, a regulated form of cell death driven by oxidative stress and lipid peroxidation, has emerged as a pivotal research focus with implications across various cellular contexts. In this study, we employed a multifaceted approach, integrating label-free Raman spectroscopy and microfluidics to study the mechanisms underpinning ferroptosis. Our investigations included the ferroptosis initiat… ▽ More Ferroptosis, a regulated form of cell death driven by oxidative stress and lipid peroxidation, has emerged as a pivotal research focus with implications across various cellular contexts. In this study, we employed a multifaceted approach, integrating label-free Raman spectroscopy and microfluidics to study the mechanisms underpinning ferroptosis. Our investigations included the ferroptosis initiation based on the changes in the lipid Raman band at 1436 cm-1 under different cellular states, the generation of reactive oxygen species (ROS), lipid peroxidation, DNA damage/repair, and mitochondrial dysfunction. Importantly, our work highlighted the dynamic role of vital cellular components, such as NADPH, ferredoxin clusters, and key genes like GPX-4, VDAC2, and NRF2, as they collectively influenced cellular responses to redox imbalance and oxidative stress. Quantum mechanical (QM) and molecular docking simulations (MD) provided further evidence of interactions between the ferredoxin (containing 4Fe-4S clusters), NADPH and ROS which led to the production of reactive Fe species in the cells. As such, our approach offered a real-time, multidimensional perspective on ferroptosis, surpassing traditional biological methods, and providing valuable insights for therapeutic interventions in diverse biomedical contexts. △ Less

Submitted 21 February, 2025; originally announced March 2025.

Wafer-scale Integration of Single-Crystalline MoS$_2$ for Flexible Electronics Enabled by Oxide Dry-transfer

Authors: Xiang Xu, Yitong Chen, Jichuang Shen, Qi Huang, Tong Jiang, Han Chen, Huaze Zhu, Yaqing Ma, Hao Wang, Wenhao Li, Chen Ji, Dingwei Li, Siyu Zhang, Yan Wang, Bowen Zhu, Wei Kong

Abstract: Atomically thin, single-crystalline transition metal dichalcogenides (TMDCs) grown via chemical vapor deposition (CVD) on sapphire substrates exhibit exceptional mechanical and electrical properties, positioning them as excellent channel materials for flexible electronics. However, conventional wet-transfer processes for integrating these materials onto flexible substrates often introduce surface… ▽ More Atomically thin, single-crystalline transition metal dichalcogenides (TMDCs) grown via chemical vapor deposition (CVD) on sapphire substrates exhibit exceptional mechanical and electrical properties, positioning them as excellent channel materials for flexible electronics. However, conventional wet-transfer processes for integrating these materials onto flexible substrates often introduce surface contamination, significantly degrading device performance. Here, we present a wafer-scale dry-transfer technique using a high-dielectric oxide as the transfer medium, enabling the integration of 4-inch single-crystalline MoS$_2$ onto flexible substrates. This method eliminates contact with polymers or solvents, thus preserving the intrinsic electronic properties of MoS$_2$. As a result, the fabricated flexible field-effect transistor (FET) arrays exhibit remarkable performance, with a mobility of 117 cm$^2$/Vs, a subthreshold swing of 68.8 mV dec$^{-1}$, and an ultra-high current on/off ratio of $10^{12}$-values comparable to those achieved on rigid substrates. Leveraging the outstanding electrical characteristics, we demonstrated MoS$_2$-based flexible inverters operating in the subthreshold regime, achieving both a high gain of 218 and ultra-low power consumption of 1.4 pW/$μ$m. Additionally, we integrated a flexible tactile sensing system driven by active-matrix MoS$_2$ FET arrays onto a robotic gripper, enabling real-time object identification. These findings demonstrate the simultaneous achievement of high electrical performance and flexibility, highlighting the immense potential of single-crystalline TMDC-based flexible electronics for real-world applications. △ Less

Submitted 23 January, 2025; originally announced January 2025.

Identifying rich clubs in spatiotemporal interaction networks

Authors: Jacob Kruse, Song Gao, Yuhan Ji, Keith Levin, Qunying Huang, Kenneth R. Mayer

Abstract: Spatial networks are widely used in various fields to represent and analyze interactions or relationships between locations or spatially distributed entities.There is a network science concept known as the 'rich club' phenomenon, which describes the tendency of 'rich' nodes to form densely interconnected sub-networks. Although there are established methods to quantify topological, weighted, and te… ▽ More Spatial networks are widely used in various fields to represent and analyze interactions or relationships between locations or spatially distributed entities.There is a network science concept known as the 'rich club' phenomenon, which describes the tendency of 'rich' nodes to form densely interconnected sub-networks. Although there are established methods to quantify topological, weighted, and temporal rich clubs individually, there is limited research on measuring the rich club effect in spatially-weighted temporal networks, which could be particularly useful for studying dynamic spatial interaction networks. To address this gap, we introduce the spatially-weighted temporal rich club (WTRC), a metric that quantifies the strength and consistency of connections between rich nodes in a spatiotemporal network. Additionally, we present a unified rich club framework that distinguishes the WTRC effect from other rich club effects, providing a way to measure topological, weighted, and temporal rich club effects together. Through two case studies of human mobility networks at different spatial scales, we demonstrate how the WTRC is able to identify significant weighted temporal rich club effects, whereas the unweighted equivalent in the same network either fails to detect a rich club effect or inaccurately estimates its significance. In each case study, we explore the spatial layout and temporal variations revealed by the WTRC analysis, showcasing its particular value in studying spatiotemporal interaction networks. This research offers new insights into the study of spatiotemporal networks, with critical implications for applications such as transportation, redistricting, and epidemiology. △ Less

Submitted 9 January, 2025; originally announced January 2025.

Comments: 25 pages, 14 figures

ACM Class: I.2

Journal ref: Annals of the American Association of Geographers, 2025

Ultrafast high-fidelity state readout of single neutral atom

Authors: Jian Wang, Dong-Yu Huang, Xiao-Long Zhou, Ze-Min Shen, Si-Jian He, Qi-Yang Huang, Yi-Jia Liu, Chuan-Feng Li, Guang-Can Guo

Abstract: The capability to measure the state of a quantum system is vital to a practical quantum network, for applications including distributed quantum computing and long-distance quantum communication. As a thriving platform for quantum information technology, single neutral atoms suffer from low achievable photon scattering rate and shallow trapping potential, which limits the fidelity and speed of stat… ▽ More The capability to measure the state of a quantum system is vital to a practical quantum network, for applications including distributed quantum computing and long-distance quantum communication. As a thriving platform for quantum information technology, single neutral atoms suffer from low achievable photon scattering rate and shallow trapping potential, which limits the fidelity and speed of state readout process. Here, by coupling an single neutral atom with a high-finesse fiber-based Fabry-Pérot microcavity (FFPC) in Purcell regime, we realize strong enhancement of the atomic photoemission rate, which enables ultrafast and high-fidelity discrimination of bright and dark hyperfine states of the atom. The readout fidelity can reach 99.1(2)% within 200 ns and 99.985(8)% within 9 $μ$s. Furthermore, we demonstrate that state preparation via optical pumping can be efficiently accelerated by real-time decision protocol based on ultrafast state readout. This work paves the way to the implementation of quantum networking protocols with high communication rate and high fidelity. △ Less

Submitted 17 December, 2024; originally announced December 2024.

Comments: 9 pages, 9 figures, 53 references

Purcell-Enhanced Generation of Photonic Bell States via the Inelastic Scattering of Single Atoms

Authors: Jian Wang, Xiao-Long Zhou, Ze-Min Shen, Dong-Yu Huang, Si-Jian He, Qi-Yang Huang, Yi-Jia Liu, Chuan-Feng Li, Guang-Can Guo

Abstract: Single atoms trapped in optical cavities exhibit immense potential as key nodes in future quantum information processing. They have already demonstrated significant advancement in various quantum technologies, particularly regarding the generation of nonclassical light. Here, we efficiently produce genuine photonic Bell states through the inelastic scattering process of single two-level intracavit… ▽ More Single atoms trapped in optical cavities exhibit immense potential as key nodes in future quantum information processing. They have already demonstrated significant advancement in various quantum technologies, particularly regarding the generation of nonclassical light. Here, we efficiently produce genuine photonic Bell states through the inelastic scattering process of single two-level intracavity atoms. An experimental violation of the Bell inequality, arising from the interference between the probability amplitudes of two photons, validates the intrinsic nature of energy-time entanglement. Coupling atoms with an optical cavity in the Purcell regime substantially enhances the two-photon scattering. This Bell state generation process does not require atomic spin control, thereby rendering it inherently immune to decoherence effects. This work advances the comprehension of resonance fluorescence and has the potential to broaden the landscape of quantum technologies and facilitate the application of photonic Bell states. △ Less

Submitted 16 December, 2024; originally announced December 2024.

Comments: 9 pages, 8 figures, 47 reference

Direct measurement of Tan's contact in a one-dimensional Lieb-Liniger gas

Authors: Qi Huang, Hepeng Yao, Xuzong Chen, Laurent Sanchez-Palencia

Abstract: The Tan contact has emerged as a pivotal quantity in characterizing many-body quantum systems, bridging microscopic short-range correlations to thermodynamic behavior. It is defined as the weight of universal $1/k^4$ fall off in momentum distribution tails, which can be measured directly in ultracold gases. So far, however, its direct measurement has been hindered in Bose gases due to interactions… ▽ More The Tan contact has emerged as a pivotal quantity in characterizing many-body quantum systems, bridging microscopic short-range correlations to thermodynamic behavior. It is defined as the weight of universal $1/k^4$ fall off in momentum distribution tails, which can be measured directly in ultracold gases. So far, however, its direct measurement has been hindered in Bose gases due to interactions strongly affecting the expansion dynamics. Here, we present the first direct measurement of the Tan contact in a strongly-correlated Lieb-Liniger gas. Leveraging the one-dimensional geometry of our system, we implement a two-stage expansion scheme, yielding interaction-immune time-of-flight imaging. Our results show excellent agreement with theoretical predictions from quantum Monte Carlo calculations, which also provides independent thermometry of the experiment. By varying atom number, temperature, and interaction strength, we obtain results consistent with the universal scaling law predicted for the trapped Lieb-Liniger model. Our work paves the way for further characterization of the Lieb-Liniger gas across broad interaction regimes and holds promise for extension to other correlated quantum gases in confined geometries. △ Less

Submitted 11 December, 2024; originally announced December 2024.

Sublayers Editing of Covalent MAX Phase for Nanolaminated Early Transition Metal Compounds

Authors: Ziqian Li, Ke Chen, Xudong Wang, Kan Luo, Lei Lei, Mian Li, Kun Liang, Degao Wang, Shiyu Du, Zhifang Chai, Qing Huang

Abstract: Two-dimensional transition metal carbides and nitrides (MXenes) have gained popularity in fields such as energy storage, catalysis, and electromagnetic interference due to their diverse elemental compositions and variable surface terminations (T). Generally, the synthesis of MXene materials involves etching the weak M-A metallic bonds in the ternary layered transition metal carbides and nitrides (… ▽ More Two-dimensional transition metal carbides and nitrides (MXenes) have gained popularity in fields such as energy storage, catalysis, and electromagnetic interference due to their diverse elemental compositions and variable surface terminations (T). Generally, the synthesis of MXene materials involves etching the weak M-A metallic bonds in the ternary layered transition metal carbides and nitrides (MAX phase) using HF acid or Lewis acid molten salts, while the strong M-X covalent bonds preserve the two-dimensional framework structure of MXenes. On the other hand, the MAX phase material family also includes a significant class of members where the A site is occupied by non-metal main group elements (such as sulfur and phosphorus), in which both M-A and M-X are covalent bond-type sublayers. The aforementioned etching methods cannot be used to synthesize MXene materials from these parent phases. In this work, we discovered that the covalent bond-type M-A and M-X sublayers exhibit different reactivity with some inorganic materials in a high-temperature molten state. By utilizing this difference in reactivity, we can structurally modify these covalent sublayers, allowing for the substitution of elements at the X site (from B to Se, S, P, C) and converting non-metal A site atoms in non-van der Waals (non-vdW) MAX phases into surface atoms in vdW layered materials. This results in a family of early transition metal Xide chalcogenides (TMXCs) that exhibit lattice characteristics of both MXenes and transition metal chalcogenides. Using electron-donor chemical scissors, these TMXC layered materials can be further exfoliated into monolayer nanosheets. The atomic configurations of each atom in these monolayer TMXCs are the same as those of conventional MXenes, but the oxidation states of the M-site atoms can be regulated by both X-site atoms and intercalated cations. △ Less

Submitted 2 December, 2024; originally announced December 2024.

A weighted scalar auxiliary variable method for solving gradient flows: bridging the nonlinear energy-based and Lagrange multiplier approaches

Authors: Qiong-Ao Huang, Wei Jiang, Jerry Zhijian Yang, Cheng Yuan

Abstract: Two primary scalar auxiliary variable (SAV) approaches are widely applied for simulating gradient flow systems, i.e., the nonlinear energy-based approach and the Lagrange multiplier approach. The former guarantees unconditional energy stability through a modified energy formulation, whereas the latter preserves original energy stability but requires small time steps for numerical solutions. In thi… ▽ More Two primary scalar auxiliary variable (SAV) approaches are widely applied for simulating gradient flow systems, i.e., the nonlinear energy-based approach and the Lagrange multiplier approach. The former guarantees unconditional energy stability through a modified energy formulation, whereas the latter preserves original energy stability but requires small time steps for numerical solutions. In this paper, we introduce a novel weighted SAV method which integrates these two approaches for the first time. Our method leverages the advantages of both approaches: (i) it ensures the existence of numerical solutions for any time step size with a sufficiently large weight coefficient; (ii) by using a weight coefficient smaller than one, it achieves a discrete energy closer to the original, potentially ensuring stability under mild conditions; and (iii) it maintains consistency in computational cost by utilizing the same time/spatial discretization formulas. We present several theorems and numerical experiments to validate the accuracy, energy stability and superiority of our proposed method. △ Less

Submitted 26 November, 2024; originally announced November 2024.

MSC Class: 65M22; 65M70; 35K35; 35K55

P2DFlow: A Protein Ensemble Generative Model with SE(3) Flow Matching

Authors: Yaowei Jin, Qi Huang, Ziyang Song, Mingyue Zheng, Dan Teng, Qian Shi

Abstract: Biological processes, functions, and properties are intricately linked to the ensemble of protein conformations, rather than being solely determined by a single stable conformation. In this study, we have developed P2DFlow, a generative model based on SE(3) flow matching, to predict the structural ensembles of proteins. We specifically designed a valuable prior for the flow process and enhanced th… ▽ More Biological processes, functions, and properties are intricately linked to the ensemble of protein conformations, rather than being solely determined by a single stable conformation. In this study, we have developed P2DFlow, a generative model based on SE(3) flow matching, to predict the structural ensembles of proteins. We specifically designed a valuable prior for the flow process and enhanced the model's ability to distinguish each intermediate state by incorporating an additional dimension to describe the ensemble data, which can reflect the physical laws governing the distribution of ensembles, so that the prior knowledge can effectively guide the generation process. When trained and evaluated on the MD datasets of ATLAS, P2DFlow outperforms other baseline models on extensive experiments, successfully capturing the observable dynamic fluctuations as evidenced in crystal structure and MD simulations. As a potential proxy agent for protein molecular simulation, the high-quality ensembles generated by P2DFlow could significantly aid in understanding protein functions across various scenarios. Code is available at https://github.com/BLEACH366/P2DFlow △ Less

Submitted 3 March, 2025; v1 submitted 26 November, 2024; originally announced November 2024.

Combining Hyperbolic Quadrature Method of Moments and Discrete-Velocity-Direction Models for Solving BGK-type Equations

Authors: Tianshu Li, Yihong Chen, Qian Huang

Abstract: This paper introduces the discrete-velocity-direction model (DVDM) in conjunction with the hyperbolic quadrature method of moments (HyQMOM) to develop a multidimensional spatial-temporal approximation of the BGK equation, termed DVD-HyQMOM. Serving as a multidimensional extension of HyQMOM, DVD-HyQMOM model achieves higher accuracy than other DVDM submodels, especially with an increased number of… ▽ More This paper introduces the discrete-velocity-direction model (DVDM) in conjunction with the hyperbolic quadrature method of moments (HyQMOM) to develop a multidimensional spatial-temporal approximation of the BGK equation, termed DVD-HyQMOM. Serving as a multidimensional extension of HyQMOM, DVD-HyQMOM model achieves higher accuracy than other DVDM submodels, especially with an increased number of abscissas. The efficiency and effectiveness of this model are demonstrated through various numerical tests. △ Less

Submitted 19 November, 2024; originally announced November 2024.

Bell state generation and CNOT operation using on-demand identical photons from shape-controlled spatially ordered quantum dots

Authors: Qi Huang, Swarnabha Chattaraj, Lucas Jordao, Jiefei Zhang, Siyuan Lu, Anupam Madhukar

Abstract: Fault tolerant on-chip photonic quantum computation is enormously helped by (a) deterministic generation of the needed thousands to millions of photon qubits from (b) quantum emitters in designed spatially ordered arrays to enable networks for implementing many-qubit logic circuits. Scaling up photonic quantum information processing systems has, however, been prevented by the lack of such quantum… ▽ More Fault tolerant on-chip photonic quantum computation is enormously helped by (a) deterministic generation of the needed thousands to millions of photon qubits from (b) quantum emitters in designed spatially ordered arrays to enable networks for implementing many-qubit logic circuits. Scaling up photonic quantum information processing systems has, however, been prevented by the lack of such quantum emitters until the demonstration of the platform of mesa-top single quantum dots (MTSQDs) -- controlled shape, size, and volume single QD -- located in designed regular arrays. Here we demonstrate 2 qubit CNOT gate operation -- a universal gate necessary to enable quantum circuits of arbitrary complexity -- in polarization basis using photons emitted from individual MTSQDs. A Bell state fidelity of 0.825$\pm$0.010 is achieved with two photon interference (TPI) visibility of 0.947$\pm$0.0015 at 4K without Purcell enhancement. The results make a strong case for developing MTSQD arrays for utility scale optical quantum information processing platforms. △ Less

Submitted 8 November, 2024; v1 submitted 6 November, 2024; originally announced November 2024.

Comments: 17 pages, 8 figures