Showing 1–50 of 100 results for author: Xiao, T

Cold-atom comagnetometry via optical control of spin states

Authors: J. -L. Zhang, W. -T. Luo, Y. A. Yang, Y. -Q. Wang, T. Xia, Z. -T. Lu

Abstract: Atomic spin-based comagnetometers are powerful tools for precision sensing and tests of fundamental physics. Compared with the widely used gas-cell comagnetometer systems, cold-atom systems offer access to much shorter distance scales and allow implementation of {optical} quantum control techniques. However, in order to realize long spin coherence times with cold atoms, it is necessary to employ d… ▽ More Atomic spin-based comagnetometers are powerful tools for precision sensing and tests of fundamental physics. Compared with the widely used gas-cell comagnetometer systems, cold-atom systems offer access to much shorter distance scales and allow implementation of {optical} quantum control techniques. However, in order to realize long spin coherence times with cold atoms, it is necessary to employ diamagnetic atoms and overcome decoherence induced by light shifts. Here we demonstrate a cold-atom comagnetometer based on the nuclear spins of $^{171}$Yb (spin-1/2) and $^{173}$Yb (spin-5/2), jointly trapped in an optical lattice. Vector light shifts are suppressed by enforcing linear polarization of the lattice, while tensor shifts in $^{173}$Yb are suppressed via the use of a Schrödinger cat state. This enables simultaneous Ramsey interferometry on both isotopes with a spin coherence time of 60 s. We achieve a magnetic noise suppression factor exceeding $3\times10^4$, and determine the ratio of nuclear magnetic moments to 4 ppm precision. Our results establish a new cold-atom platform for spin-based sensing and open pathways toward quantum-enhanced searches for physics beyond the Standard Model. △ Less

Submitted 14 August, 2026; originally announced August 2026.

Time-Reversal-Invariant Altermagnetic Acoustic Crystals

Authors: Tianzhi Xia, Han-Rong Xia, Jinglin Liu, Xiying Fan, Zebin Zhu, Zhen Gao

Abstract: Altermagnets have emerged as a new class of magnetic materials that combine spin-split electronic bands with zero net magnetization. Extending this paradigm to classical-wave systems has, however, been fundamentally challenging because conventional realizations require broken time-reversal symmetry (TRS). Here, we overcome this limitation by introducing two pseudospin degrees of freedom and constr… ▽ More Altermagnets have emerged as a new class of magnetic materials that combine spin-split electronic bands with zero net magnetization. Extending this paradigm to classical-wave systems has, however, been fundamentally challenging because conventional realizations require broken time-reversal symmetry (TRS). Here, we overcome this limitation by introducing two pseudospin degrees of freedom and constructing a pseudo-time-reversal operator that faithfully reproduces the action of its physical counterpart while preserving actual TRS. Building on this framework, we theoretically propose and experimentally realize the first time-reversal-invariant altermagnetic acoustic crystal. Acoustic measurements directly reveal pseudospin-dependent band splitting--a defining hallmark of altermagnetism--under strictly TRS-preserving conditions. Moreover, the altermagnetic acoustic crystal exhibits sublattice-pseudospin locking, enabling flexible control over acoustic pseudospin splitting and filtering. Our work establishes acoustic crystals as a versatile platform for exploring altermagnetic physics and opens new avenues for spin-inspired wave manipulation in nonmagnetic devices. △ Less

Submitted 9 August, 2026; originally announced August 2026.

Comments: 12pages, 4 figures

Observation of Antichiral Hinge States in a Three-dimensional Gyromagnetic Photonic Crystal

Authors: Ziyao Wang, Tianzhi Xia, Han-Rong Xia, Zhen Gao

Abstract: Recent advances in topological physics have revealed a counterintuitive class of antichiral edge and surface states that propagate in the same direction along spatially separated parallel boundaries. To date, however, experimental realizations of antichiral states have been restricted to first-order topological phases, while their higher-order counterparts--antichiral hinge states--have remained e… ▽ More Recent advances in topological physics have revealed a counterintuitive class of antichiral edge and surface states that propagate in the same direction along spatially separated parallel boundaries. To date, however, experimental realizations of antichiral states have been restricted to first-order topological phases, while their higher-order counterparts--antichiral hinge states--have remained experimentally elusive. Here, we report the first experimental observation of antichiral hinge states in a gyromagnetic photonic crystal that realizes a three-dimensional (3D) modified Haldane model with dimerized interlayer coupling. Through microwave near-field mapping, we directly resolve their defining signatures: nonreciprocal, co-propagating transport along four parallel hinges and characteristically tilted hinge-state dispersions. These results extend antichiral topology into the higher-order regime and provide a new platform for 3D nonreciprocal topological photonic devices. △ Less

Submitted 31 July, 2026; originally announced July 2026.

Final assessment of radioactive impurities in the JUNO detector

Authors: Thomas Adam, Fengpeng An, Costas Andreopoulos, Giuseppe Andronico, Nikolay Anfimov, Vito Antonelli, Tatiana Antoshkina, João Pedro Athayde Marcondes de André, Didier Auguste, Nikita Balashov, Andrea Barresi, Davide Basilico, Eric Baussan, Marco Beretta, Antonio Bergnoli, Nikita Bessonov, Daniel Bick, Lukas Bieger, Svetlana Biktemerova, Thilo Birkenfeld, Simon Blyth, Manuel Böhles, Anastasia Bolshakova, Mathieu Bongrand, Matteo Borghesi , et al. (549 additional authors not shown)

Abstract: The Jiangmen Underground Neutrino Observatory (JUNO) collaboration has completed the construction of the 20,000-ton liquid scintillator detector and the associated muon veto detector system. To meet the physics objectives, the materials used in the detector must exhibit low radioactive contamination. The single-event rate in the fiducial volume (R $<$ 17.2 m) of the scintillator is required to be… ▽ More The Jiangmen Underground Neutrino Observatory (JUNO) collaboration has completed the construction of the 20,000-ton liquid scintillator detector and the associated muon veto detector system. To meet the physics objectives, the materials used in the detector must exhibit low radioactive contamination. The single-event rate in the fiducial volume (R $<$ 17.2 m) of the scintillator is required to be approximately 7 Hz for energies above 0.7 MeV, resulting in an accidental coincidence background of about 1 event per day for reactor neutrino physics analyses. Since the beginning of the construction phase, we have screened the natural radioactivity content of thousands of materials, to select those that meet the design background budget. The radioactive impurity concentrations of the materials ultimately used in the JUNO detector are summarized in this paper. The construction of the entire detector and the subsequent filling of the liquid scintillator were completed in August 2025. From the initial data, the total count rate of natural radioactivity within the detector's fiducial volume has met the requirements and is sufficient to support the reactor antineutrino analysis. △ Less

Submitted 19 July, 2026; originally announced July 2026.

Physics informed wavelet Fourier representation for multiscale fluid dynamics

Authors: Chao Wang, Shilong Li, Yunpeng Wang, Tianbai Xiao, Zelong Yuan, Chenyue Xie, Chunyu Guo

Abstract: Multiscale fluid flows often contain localized flow structures, such as viscous shock layers, wet-dry fronts, steady viscous wakes, decaying vortical structures, and vortex-shedding patterns, whose accurate prediction requires the simultaneous preservation of global conservation trends and small-scale gradients. This study examines these flow-physics requirements through a physics-informed wavelet… ▽ More Multiscale fluid flows often contain localized flow structures, such as viscous shock layers, wet-dry fronts, steady viscous wakes, decaying vortical structures, and vortex-shedding patterns, whose accurate prediction requires the simultaneous preservation of global conservation trends and small-scale gradients. This study examines these flow-physics requirements through a physics-informed wavelet-Fourier (PIWF) representation for multiscale fluid dynamics. Instead of relying on a single monolithic neural approximator, the formulation separates two complementary components of the flow field within a physics-informed neural representation: long-range coherent modes through a Fourier-basis branch and localized steep-gradient or vortical features through a compactly supported wavelet branch. The outputs are fused with a residual multilayer perceptron using channel attention, and the governing equations, initial conditions, and boundary conditions are imposed directly through the physics-informed loss. The model is assessed on five canonical fluid-dynamics problems: Burgers' equation, the shallow water equations, Kovasznay flow, Taylor--Green vortex flow, and two-dimensional cylinder wake flow. The results show that PIWF improves the resolution of shock-like gradients, wet--dry interfaces, steady wake fields, decaying vortical structures, vorticity extrema, and broadband wake spectra relative to standard physics-informed neural networks and physics-informed Kolmogorov--Arnold networks. These findings indicate that a wavelet-Fourier physics-informed representation can provide a useful route for analyzing multiscale flow phenomena when high-fidelity interior reference data are limited or unavailable. △ Less

Submitted 9 July, 2026; originally announced July 2026.

Perceiving exposure segregation with open urban imagery

Authors: Yunke Zhang, Ruolong Ma, Xin Zhang, Yu Shang, Fengli Xu, Tong Xia, Yong Li

Abstract: Socioeconomic exposure segregation -- the lack of daily interaction between income groups -- erodes social capital and entrenches inequality, yet the specific physical features that drive these behavioral restrictions remain poorly understood. Prior research has quantified where segregation occurs using mobility data, but has not identified how the built environment facilitates or inhibits these i… ▽ More Socioeconomic exposure segregation -- the lack of daily interaction between income groups -- erodes social capital and entrenches inequality, yet the specific physical features that drive these behavioral restrictions remain poorly understood. Prior research has quantified where segregation occurs using mobility data, but has not identified how the built environment facilitates or inhibits these interactions. Here we introduce VISAGE, a large multi-modal model-enabled framework that perceives exposure segregation directly from open satellite and street-level imagery across 10,030 communities in 31 U.S. cities. Moving beyond black-box correlations, we operationalize cross-disciplinary sociological theory into an interpretable visual codebook to detect physical regulators of social mixing. We find that the built environment encodes a legible grammar of segregation: "defensible" architectural forms (e.g., fences, gated enclosures) and monofunctional zoning systematically predict higher social isolation, whereas mixed-use infrastructure fosters interaction, explaining substantial variance in mobility-derived segregation patterns (Pearson $r=0.770$). Crucially, we show that inclusionary housing policies manifest in distinct visual signatures associated with higher mixing, suggesting that policy interventions successfully alter the physical landscape to encourage diversity. Our findings offer a scalable pathway to decipher the social production of space, providing a mechanism-based lens to understand how the built environment shapes social behavior. △ Less

Submitted 19 June, 2026; originally announced June 2026.

Comments: 34 pages, 15 figures

TransportBench: A Comprehensive Benchmark for Non-Equilibrium Flow Transport

Authors: Xu Wang, Minghao Li, Qizhen Hong, Yang Liu, Chen-an Zhang, Shuai Zhang, Wenhao Li, Yonghao Zhang, Tianbai Xiao

Abstract: Scientific machine learning models, as versatile tools for numerical simulation and analysis, are increasingly transforming the landscape of fluid mechanics research. However, existing datasets and benchmarks are primarily limited to continuum fluids and provide limited support for non-equilibrium transport phenomena. To address this gap, we present TransportBench, a high-fidelity dataset and stan… ▽ More Scientific machine learning models, as versatile tools for numerical simulation and analysis, are increasingly transforming the landscape of fluid mechanics research. However, existing datasets and benchmarks are primarily limited to continuum fluids and provide limited support for non-equilibrium transport phenomena. To address this gap, we present TransportBench, a high-fidelity dataset and standardized benchmark for non-equilibrium flow transport, designed to reveal the strengths and limitations of neural network models across diverse flow regimes. Specifically, the dataset encompasses a broad physical spectrum, covering continuum and rarefied regimes, low-speed and hypersonic flows, inert and chemically reactive gases, and both translational and internal-energy non-equilibrium effects. Built upon this dataset, we systematically benchmark representative neural architectures using unified evaluation protocols to probe key challenges in learning non-equilibrium flows, including robustness to shock-dominated discontinuities and multi-scale effects, as well as generalization across geometry and physical parameters. Numerical results demonstrate that model performance exhibits a pronounced dependence upon the specific flow characteristics. No single architecture consistently performs best for all the tasks. Instead, different architectural inductive biases provide distinct advantages in capturing smooth flow fields, shock-induced discontinuities, and high-order non-equilibrium statistics. By jointly providing the non-equilibrium flow dataset and model benchmark, TransportBench offers a new testbed for the development, evaluation, and diagnosis of scientific machine learning methods for fluid transport beyond the Navier-Stokes hydrodynamics. The benchmark datasets and implementation codes are available under the MIT license. △ Less

Submitted 1 June, 2026; originally announced June 2026.

Comments: 40 pages, 12 figures, 8 tables

Accelerating ground state search of spatial photonic Ising machines with genetic-simulated annealing hybrid algorithm

Authors: Ze Zheng, Ruhui Ni, Jingyi Zhao, Xiaojian Hu, Wen Jiang, Yuegang Li, Hang Xu, Tailong Xiao, Guihua Zeng

Abstract: Spatial photonic Ising machines (SPIMs) based on spatial light modulators (SLMs) have emerged as highly effective solvers for many tasks, including combinatorial optimization problems and spin-glass simulations. However, traditional SPIMs relying solely on the simulated annealing algorithm require a large number of measurement-feedback iterations to find a relatively optimal solution in complex en… ▽ More Spatial photonic Ising machines (SPIMs) based on spatial light modulators (SLMs) have emerged as highly effective solvers for many tasks, including combinatorial optimization problems and spin-glass simulations. However, traditional SPIMs relying solely on the simulated annealing algorithm require a large number of measurement-feedback iterations to find a relatively optimal solution in complex energy landscapes, suffering from slow convergence and high time cost. Here, we propose an optical genetic-simulated annealing hybrid algorithm to accelerate the ground-state search of SPIMs. GA conducts a global coarse-grained search in the early iteration stage, while SA performs fine-grained local refinement in the late stage. Numerical simulations show that our method enables a higher solution quality of full-rank Max-Cut problems than pure GA or SA at different scales. We also experimentally demonstrate its superiority over conventional algorithms on a gauge-transformation time-division multiplexing SPIM for high-rank optimization problems under the same iteration budget. Our approach can be further developed with other advanced metaheuristic algorithms toward intelligent optical Ising computing systems. △ Less

Submitted 22 May, 2026; originally announced May 2026.

Comments: 12 pages, 6 figures

Embedded underwater front-end electronics for the 3-inch photomultipliers in the JUNO experiment

Authors: Cédric Cerna, Miao He, Xiaoshan Jiang, Juan Pedro Ochoa-Ricoux, Frédéric Perrot, Angel Abusleme, Thomas Adam, Fengpeng An, Costas Andreopoulos, Giuseppe Andronico, João Pedro Athayde Marcondes de André, Nikolay Anfimov, Vito Antonelli, Tatiana Antoshkina, Didier Auguste, Nikita Balashov, Andrea Barresi, Davide Basilico, Eric Baussan, Marco Beretta, Antonio Bergnoli, Nikita Bessonov, Daniel Bick, Lukas Bieger, Svetlana Biktemerova , et al. (576 additional authors not shown)

Abstract: The Jiangmen Underground Neutrino Observatory (JUNO) is a 20-kton liquid scintillator-based, low-radioactivity, multi-purpose neutrino detector located 693 meters (1800 m.w.e.) underground in the Guangdong province, China. To detect scintillation light produced in the target, the detector is equipped with 17,612 20-inch photomultipliers (PMTs), forming the Large PMT system (LPMT). In addition, 25,… ▽ More The Jiangmen Underground Neutrino Observatory (JUNO) is a 20-kton liquid scintillator-based, low-radioactivity, multi-purpose neutrino detector located 693 meters (1800 m.w.e.) underground in the Guangdong province, China. To detect scintillation light produced in the target, the detector is equipped with 17,612 20-inch photomultipliers (PMTs), forming the Large PMT system (LPMT). In addition, 25,600 3-inch photomultipliers (the Small Photomultiplier System or SPMT) are deployed in the gaps between the LPMTs. This paper presents the design and performance of the underwater front-end electronics developed for the SPMT system. It details the individual electronics boards and their key components, the inter-board interfaces, the system-level design, and the firmware architecture that supports data acquisition and control. It also outlines mechanical and thermal integration, board validation procedures, and system performance metrics. The readout chain includes digitization of 128 PMT channels per unit, synchronized time-stamping, charge measurement, event packaging, and bandwidth management. Comprehensive validation confirms the system's readiness to meet JUNO's stringent physics goals. The underwater electronics achieve noise levels as low as 0.04 photoelectrons with minimal crosstalk (below 0.4%) and a bandwidth of 57 MB/s, ensuring reliable single photo-electron detection and operation under high-rate conditions. The SPMT system has now been fully integrated and installed in JUNO. Its commissioning and physics performance will be reported in a future publication. △ Less

Submitted 1 June, 2026; v1 submitted 28 April, 2026; originally announced April 2026.

Comments: Submitted to Nucl. Instrum. Methods Phys. Res. A

SesQ: A Surface Electrostatic Simulator for Precise Energy Participation Ratio Simulation in Superconducting Qubits

Authors: Ziang Wang, Shuyuan Guan, Feng Wu, Xiaohang Zhang, Qiong Li, Jianxin Chen, Xin Wan, Tian Xia, Hui-Hai Zhao

Abstract: An accurate and efficient numerical electromagnetic model for superconducting qubits is essential for characterizing and minimizing design-dependent dielectric losses. The energy participation ratio (EPR) is the commonly adopted metric used to evaluate these losses, but its calculation presents a severe multiscale computational challenge. Conventional finite element method (FEM) requires 3D volume… ▽ More An accurate and efficient numerical electromagnetic model for superconducting qubits is essential for characterizing and minimizing design-dependent dielectric losses. The energy participation ratio (EPR) is the commonly adopted metric used to evaluate these losses, but its calculation presents a severe multiscale computational challenge. Conventional finite element method (FEM) requires 3D volumetric meshing, leading to prohibitive computational costs and memory requirements when attempting to capture singular electric fields at nanometer-thin material interfaces. To address this bottleneck, we propose SesQ, a surface integral equation simulator tailored for the precise simulation of the EPR. By applying discretization on 2D surfaces, deriving a semi-analytical multilayer Green's function, and employing a dedicated non-conformal boundary mesh refinement scheme, SesQ accurately resolves singular edge fields without an explosive growth in the number of unknowns. Validations with analytically solvable models demonstrate that SesQ accelerates capacitance extraction by roughly two orders of magnitude compared to commercial FEM tools. While achieving comparable accuracy for capacitance extraction, SesQ delivers superior precision for EPR calculation. Simulations of practical transmon qubits further reveal that FEM approaches tend to significantly underestimate the EPR. Finally, the high efficiency of SesQ enables rapid iteration in the layout optimization, as demonstrated by minimizing the EPR of the qubit pattern, establishing the simulator as a powerful tool for the automated design of low-loss superconducting quantum circuits. △ Less

Submitted 19 May, 2026; v1 submitted 30 March, 2026; originally announced March 2026.

Comments: 15 pages, 14 figures, 3 tables

Simulation Based Characterization of Deconvolution-Based PMT Waveform Reconstruction Under Large Charge Dynamic Range and Varying Scintillation Time Profiles

Authors: Xingyi Lin, Jinghuan Xu, Yongbo Huang, Jingzhe Tang, Tianying Xiao, Yingke Li

Abstract: Photomultiplier tubes (PMTs) are widely used as photon sensors for neutrino and dark matter detection. Accurate charge and time information extracted from PMT waveforms is crucial for event reconstruction. An algorithm based on deconvolution technology was proposed and applied to the reconstruction of PMT waveforms. This study further investigated the reliability of the deconvolution algorithm whe… ▽ More Photomultiplier tubes (PMTs) are widely used as photon sensors for neutrino and dark matter detection. Accurate charge and time information extracted from PMT waveforms is crucial for event reconstruction. An algorithm based on deconvolution technology was proposed and applied to the reconstruction of PMT waveforms. This study further investigated the reliability of the deconvolution algorithm when handling a large charge dynamic range (0-200 photoelectrons), varying scintillation time profiles, and muon-induced large signals. Monte Carlo data confirmed that the deconvolution algorithm exhibits relatively stable reconstruction performance: under the simulation conditions described in this paper (including a noise level of 0.1 PE, single photoelectron charge resolution of 30%, 1 GHz sampling rate, 1000 ns window, three undershoot configurations, and eight scintillation time profiles), the residual non-linearity of charge reconstruction is controlled to approximately 1% over the range of 0 to 200 photoelectrons, and the algorithm is capable of handling muon-induced large signals. The reconstruction performance depends on adequate baseline recovery; a waveform window that is too short relative to the undershoot tail leads to degraded reconstruction quality, which can be mitigated by extending the sampling window. △ Less

Submitted 28 June, 2026; v1 submitted 18 March, 2026; originally announced March 2026.

Experimental Quantification of Spin-Phonon Coupling in Molecular Qubits using Inelastic Neutron Scattering

Authors: Stefan H. Lohaus, Kay T. Xia, Yongqiang Cheng, Ryan G. Hadt

Abstract: Electronic spin superposition states enable nanoscale sensing through their sensitivity to the local environment, yet their sensitivity to vibrational motion also limits their coherence times. In molecular spin systems, chemical tunability and atomic-scale resolution are accompanied by a dense, thermally accessible phonon spectrum that introduces efficient spin relaxation pathways. Despite extensi… ▽ More Electronic spin superposition states enable nanoscale sensing through their sensitivity to the local environment, yet their sensitivity to vibrational motion also limits their coherence times. In molecular spin systems, chemical tunability and atomic-scale resolution are accompanied by a dense, thermally accessible phonon spectrum that introduces efficient spin relaxation pathways. Despite extensive theoretical work, there is little experimental consensus on which vibrational energies dominate spin relaxation or how molecular structure controls spin-phonon coupling (SPC). We present a fully experimental method to quantify SPC coefficients by combining temperature-dependent vibrational spectra from inelastic neutron scattering with spin relaxation rates measured by electron paramagnetic resonance. We apply this framework to two model S = 1/2 systems, copper(II) phthalocyanine (CuPc) and copper(II) octaethylporphyrin (CuOEP). Two distinct relaxation regimes emerge: below 40 K, weakly coupled lattice modes below $50~\mathrm{cm}^{-1}$ dominate, whereas above 40 K, optical phonons above ~$185~\mathrm{cm}^{-1}$ become thermally populated and drive relaxation with SPC coefficients nearly three orders of magnitude larger. Structural distortions in CuOEP that break planar symmetry soften the crystal lattice and enhance anharmonic scattering, but also raise the energy of stretching modes at the molecular core where the spins reside. This redistributes vibrational energy toward the molecular periphery and out of plane, ultimately reducing SPC relative to CuPc and enabling room-temperature spin coherence in CuOEP. Although our method does not provide mode-specific SPC coefficients, it quantifies contributions from distinct spectral regions and establishes a broadly applicable, fully experimental link between crystal structure, lattice dynamics, and spin relaxation. △ Less

Submitted 2 February, 2026; originally announced February 2026.

Comments: 21 pages, 5 figures, 1 table

Incorporating rank-free coupling and external field via an incoherent modulated spatial photonic Ising machine

Authors: Ze Zheng, Yuegang Li, Hang Xu, Jingzheng Huang, Tailong Xiao, Guihua Zeng

Abstract: Spatial photonic Ising machines offer a novel optical platform for optimization and spin-model simulation, but existing diffraction-based schemes rely on auxiliary spins or multiplexing to encode high-rank couplings and external fields, reducing either speed or spin count. We demonstrate an amplitude-only, rank-free spatial photonic Ising machine in which arbitrary Ising Hamiltonians are encoded a… ▽ More Spatial photonic Ising machines offer a novel optical platform for optimization and spin-model simulation, but existing diffraction-based schemes rely on auxiliary spins or multiplexing to encode high-rank couplings and external fields, reducing either speed or spin count. We demonstrate an amplitude-only, rank-free spatial photonic Ising machine in which arbitrary Ising Hamiltonians are encoded as Hadamard products on aligned amplitude and binary spatial modulators and read out by a single-pixel intensity measurement. The machine directly programs fully connected 797-spin Ising models with external fields at nearly 9-bit precision and operates at a constant iteration rate of ~200 Hz. By removing zero-valued product terms, the same architecture scales to sparse problems and experimentally solves a Max-Cut instance on a 424,108-vertex Mobius ladder graph. We also observe the phase transition of the Sherrington-Kirkpatrick model, demonstrating programmable optical simulation beyond low-rank couplings. These results establish amplitude modulation as a scalable route to programmable photonic Ising machines. △ Less

Submitted 11 May, 2026; v1 submitted 25 December, 2025; originally announced December 2025.

Comments: 15 pages, 6 figures

An immersed boundary method for the discrete velocity model of the Boltzmann equation

Authors: Longqing Ge, Qingdong Cai, Yonghao Zhang, Tianbai Xiao

Abstract: Computational modeling and simulation of fluid-structure interactions constitute a fundamental cornerstone for advancing aerospace engineering endeavors. This paper addresses the notion and implementation of the immersed boundary method for the discrete velocity model of the Boltzmann equation. The method incorporates the Maxwell gas-surface interaction model into the construction of ghost-cell pa… ▽ More Computational modeling and simulation of fluid-structure interactions constitute a fundamental cornerstone for advancing aerospace engineering endeavors. This paper addresses the notion and implementation of the immersed boundary method for the discrete velocity model of the Boltzmann equation. The method incorporates the Maxwell gas-surface interaction model into the construction of ghost-cell particle distribution functions, facilitating meticulous characterization of velocity slip and temperature jump effects within a Cartesian grid framework, which ultimately achieves accurate prediction of aerodynamic parameters. This study presents two principal advancements. First, an upwind-weighted compact interpolation strategy is developed in physical space, which ensures numerical stability and robustness for arbitrary geometries without relying on large stencils or normal-direction projections. Second, a cut-cell correction methodology is proposed in velocity space to address the degradation of quadrature accuracy caused by surface discontinuities. The resulting framework is equally applicable to both two- and three-dimensional problems without requiring any dimension-specific modifications. Rigorous analysis is provided to prove that the approach maintains second-order accuracy across both physical and velocity space, while ensuring robust numerical stability. Comprehensive numerical experiments demonstrate that the solution algorithm achieves the designed accuracy and delivers precise predictions comparable to body-conformal solvers, while retaining the simplicity, flexibility, and scalability of the Cartesian grid method. The proposed approach provides a unified and physically consistent immersed boundary framework for simulating dynamic interactions between non-equilibrium flows and structural components across a wide range of flow regimes. △ Less

Submitted 23 December, 2025; originally announced December 2025.

Comments: 44 pages, 25 figures, 1 table

Optical diffraction neural networks assisted computational ghost imaging through dynamic scattering media

Authors: Yue-Gang Li, Ze Zheng, Jun-jie Wang, Ming He, Jianping Fan, Tailong Xiao, Guihua Zeng

Abstract: Ghost imaging leverages a single-pixel detector with no spatial resolution to acquire object echo intensity signals, which are correlated with illumination patterns to reconstruct an image. This architecture inherently mitigates scattering interference between the object and the detector but sensitive to scattering between the light source and the object. To address this challenge, we propose an o… ▽ More Ghost imaging leverages a single-pixel detector with no spatial resolution to acquire object echo intensity signals, which are correlated with illumination patterns to reconstruct an image. This architecture inherently mitigates scattering interference between the object and the detector but sensitive to scattering between the light source and the object. To address this challenge, we propose an optical diffraction neural networks (ODNNs) assisted ghost imaging method for imaging through dynamic scattering media. In our scheme, a set of fixed ODNNs, trained on simulated datasets, is incorporated into the experimental optical path to actively correct random distortions induced by dynamic scattering media. Experimental validation using rotating single-layer and double-layer ground glass confirms the feasibility and effectiveness of our approach. Furthermore, our scheme can also be combined with physics-prior-based reconstruction algorithms, enabling high-quality imaging under undersampled conditions. This work demonstrates a novel strategy for imaging through dynamic scattering media, which can be extended to other imaging systems. △ Less

Submitted 28 November, 2025; originally announced November 2025.

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

Detection of Temporal Variability in U.S. Climate Using Harmonic and Wavelet Decomposition

Authors: Thomas Xiao

Abstract: This study investigates temporal variability in U.S. climate using harmonic decomposition techniques, specifically Fourier and wavelet transforms. Monthly temperature, precipitation, and drought index data from the National Oceanic and Atmospheric Administration (NOAA) U.S. Climate Divisional Dataset (nClimDiv, 1895--2024) were analyzed to detect periodic structures and their evolution over time.… ▽ More This study investigates temporal variability in U.S. climate using harmonic decomposition techniques, specifically Fourier and wavelet transforms. Monthly temperature, precipitation, and drought index data from the National Oceanic and Atmospheric Administration (NOAA) U.S. Climate Divisional Dataset (nClimDiv, 1895--2024) were analyzed to detect periodic structures and their evolution over time. By comparing harmonic-based models with linear regression trends, this research evaluates the explanatory power of cyclic components in reproducing and predicting observed variability. Results show that U.S. climate records exhibit dominant periodicities near one year (seasonal) and 2--7 years (associated with the El Nino--Southern Oscillation, ENSO), and that incorporating harmonic terms significantly improves model performance across most states and variables. The findings indicate that U.S. climate fluctuations are characterized by quasi-stationary oscillations rather than purely monotonic trends. Overall, the main implication is that frequency-aware models provide measurably better predictive skill than trend-only approaches and should be incorporated into seasonal outlooks, drought monitoring, and resource planning. △ Less

Submitted 9 November, 2025; originally announced November 2025.

Prospects for geoneutrino detection with JUNO

Authors: Thomas Adam, Shakeel Ahmad, Rizwan Ahmed, Fengpeng An, João Pedro Athayde Marcondes de André, Costas Andreopoulos, Giuseppe Andronico, Nikolay Anfimov, Vito Antonelli, Tatiana Antoshkina, Didier Auguste, Marcel Büchner, Weidong Bai, Nikita Balashov, Andrea Barresi, Davide Basilico, Eric Baussan, Marco Beretta, Antonio Bergnoli, Nikita Bessonov, Daniel Bick, Lukas Bieger, Svetlana Biktemerova, Thilo Birkenfeld, Simon Blyth , et al. (605 additional authors not shown)

Abstract: Geoneutrinos, which are antineutrinos emitted during the decay of long-lived radioactive elements inside Earth, serve as a unique tool for studying the composition and heat budget of our planet. The Jiangmen Underground Neutrino Observatory (JUNO) experiment in China, which has recently completed construction, is expected to collect a sample comparable in size to the entire existing world geoneutr… ▽ More Geoneutrinos, which are antineutrinos emitted during the decay of long-lived radioactive elements inside Earth, serve as a unique tool for studying the composition and heat budget of our planet. The Jiangmen Underground Neutrino Observatory (JUNO) experiment in China, which has recently completed construction, is expected to collect a sample comparable in size to the entire existing world geoneutrino dataset in less than a year. This paper presents an updated estimation of sensitivity to geoneutrinos of JUNO using the best knowledge available to date about the experimental site, the surrounding nuclear reactors, the detector response uncertainties, and the constraints expected from the TAO satellite detector. To facilitate comparison with present and future geological models, our results cover a wide range of predicted signal strengths. Despite the significant background from reactor antineutrinos, the experiment will measure the total geoneutrino flux with a precision comparable to that of existing experiments within its first few years, ultimately achieving a world-leading precision of about 8% over ten years. The large statistics of JUNO will also allow separation of the Uranium-238 and Thorium-232 contributions with unprecedented precision, providing crucial constraints on models of formation and composition of Earth. Observation of the mantle signal above the lithospheric flux will be possible but challenging. For models with the highest predicted mantle concentrations of heat-producing elements, a 3-sigma detection over six years requires knowledge of the lithospheric flux to within 15%. Together with complementary measurements from other locations, the geoneutrino results of JUNO will offer cutting-edge, high-precision insights into the interior of Earth, of fundamental importance to both the geoscience and neutrino physics communities. △ Less

Submitted 10 November, 2025; originally announced November 2025.

Comments: 32 pages, with 13 figures and 5 tables

Diversity legitimizes science: Holding basic research in the physical sciences accountable to the public

Authors: Kay T. Xia, Thayer L. Anderson, Phelan Yu

Abstract: The American scientific community is reeling from funding cuts and policy directives that will debilitate scientific research and education. The underlying hostilities fueling these attacks have intensified in recent years as the COVID-19 pandemic increased suspicion of scientific experts and the institutional embrace of diversity, equity, and inclusion (DEI) policies in 2020 prompted a backlash a… ▽ More The American scientific community is reeling from funding cuts and policy directives that will debilitate scientific research and education. The underlying hostilities fueling these attacks have intensified in recent years as the COVID-19 pandemic increased suspicion of scientific experts and the institutional embrace of diversity, equity, and inclusion (DEI) policies in 2020 prompted a backlash along longstanding political fault lines. Under the banner of anti-elitism, opponents of science and DEI have formed a coalition that sees attacks on higher education as a strategic means to achieve their political ends. While some of their arguments contain legitimate criticisms, academics must resist these attacks that seek to dismantle higher education altogether. Instead, we should engage the public in our research process, build a scientific practice representative of and accountable to the communities we serve, and interrogate the aims of our work by critically studying the history of science. △ Less

Submitted 17 October, 2025; originally announced October 2025.

Comments: 13 pages excluding references. This paper was written for an invited editorial, but its publication was denied on political grounds

Thermodynamically consistent modeling and simulation of two-fluid magnetohydrodynamic equations

Authors: Ting Xiao, Qiaolin He

Abstract: Based on a rigorous thermodynamic framework, this work develops a two-fluid magnetohydrodynamic model grounded in the Helmholtz free energy formalism. The model maintains full thermodynamic consistency by simultaneously satisfying energy conservation and entropy production laws in two-fluid systems. By analyzing the convex-concave structure of the Helmholtz free energy density, we systematically d… ▽ More Based on a rigorous thermodynamic framework, this work develops a two-fluid magnetohydrodynamic model grounded in the Helmholtz free energy formalism. The model maintains full thermodynamic consistency by simultaneously satisfying energy conservation and entropy production laws in two-fluid systems. By analyzing the convex-concave structure of the Helmholtz free energy density, we systematically derive key thermodynamic variables-chemical potential, entropy density, and internal energy-in a self-consistent manner. Building on this foundation, we construct a temporally discrete numerical scheme that inherits the thermodynamic consistency of the continuous model. The scheme is proven to adhere rigorously to both the first and second laws of thermodynamics. For the implemented two-dimensional degenerate system, we establish comprehensive a priori error estimates in space and time. Numerical simulations validate the model's effectiveness in capturing essential plasma phenomena, demonstrating its applicability to complex physical scenarios. △ Less

Submitted 5 November, 2025; v1 submitted 17 August, 2025; originally announced September 2025.

Real-time imaging through dynamic scattering media enabled by fixed optical modulations

Authors: Yuegang Li, Junjie Wang, Tailong Xiao, Ze Zheng, Jingzheng Huang, Ming He, Jianping Fan, Guihua Zeng

Abstract: Dynamic scattering remains a significant challenge to the practical deployment of anti-scattering imaging. Existing methods, such as transmission matrix measurements, iterative wavefront shaping, and optical phase conjugation, depend on a quasi-static assumption, requiring the object and scattering medium to remain stable during a single imaging process to enable one-to-one compensation. However,… ▽ More Dynamic scattering remains a significant challenge to the practical deployment of anti-scattering imaging. Existing methods, such as transmission matrix measurements, iterative wavefront shaping, and optical phase conjugation, depend on a quasi-static assumption, requiring the object and scattering medium to remain stable during a single imaging process to enable one-to-one compensation. However, image reconstruction becomes unattainable when this assumption is violated. Here, we propose a novel imaging strategy that counteracts time-dependent scattering perturbations through a fixed modulation module. This one-to-many compensation mechanism is realized via optical diffraction neural networks (ODNNs) trained on simulated datasets. For the first time, we reveal that its feasibility stems from the optical shower-curtain effect, and its effectiveness typically within 1-2 transport mean free paths. Our approach is not only immune to speckle decorrelation but also leverages it to enhance image quality. ODNNs generalize effectively to real-world scattering medium scenarios via multi-simulated scattering media learning and reconstruct images in real time with light-speed processing. We achieve 80 Hz imaging of moving objects in dynamic scattering media with decorrelation times < 1 ms, demonstrating applicability in large-field-of-view imaging and incoherent illumination scenarios. This work lays the foundation for high-speed, intelligent optical imaging, advancing practical anti-dynamic scattering techniques. △ Less

Submitted 21 August, 2025; originally announced August 2025.

Comments: 5figures

Incoherent Light-Driven Nonlinear Optical Extreme Learner via Data Reverberation

Authors: Bofeng Liu, Xu Mei, Sadman Shafi, Tunan Xia, Iam-Choon Khoo, Zhiwen Liu, Xingjie Ni

Abstract: Artificial neural networks have revolutionized fields from computer vision to natural language processing, yet their growing energy and computational demands threaten future progress. Optical neural networks promise greater speed, bandwidth, and energy efficiency, but suffer from weak optical nonlinearities. Here, we demonstrate a low-power, incoherent-light-driven optical extreme learner that lev… ▽ More Artificial neural networks have revolutionized fields from computer vision to natural language processing, yet their growing energy and computational demands threaten future progress. Optical neural networks promise greater speed, bandwidth, and energy efficiency, but suffer from weak optical nonlinearities. Here, we demonstrate a low-power, incoherent-light-driven optical extreme learner that leverages 'data nonlinearity' from optical pattern reverberation, eliminating reliance on intrinsic nonlinear materials. By encoding input data in the spatial polarization distribution of a tailored optical cavity and allowing light to pass through it multiple times, we achieve nonlinear transformations at extremely low optical power. Coupled with a simple trainable readout, our optical learner consistently outperforms linear digital networks in standard image classification tasks and XOR benchmarks, delivering accuracy matching fully nonlinear digital models. Our compact, energy-efficient approach significantly reduces complexity, cost, and energy consumption, paving the way for practical, scalable all-optical machine learning platforms. △ Less

Submitted 15 August, 2025; v1 submitted 11 August, 2025; originally announced August 2025.

Observation of Anti-helical Edge States in Acoustic Metamaterials

Authors: Tianzhi Xia, Qicheng Zhang, Chunyin Qiu

Abstract: As a hallmark of the quantum Hall effect, chiral edge modes (CEMs) counterpropagate along the two parallel edges of a ribbon structure. However, recent studies demonstrate counterintuitive antiCEMs that copropagate along the parallel edges. Analogous to the established extension of the CEMs to helical edge modes (HEMs) in the quantum spin Hall effect, it is natural to extend the antiCEMs to antiHE… ▽ More As a hallmark of the quantum Hall effect, chiral edge modes (CEMs) counterpropagate along the two parallel edges of a ribbon structure. However, recent studies demonstrate counterintuitive antiCEMs that copropagate along the parallel edges. Analogous to the established extension of the CEMs to helical edge modes (HEMs) in the quantum spin Hall effect, it is natural to extend the antiCEMs to antiHEMs, which comprise a pair of time-reversal-related antiCEMs. In this Letter, we report the first observation of the antiHEMs based on a bilayer model that features staggered positive and negative interlayer hoppings. Experimentally, we implement this anti-helical model on an acoustic platform and provide compelling evidence for the antiHEMs by selectively exciting different spin subspaces, along with identifying the energybiased Dirac points in bulk spectra. Our findings may offer new insights into topological phases of matter and potentially pave the way for designing novel devices with unique edge transport properties. △ Less

Submitted 9 August, 2025; originally announced August 2025.

Comments: Phys. Rev. Lett. 135, 056601 Published 30 July, 2025

Tight-binding photonics

Authors: Jing Li, Aodong Li, Yutao Chen, Tao Xiao, Renwen Huang, Xiaolu Zhuo, Jun Guan, Zhen Gao, Peng Zhan, Minghui Lu, Biye Xie

Abstract: Photonics, dealing with the generation, manipulation, and detection of photons in various systems, lays the foundation of many advanced technologies. A key task of photonics is to know how photons propagate in complex media such as periodic and aperiodic photonic crystals. The conventional wisdom is to numerically solve the Maxwell equations either by dedicated numerical techniques or brute-force… ▽ More Photonics, dealing with the generation, manipulation, and detection of photons in various systems, lays the foundation of many advanced technologies. A key task of photonics is to know how photons propagate in complex media such as periodic and aperiodic photonic crystals. The conventional wisdom is to numerically solve the Maxwell equations either by dedicated numerical techniques or brute-force finite-element calculations. Recently, the strict analogy between photonic crystals and theoretical tight-binding models provides an unprecedentedly convenient wayof understanding the spectra and wavefunctions of photonic systems by mapping the complicated differential equationsinto matrixed Hamiltonians that can be easily solved through the band theory and exact diagonalization. in this paper, we present a timely review of tight-binding-like photonics in various platforms, covering fundamental theories, experimental realizations, unique physical efiects, and their potential applications. We also provide a brief outlook on the future trends of this active area. Our review offers an in-depth and comprehensive picture on this rapidly developing field and may shed light on the future design on advanced tight-binding-like photonic devices. △ Less

Submitted 6 August, 2025; originally announced August 2025.

Comments: 90 pages, 7 figures

An efficient solution algorithm for force-driven continuum and rarefied flows

Authors: Shuangqing Liu, Zuoxu Li, Yonghao Zhang, Tianbai Xiao

Abstract: Gaseous flows under an external force are intrinsically defined by their multi-scale nature due to the large variation of densities along the forcing direction. Devising a numerical method capable of accurately and efficiently solving force-driven cross-scale flow dynamics, encompassing both continuum and rarefied regimes, continues to pose a formidable and enduring challenge. In this work, a nove… ▽ More Gaseous flows under an external force are intrinsically defined by their multi-scale nature due to the large variation of densities along the forcing direction. Devising a numerical method capable of accurately and efficiently solving force-driven cross-scale flow dynamics, encompassing both continuum and rarefied regimes, continues to pose a formidable and enduring challenge. In this work, a novel solution algorithm for multi-scale and non-equilibrium flow transport under an external force is developed based on the Boltzmann-BGK equation. The core innovation lies in the fusion of the Hermite spectral method (employed to characterize non-equilibrium particle distributions) with a multi-scale evolution model (sourced from the unified gas-kinetic scheme), achieving a seamless connection between computational methods and physical models. To accommodate the properties of the spectral-collocation method, a series of collocation points and weights are adapted based on the Gauss-Hermite quadrature. As a result, the computational efficiency of the solution algorithm is significantly improved (up to 50 times) while maintaining comparable accuracy as the classical discrete velocity method. It is demonstrated that the solution algorithm effectively preserves the key structural features of gas-dynamic systems subjected to an external force, e.g., the well-balanced property. Extensive numerical experiments have been performed to verify the accuracy and efficiency of the proposed method, including the one-dimensional hydrostatic equilibrium problem, the Sod shock tube, the Fourier flow, the Poiseuille flow, and the Rayleigh-Taylor instability problem. The proposed methodology can provide substantive theoretical insights into a wide range of engineering challenges involving force-driven multi-scale flows. △ Less

Submitted 14 July, 2025; originally announced July 2025.

Comments: 33 pages, 12 figures, 11 tables

Observation of the electric Breit-Rabi Effect

Authors: S. -Z. Wang, S. -B. Wang, Z. -J. Tao, T. Xia, Z. -T. Lu

Abstract: The response of an atom to external electric and magnetic fields can reveal fundamental atomic properties. It has long been verified that, in a static magnetic field, those atomic energy levels with hyperfine interactions shift according to the Breit-Rabi formula, which introduces nonlinear dependence on the magnetic field. On the other hand, the corresponding Breit-Rabi dependence on a static ele… ▽ More The response of an atom to external electric and magnetic fields can reveal fundamental atomic properties. It has long been verified that, in a static magnetic field, those atomic energy levels with hyperfine interactions shift according to the Breit-Rabi formula, which introduces nonlinear dependence on the magnetic field. On the other hand, the corresponding Breit-Rabi dependence on a static electric field has not been observed before due to a combination of experimental challenges. Here we precisely measure the Stark shift of the $6s^2\ ^1S_0\ \leftrightarrow\ 6s6p\ ^1P_1$ transition of $^{171}$Yb ($I$ = 1/2) with cold atoms held by an optical dipole trap in a static electric field up to 120 kV/cm. We observe the electric Breit-Rabi effect displaying high-order ($E^4$ and $E^6$) DC Stark shifts. These effects arise from the influence of the strong electric field on hyperfine interactions. △ Less

Submitted 10 July, 2025; originally announced July 2025.

Comments: 12 pages, 8 figures

Journal ref: 122 (26)e2423902122 June 27 2025

Ensemble nonlinear optical learner by electrically tunable linear scattering

Authors: Tunan Xia, Cheng-Kuan Wu, Duan-Yi Guo, Lidan Zhang, Bofeng Liu, Tsung-Hsien Lin, Xingjie Ni, Iam-Choon Khoo, Zhiwen Liu

Abstract: Recent progress in effective nonlinearity, achieved by exploiting multiple scatterings within the linear optical regime, has been demonstrated to be a promising approach to enable nonlinear optical processing without relying on actual material nonlinearity. Here we introduce an ensemble nonlinear optical learner, via electrically tunable linear scattering in a liquid-crystal-polymer composite film… ▽ More Recent progress in effective nonlinearity, achieved by exploiting multiple scatterings within the linear optical regime, has been demonstrated to be a promising approach to enable nonlinear optical processing without relying on actual material nonlinearity. Here we introduce an ensemble nonlinear optical learner, via electrically tunable linear scattering in a liquid-crystal-polymer composite film under low optical power and low applied electrical voltages. We demonstrate, through several image classification tasks, that by combining inference results from an ensemble of nonlinear optical learners realized at different applied voltages, the ensemble optical learning significantly outperforms the classification performance of individual processors. With very low-level optical power and electrical voltage requirements, and ease in reconfiguration simply by varying applied voltages, the ensemble nonlinear optical learning offers a cost-effective and flexible way to improve computing performance and enhance inference accuracy. △ Less

Submitted 24 June, 2025; originally announced June 2025.

A self-heating electrochemical cell with nine decades of programmable linear resistance

Authors: Adam L. Gross, Sangheon Oh, Minseong Park, T. Patrick Xiao, François Léonard, Wyatt Hodges, Joshua D. Sugar, Jacklyn Zhu, Sritharini Radhakrishnan, Sangyong Lee, Jolie Wang, Adam S. Christensen, Sam Lilak, Patrick S. Finnegan, Patrick Crandall, Christopher H. Bennett, William Wahby, Robin Jacobs-Gedrim, Matthew J. Marinella, Yiyang Li, Su-in Yi, Nad Gilbert, Sapan Agarwal, A. Alec Talin, Elliot J. Fuller

Abstract: A programmable linear resistor with a compact footprint would have profound implications for microelectronics, enabling efficient in-sensor analog signal processing and in-memory computing. Non-volatile memory offers a potential solution but suffers from limitations due to the programming mechanisms that confine switching to nanoscale constrictions or field-sensitive semiconductor junctions, leadi… ▽ More A programmable linear resistor with a compact footprint would have profound implications for microelectronics, enabling efficient in-sensor analog signal processing and in-memory computing. Non-volatile memory offers a potential solution but suffers from limitations due to the programming mechanisms that confine switching to nanoscale constrictions or field-sensitive semiconductor junctions, leading to non-linear current-voltage relationships and errors. Here, we introduce a tunable resistor that is programmed into non-volatile, high-precision resistance states spanning nine orders of magnitude, with linear current-voltage characteristics across the entire range -- significantly improving the performance and widening the application space of resistive memory. A key advance is an electrothermal gate that simultaneously spreads heat and electrochemical reactions during programming to enable large, bulk composition modulation. The volumetric modulation can host thousands of linear resistance states with 100x lower conductance errors than other memory. This enables direct processing of analog signals with high fidelity, and we demonstrate variable-gain amplification, division, and multiplication. Integration with CMOS is used to show resilience to electrical and thermal disturb in arrays and to demonstrate retention of analog levels at <1% average loss for more than 2 months across 100 devices. Simulations indicate matrix multiplication efficiency could approach >1,000 TOPS/W. △ Less

Submitted 2 April, 2026; v1 submitted 21 May, 2025; originally announced May 2025.

Interaction effects on electronic Floquet spectra: Excitonic effects

Authors: Teng Xiao, Tsan Huang, Changhua Bao, Zhiyuan Sun

Abstract: Floquet engineering of electronic states by light is a central topic in modern experiments. However, the impact of many-body interactions on the single-electron properties remains unclear in this non-equilibrium situation. We propose that interaction effects could be reasonably understood by performing perturbative expansion in both the pump field and the electron-electron interaction when computi… ▽ More Floquet engineering of electronic states by light is a central topic in modern experiments. However, the impact of many-body interactions on the single-electron properties remains unclear in this non-equilibrium situation. We propose that interaction effects could be reasonably understood by performing perturbative expansion in both the pump field and the electron-electron interaction when computing physical quantities. As an example, we apply this approach to semiconductors and show analytically that excitonic effects, i.e., effects of electron-hole interaction, lead to dramatic corrections to the single-electron Floquet spectra even when the excitons are only virtually excited by the pump light. We compute these effects in phosphorene and monolayer MoS$_2$ for time- and angle-resolved photoemission spectroscopy and ultrafast optical experiments. △ Less

Submitted 5 October, 2025; v1 submitted 12 May, 2025; originally announced May 2025.

Journal ref: Phys. Rev. B 112, L161106(2025)

High-Dimensional Light Field Modulation via Conjugate Phase Encoding in Liquid Crystal Devices

Authors: Tian Xia, Quanzhou Long, Wanlong Zhang, Zhenwei Xie, Xiaocong Yuan

Abstract: High-dimensional light field modulation demands precise control over multiple optical parameters, a capability critical for next-generation photonic systems. While liquid crystals offer inherent advantages in dynamic birefringence tuning, existing approaches face fundamental limitations in decoupling interdependent phase responses across polarization states. Here, we demonstrate a conjugate phase… ▽ More High-dimensional light field modulation demands precise control over multiple optical parameters, a capability critical for next-generation photonic systems. While liquid crystals offer inherent advantages in dynamic birefringence tuning, existing approaches face fundamental limitations in decoupling interdependent phase responses across polarization states. Here, we demonstrate a conjugate phase encoding paradigm enabling simultaneous manipulation of wavelength-dependent wavefronts, orbital angular momentum (OAM), and polarization states in photoaligned liquid crystal devices. △ Less

Submitted 20 April, 2025; originally announced April 2025.

A Navier-Stokes-Peridynamics hybrid algorithm for the coupling of compressible flows and fracturing materials

Authors: Mingshuo Han, Shiwei Hu, Tianbai Xiao, Yonghao Zhang

Abstract: Modeling and simulation of fluid-structure interactions are crucial to the success of aerospace engineering. This work addresses a novel hybrid algorithm that models the close coupling between compressible flows and deformable materials using a mesoscopic approach. Specifically, the high-speed flows are described by the gas-kinetic scheme, which is a robust Navier-Stokes alternative solver built o… ▽ More Modeling and simulation of fluid-structure interactions are crucial to the success of aerospace engineering. This work addresses a novel hybrid algorithm that models the close coupling between compressible flows and deformable materials using a mesoscopic approach. Specifically, the high-speed flows are described by the gas-kinetic scheme, which is a robust Navier-Stokes alternative solver built on the molecular kinetic theory. The deformation, damage, and fracture of materials are depicted using the bond-based peridynamics, which serves as coarse-grained molecular dynamics to construct non-local extensions of classical continuum mechanics. The evolution of fluids and materials are closely coupled using the ghost-cell immersed boundary method. Within each time step, the solutions of flow and solid fields are updated simultaneously, and physics-driven boundary conditions are exchanged for each other via ghost cells. Extensive numerical experiments, including crack propagation in a pre-cracked plate, subsonic flow around the NACA0012 airfoil, supersonic flow around the circular cylinder, and shock wave impacting on the elastic panel, are performed to validate the algorithm. The simulation results demonstrate the unique advantages of current hybrid algorithm in solving fracture propagation induced by high-speed flows. △ Less

Submitted 15 April, 2025; originally announced April 2025.

Comments: 25 pages, 17 figures, 3 tables

Quantum neural compressive sensing for ghost imaging

Authors: Xinliang Zhai, Tailong Xiao, Jingzheng Huang, Jianping Fan, Guihua Zeng

Abstract: Demonstrating the utility of quantum algorithms is a long-standing challenge, where quantum machine learning becomes one of the most promising candidate that can be resorted to. In this study, we investigate a quantum neural compressive sensing algorithm for ghost imaging to showcase its utility. The algorithm utilizes the variational quantum circuits to reparameterize the inverse problem of ghost… ▽ More Demonstrating the utility of quantum algorithms is a long-standing challenge, where quantum machine learning becomes one of the most promising candidate that can be resorted to. In this study, we investigate a quantum neural compressive sensing algorithm for ghost imaging to showcase its utility. The algorithm utilizes the variational quantum circuits to reparameterize the inverse problem of ghost imaging and uses the inductive bias of the physical forward model to perform optimization. To validate the algorithm's effectiveness, we conduct optical ghost imaging experiments, capturing signals from objects at different physical sampling rates and detection signal-to-noise ratios. The experimental results show that our proposed algorithm surpasses conventional methods in both visual appearance and quantitative metrics, achieving state-of-the-art performance. Importantly, we observe that the quantum neural network, guided by prior knowledge of physics, effectively overcomes the challenge of barren plateau in the optimization process. The proposed algorithm demonstrates robustness against various quantum noise levels, making it suitable for near-term quantum devices. Our study leverages physical inductive bias guided variational quantum algorithm, underscoring the potential of quantum computation in tackling a broad range of optimization and inverse problems. △ Less

Submitted 24 February, 2025; originally announced February 2025.

Journal ref: Physical Review Applied 23.1 (2025): 014018

Flexible radiofrequency carbon nanotube transistors operating at frequencies above 100 GHz

Authors: Fan Xia, Tian Xia, Haotian Su, Lanyue Gan, Qianlan Hu, Wanyi Wang, Ruyi Huang, Tianshun Bai, Yufan Chen, Chao Ma, Guanhua Long, Shan X. Wang, Eric Pop, Lian-Mao Peng, Youfan Hu

Abstract: The development of the sixth generation of wireless communications technology (6G) requires terminals that can operate at frequencies above 100 GHz. For human-centric applications, these terminals should also be flexible and have low power. However, current flexible radiofrequency transistors typically have lower maximum frequencies, in part due to the poor thermal conductivity of flexible substra… ▽ More The development of the sixth generation of wireless communications technology (6G) requires terminals that can operate at frequencies above 100 GHz. For human-centric applications, these terminals should also be flexible and have low power. However, current flexible radiofrequency transistors typically have lower maximum frequencies, in part due to the poor thermal conductivity of flexible substrates. Here, we report radiofrequency transistors that are based on aligned carbon nanotube arrays on flexible substrates and have current gain cutoff frequencies ($f_{\text{T}}$) and power gain cutoff frequencies ($f_{\text{max}}$) above 100 GHz. This is achieved by using electro-thermal co-design to improve the heat dissipation and radiofrequency performance of the devices. The transistors exhibit an on-state current of 0.947 mA $μ$m$^{-1}$, a transconductance of 0.728 mS $μ$m$^{-1}$, a peak extrinsic $f_{\text{T}}$ of 152 GHz, a peak extrinsic $f_{\text{max}}$ of 102 GHz, and a power consumption under 200 mW mm$^{-1}$. We also show that the devices can be used to create flexible radiofrequency amplifiers with an output power of 64 mW mm$^{-1}$ and a 11 dB power gain in the K-band. △ Less

Submitted 15 March, 2026; v1 submitted 4 February, 2025; originally announced February 2025.

Comments: 63 pages, 30 figures

Two measurement bases are asymptotically informationally complete for any pure state tomography

Authors: Tianfeng Feng, Tianqi Xiao, Yu Wang, Shengshi Pang, Farhan Hanif, Xiaoqi Zhou, Qi Zhao, M. S. Kim, Jinzhao Sun

Abstract: One of the fundamental questions in quantum information theory is to find how many measurement bases are required to obtain the full information of a quantum state. While a minimum of four measurement bases is typically required to determine an arbitrary pure state, we prove that for any states generated by finite-depth Clifford + T circuits, just two measurement bases are sufficient. More general… ▽ More One of the fundamental questions in quantum information theory is to find how many measurement bases are required to obtain the full information of a quantum state. While a minimum of four measurement bases is typically required to determine an arbitrary pure state, we prove that for any states generated by finite-depth Clifford + T circuits, just two measurement bases are sufficient. More generally, we prove that two measurement bases are informationally complete for determining algebraic pure states whose state-vector elements represented in the computational basis are algebraic numbers. Since any pure state can be asymptotically approximated by a sequence of algebraic states with arbitrarily high precision, our scheme is referred to as asymptotically informationally complete for pure state tomography. Furthermore, existing works mostly construct the measurements using entangled bases. So far, the best result requires $O(n)$ local measurement bases for $n$-qubit pure-state tomography. Here, we show that two measurement bases that involve polynomial elementary gates are sufficient for uniquely determining sparse algebraic states. Moreover, we prove that two local measurement bases, involving single-qubit local operations only, are informationally complete for certain algebraic states, such as GHZ-like and W-like states. Besides, our two-measurement-bases scheme remains valid for mixed states with certain types of noises. We numerically test the uniqueness of the reconstructed states under two (local) measurement bases with and without measurement and depolarising types of noise. Our scheme provides a theoretical guarantee for pure state tomography in the fault-tolerant quantum computing regime. △ Less

Submitted 28 January, 2025; originally announced January 2025.

Comments: 28 pages, 8 figures, 1 table

Solving continuum and rarefied flows using differentiable programming

Authors: Tianbai Xiao

Abstract: Accurate and efficient prediction of multi-scale flows remains a formidable challenge. Constructing theoretical models and numerical methods often involves the design and optimization of parameters. While gradient descent methods have been mainly manifested to shine in the wave of deep learning, composable automatic differentiation can advance scientific computing where the application of classica… ▽ More Accurate and efficient prediction of multi-scale flows remains a formidable challenge. Constructing theoretical models and numerical methods often involves the design and optimization of parameters. While gradient descent methods have been mainly manifested to shine in the wave of deep learning, composable automatic differentiation can advance scientific computing where the application of classical adjoint methods alone is infeasible or cumbersome. Differentiable programming provides a novel paradigm that unifies data structures and control flows and facilitates gradient-based optimization of parameters in a computer program. This paper addresses the notion and implementation of the first solution algorithm for multi-scale flow physics across continuum and rarefied regimes based on differentiable programming. The fully differentiable simulator provides a unified framework for the convergence of computational fluid dynamics and machine learning, i.e., scientific machine learning. Specifically, parameterized mechanical-neural flow models and numerical methods can be constructed for forward physical processes, while the parameters can be trained on the fly with the help of the gradients that are taken through the backward passes of the whole simulation program, a.k.a., end-to-end optimization. As a result, versatile data-driven modeling and simulation can be achieved for physics discovery, surrogate modeling, and simulation acceleration. The fundamentals and implementation of the solution algorithm are demonstrated in detail. Numerical experiments, including forward and inverse problems for hydrodynamic and kinetic equations, are presented to demonstrate the performance of the numerical method. The open-source codes to reproduce the numerical results are available under the MIT license. △ Less

Submitted 6 February, 2026; v1 submitted 23 January, 2025; originally announced January 2025.

Comments: Published in Journal of Computational Physics, Vol. 539 (2025), 114224. DOI: 10.1016/j.jcp.2025.114224

Journal ref: Journal of Computational Physics, 539 (2025) 114224

Chirality transfer from chiral perovskite to molecular dopants via charge transfer states

Authors: Guan-Lin Chen, Hsinhan Tsai, Aaron Forde, Kai-Wei Tseng, Zhe-Yu Liu, Chi-An Dai, Tong Xiao, Mircea Coltlet, Leeyih Wang, Sergei Tretiak, Wanyi Nie

Abstract: Chiral perovskites are emerging semiconducting materials with broken symmetry that can selectively absorb and emit circularly polarized light. However, most of the chiral perovskites are typically low-dimensional structures with limited electrical conductivity and their light absorption occurs in the UV region. In this work, we find doping 2,3,5,6-Tetrafluoro-7,7,8,8-tetracyanoquinodimethane (F4TC… ▽ More Chiral perovskites are emerging semiconducting materials with broken symmetry that can selectively absorb and emit circularly polarized light. However, most of the chiral perovskites are typically low-dimensional structures with limited electrical conductivity and their light absorption occurs in the UV region. In this work, we find doping 2,3,5,6-Tetrafluoro-7,7,8,8-tetracyanoquinodimethane (F4TCNQ) in the chiral perovskite matrix can improve the electrical conductivity with an addition of visible light absorption through the emerging charge-transfer electronic states. The new absorption feature exhibits strong circular dichroism adapted from the chiral matrix, which is indicative of a chirality transfer from the host to the guest via an electronic coupling. The charge transfer state is validated by transient absorption spectroscopy and theory modeling. Quantum-chemical modeling identifies a strong wave function overlap between an electron and a hole of the guest-host in a closely packed crystal configuration forming the charge-transfer absorption state. We then integrate the doped chiral perovskite film in photodetectors and demonstrate a selective detection of circularly polarized light both in the UV and visible range. Our results suggest a universal approach of introducing visible photo absorption states to the chiral matrix to broaden the optical active range and enhance the conductivity. △ Less

Submitted 15 January, 2025; originally announced January 2025.

Manipulating the symmetry of photon-dressed electronic states

Authors: Changhua Bao, Michael Schüler, Teng Xiao, Fei Wang, Haoyuan Zhong, Tianyun Lin, Xuanxi Cai, Tianshuang Sheng, Xiao Tang, Hongyun Zhang, Pu Yu, Zhiyuan Sun, Wenhui Duan, Shuyun Zhou

Abstract: Strong light-matter interaction provides opportunities for tailoring the physical properties of quantum materials on the ultrafast timescale by forming photon-dressed electronic states, i.e., Floquet-Bloch states. While the light field can in principle imprint its symmetry properties onto the photon-dressed electronic states, so far, how to experimentally detect and further engineer the symmetry o… ▽ More Strong light-matter interaction provides opportunities for tailoring the physical properties of quantum materials on the ultrafast timescale by forming photon-dressed electronic states, i.e., Floquet-Bloch states. While the light field can in principle imprint its symmetry properties onto the photon-dressed electronic states, so far, how to experimentally detect and further engineer the symmetry of photon-dressed electronic states remains elusive. Here by utilizing time- and angle-resolved photoemission spectroscopy (TrARPES) with polarization-dependent study, we directly visualize the parity symmetry of Floquet-Bloch states in black phosphorus. The photon-dressed sideband exhibits opposite photoemission intensity to the valence band at the $Γ$ point,suggesting a switch of the parity induced by the light field. Moreover, a "hot spot" with strong intensity confined near $Γ$ is observed, indicating a momentum-dependent modulation beyond the parity switch. Combining with theoretical calculations, we reveal the light-induced engineering of the wave function of the Floquet-Bloch states as a result of the hybridization between the conduction and valence bands with opposite parities, and show that the "hot spot" is intrinsically dictated by the symmetry properties of black phosphorus. Our work suggests TrARPES as a direct probe for the parity of the photon-dressed electronic states with energy- and momentum-resolved information, providing an example for engineering the wave function and symmetry of such photon-dressed electronic states via Floquet engineering. △ Less

Submitted 9 December, 2024; originally announced December 2024.

Journal ref: Nature Communications 15, 10535 (2024)

Investigation and optimization of the deconvolution method for PMT waveform reconstruction

Authors: Jingzhe Tang, Tianying Xiao, Xuan Tang, Yongbo Huang

Abstract: Photomultiplier tubes (PMTs) are extensively employed as photosensors in neutrino and dark matter detection. The precise charge and timing information extracted from the PMT waveform plays a crucial role in energy and vertex reconstruction. In this study, we investigate the deconvolution algorithm utilized for PMT waveform reconstruction, while enhancing the timing separation ability for pile-up h… ▽ More Photomultiplier tubes (PMTs) are extensively employed as photosensors in neutrino and dark matter detection. The precise charge and timing information extracted from the PMT waveform plays a crucial role in energy and vertex reconstruction. In this study, we investigate the deconvolution algorithm utilized for PMT waveform reconstruction, while enhancing the timing separation ability for pile-up hits by redesigning filters based on the time-frequency uncertainty principle. This filter design sacrifices signal-to-noise ratio (SNR) to achieve narrower pulse widths. Furthermore, we optimize the selection of signal pulses in the case of low SNR based on Short-Time Fourier Transform (STFT). Monte Carlo data confirms that our optimization yields enhanced reconstruction performance: improving timing separation ability for pile-up hits from $7\sim10$~ns to $3\sim5$~ns, while controlling the residual nonlinearity of charge reconstruction to about 1\% in the range of 0 to 20 photoelectrons. △ Less

Submitted 13 February, 2025; v1 submitted 12 November, 2024; originally announced November 2024.

Accelerate Coastal Ocean Circulation Model with AI Surrogate

Authors: Zelin Xu, Jie Ren, Yupu Zhang, Jose Maria Gonzalez Ondina, Maitane Olabarrieta, Tingsong Xiao, Wenchong He, Zibo Liu, Shigang Chen, Kaleb Smith, Zhe Jiang

Abstract: Nearly 900 million people live in low-lying coastal zones around the world and bear the brunt of impacts from more frequent and severe hurricanes and storm surges. Oceanographers simulate ocean current circulation along the coasts to develop early warning systems that save lives and prevent loss and damage to property from coastal hazards. Traditionally, such simulations are conducted using coasta… ▽ More Nearly 900 million people live in low-lying coastal zones around the world and bear the brunt of impacts from more frequent and severe hurricanes and storm surges. Oceanographers simulate ocean current circulation along the coasts to develop early warning systems that save lives and prevent loss and damage to property from coastal hazards. Traditionally, such simulations are conducted using coastal ocean circulation models such as the Regional Ocean Modeling System (ROMS), which usually runs on an HPC cluster with multiple CPU cores. However, the process is time-consuming and energy expensive. While coarse-grained ROMS simulations offer faster alternatives, they sacrifice detail and accuracy, particularly in complex coastal environments. Recent advances in deep learning and GPU architecture have enabled the development of faster AI (neural network) surrogates. This paper introduces an AI surrogate based on a 4D Swin Transformer to simulate coastal tidal wave propagation in an estuary for both hindcast and forecast (up to 12 days). Our approach not only accelerates simulations but also incorporates a physics-based constraint to detect and correct inaccurate results, ensuring reliability while minimizing manual intervention. We develop a fully GPU-accelerated workflow, optimizing the model training and inference pipeline on NVIDIA DGX-2 A100 GPUs. Our experiments demonstrate that our AI surrogate reduces the time cost of 12-day forecasting of traditional ROMS simulations from 9,908 seconds (on 512 CPU cores) to 22 seconds (on one A100 GPU), achieving over 450$\times$ speedup while maintaining high-quality simulation results. This work contributes to oceanographic modeling by offering a fast, accurate, and physically consistent alternative to traditional simulation models, particularly for real-time forecasting in rapid disaster response. △ Less

Submitted 14 April, 2025; v1 submitted 18 October, 2024; originally announced October 2024.

Comments: IPDPS 2025

Minutes-scale Schr{ö}dinger-cat state of spin-5/2 atoms

Authors: Y. A. Yang, W. -T. Luo, J. -L. Zhang, S. -Z. Wang, Chang-Ling Zou, T. Xia, Z. -T. Lu

Abstract: Quantum metrology with nonclassical states offers a promising route to improved precision in physical measurements. The quantum effects of Schr{ö}dinger-cat superpositions or entanglements allow measurement uncertainties to reach below the standard quantum limit. However, the challenge in keeping a long coherence time for such nonclassical states often prevents full exploitation of the quantum adv… ▽ More Quantum metrology with nonclassical states offers a promising route to improved precision in physical measurements. The quantum effects of Schr{ö}dinger-cat superpositions or entanglements allow measurement uncertainties to reach below the standard quantum limit. However, the challenge in keeping a long coherence time for such nonclassical states often prevents full exploitation of the quantum advantage in metrology. Here we demonstrate a long-lived Schr{ö}dinger-cat state of optically trapped $^{173}$Yb (\textit{I}\ =\ 5/2) atoms. The cat state, a superposition of two oppositely-directed and furthest-apart spin states, is generated by a non-linear spin rotation. Protected in a decoherence-free subspace against inhomogeneous light shifts of an optical lattice, the cat state achieves a coherence time of $1.4(1)\times 10^3$ s. A magnetic field is measured with Ramsey interferometry, demonstrating a scheme of Heisenberg-limited metrology for atomic magnetometry, quantum information processing, and searching for new physics beyond the Standard Model. △ Less

Submitted 11 October, 2024; originally announced October 2024.

Theoretical Study of Inhomogeneity Effects on Three-Wave Parametric Instability: A WKBJ Approach

Authors: Taotao Zhou, Nong Xiang, Chunyun Gan, Tianyang Xia

Abstract: The mechanisms by which media inhomogeneity affects the three wave parametric instability (PI), including the wave number mismatch and the parameter gradients, are investigated using an approach based on the Wentzel-Kramers-Brillouin-Jeffreys (WKBJ) approximation. This approach transforms the coupling wave equations into an amplitude equation and iteratively solves its characteristic polynomials.… ▽ More The mechanisms by which media inhomogeneity affects the three wave parametric instability (PI), including the wave number mismatch and the parameter gradients, are investigated using an approach based on the Wentzel-Kramers-Brillouin-Jeffreys (WKBJ) approximation. This approach transforms the coupling wave equations into an amplitude equation and iteratively solves its characteristic polynomials. By analyzing the solutions, we proposed that the wave number of the quasi-mode, a key term in the wave number mismatch of non-resonant type PI, should be a complex root of the quasi-mode's linear dispersion equation. Based on this, we derive a unified amplification factor formula that covers the resonant and non-resonant, the forward-scattered and backward-scattered types of PI. The impact of parameter gradients on the local spatial growth rate becomes significant when the inhomogeneity exceeds 10^{-3}. Considering parameter gradients extends our approach's validity to an inhomogeneity of about 10^{-2}. This approach holds promise for more specific PI modeling in the future. △ Less

Submitted 10 September, 2024; originally announced September 2024.

Comments: 33 pages, 5 figures, preprint version

Logarithmic Finite-Size Scaling of the Four-Dimensional Ising Model

Authors: Zhiyi Li, Tianning Xiao, Zongzheng Zhou, Sheng Fang, Youjin Deng

Abstract: Field-theoretical calculations predict that, at the upper critical dimension $d_c=4$, the finite-size scaling (FSS) behaviors of the Ising model would be modified by multiplicative logarithmic corrections with thermal and magnetic correction exponents $(\hat{y}_t, \hat{y}_h)=(1/6,1/4)$. Using high-efficient cluster algorithms and the lifted worm algorithm, we present a systematic study of the FSS… ▽ More Field-theoretical calculations predict that, at the upper critical dimension $d_c=4$, the finite-size scaling (FSS) behaviors of the Ising model would be modified by multiplicative logarithmic corrections with thermal and magnetic correction exponents $(\hat{y}_t, \hat{y}_h)=(1/6,1/4)$. Using high-efficient cluster algorithms and the lifted worm algorithm, we present a systematic study of the FSS of the four-dimensional Ising model in the Fortuin-Kasteleyn (FK) bond and loop representations. Our numerical results reveal the FSS behaviors of various geometric and physical quantities in the three representations, offering robust evidence for the logarithmic correction form conjectured by the field theory. In particular, clear evidence is obtained for the existence of $\hat{y}_t=1/6$ in the loop representation, while it is difficult to extract in the spin representations, because of mixing with the Gaussian-fixed-point asymptotics. In the FK-bond representation, the multiplicative logarithmic correction for the second-largest cluster is also numerically observed to be governed by an exponent $\hat{y}_{h2} = -1/4$ with its exact value unknown yet. △ Less

Submitted 31 October, 2024; v1 submitted 27 August, 2024; originally announced August 2024.

Comments: 7 pages, 3 figures

Journal ref: Physical Review E110,064139(2024)

Theoretical and Global Simulation Analysis of Collisional Microtearing

Authors: Kaixuan Fan, Xue-Qiao Xu, Ben Zhu, Chao Dong, Tianyang Xia, Zeyu Li

Abstract: This study delves into Microtearing Modes (MTMs) in tokamak plasmas, employing advanced simulations within the BOUT++ framework. The research, centering on collisional MTMs influenced by the time-dependent thermal force, enhances our understanding of plasma dynamics. It achieves this through the simplification and linearization of control equations in detailed linear simulations. The study meticul… ▽ More This study delves into Microtearing Modes (MTMs) in tokamak plasmas, employing advanced simulations within the BOUT++ framework. The research, centering on collisional MTMs influenced by the time-dependent thermal force, enhances our understanding of plasma dynamics. It achieves this through the simplification and linearization of control equations in detailed linear simulations. The study meticulously evaluates various conductivity models, including those proposed by Larakers, Drake, and Hassam, under diverse plasma conditions and collision regimes. A notable achievement of this research is the derivation of a unified dispersion relation that encompasses both MTM and Drift-Alfven Wave (DAW) instabilities. It interestingly reveals that DAW and MTM exhibit instability at different proximities to the rational surface. Specifically, MTMs become unstable near the rational surface but stabilize farther away, whereas the drift-Alfven instability manifests away from the rational surface. Further, the study re-derives MTM dispersion relations based on Ohm's law and the vorticity equation, providing a thorough analysis of electromagnetic and electrostatic interactions in tokamaks. Global simulations demonstrate an inverse correlation between MTM growth rates and collisionality, and a direct correlation with temperature gradients. The nonalignment of the rational surface with the peak of electron local diamagnetic frequency stabilizes the MTMs. Nonlinear simulations highlight electron temperature relaxation as the primary saturation mechanism for MTMs, with magnetic flutter identified as the dominant mode of electron thermal transport. △ Less

Submitted 11 April, 2024; originally announced April 2024.

Comments: 31 pages, 13 figures

Realization of a three-dimensional photonic higher-order topological insulator

Authors: Ziyao Wang, Yan Meng, Bei Yan, Dong Zhao, Linyun Yang, Jing-Ming Chen, Min-Qi Cheng, Tao Xiao, Perry Ping Shum, Gui-Geng Liu, Yihao Yang, Hongsheng Chen, Xiang Xi, Zhen-Xiao Zhu, Biye Xie, Zhen Gao

Abstract: The discovery of photonic higher-order topological insulators (HOTIs) has significantly expanded our understanding of band topology and provided unprecedented lower-dimensional topological boundary states for robust photonic devices. However, due to the vectorial and leaky nature of electromagnetic waves, it is challenging to discover three-dimensional (3D) topological photonic systems and photoni… ▽ More The discovery of photonic higher-order topological insulators (HOTIs) has significantly expanded our understanding of band topology and provided unprecedented lower-dimensional topological boundary states for robust photonic devices. However, due to the vectorial and leaky nature of electromagnetic waves, it is challenging to discover three-dimensional (3D) topological photonic systems and photonic HOTIs have so far still been limited to two dimensions (2D). Here, we report on the first experimental realization of a 3D Wannier-type photonic HOTI in a tight-binding-like metal-cage photonic crystal, whose band structure matches well with that of a 3D tight-binding model due to the confined Mie resonances. By microwave near-field measurements, we directly observe coexisting topological surface, hinge, and corner states in a single 3D photonic HOTI, as predicted by the tight-binding model and simulation results. Moreover, we demonstrate that all-order topological boundary states are self-guided even in the light cone continuum and can be exposed to air without ancillary cladding, making them well-suited for practical applications. Our work thus opens routes to the multi-dimensional robust manipulation of electromagnetic waves at the outer surfaces of 3D cladding-free photonic bandgap materials and may find novel applications in 3D topological integrated photonics devices. △ Less

Submitted 8 April, 2024; originally announced April 2024.

Comments: 23 pages,4 figures

Effects of wave parameters on load reduction performance for amphibious aircraft with V-hydrofoil

Authors: Yujin Lu, Shuanghou Deng, Yuanhang Chen, Tianhang Xiao, Jichang Chen, Fan Liu, Sichen Song, Bin Wu

Abstract: An investigation of the influence of the hydrofoil on load reduction performance during an amphibious aircraft landing on still and wavy water is conducted by solving the Unsteady Reynolds-Averaged Navier-Stokes equations coupled with the standard $k-ω$ turbulence model in this paper. During the simulations, the numerical wave tank is realized by using the velocity-inlet boundary wave maker couple… ▽ More An investigation of the influence of the hydrofoil on load reduction performance during an amphibious aircraft landing on still and wavy water is conducted by solving the Unsteady Reynolds-Averaged Navier-Stokes equations coupled with the standard $k-ω$ turbulence model in this paper. During the simulations, the numerical wave tank is realized by using the velocity-inlet boundary wave maker coupled with damping wave elimination technique on the outlet, while the volume of fluid model is employed to track the water-air interface. Subsequently, the effects of geometric parameters of hydrofoil have been first discussed on still water, which indicates the primary factor influencing the load reduction is the static load coefficient of hydrofoil. Furthermore, the effects of descent velocity, wave length and wave height on load reduction are comprehensively investigated. The results show that the vertical load reduces more than 55$\%$ at the early stage of landing on the still water through assembling the hydrofoil for different descent velocity cases. Meanwhile, for the amphibious aircraft with high forward velocity, the bottom of the fuselage will come into close contact with the first wave when landing on crest position, and then the forebody will impact the next wave surface with extreme force. In this circumstance, the load reduction rate decreases to around 30$\%$, which will entail a further decline with the increase of wave length or wave height. △ Less

Submitted 11 November, 2023; originally announced November 2023.

Microstructure and structural modulation of lutetium dihydride LuH2 as seen via transmission electron microscopy

Authors: Xiao-Ping Ma, Ning-Ning Wang, Wen-Tao Wang, Jing-Zhe Nie, Wen-Li Gao, Shuai-Shuai Sun, Jun Li, Huan-Fang Tian, Tian-Long Xia, Jin-Guang Cheng, Jian-Qi Li, Huai-Xin Yang

Abstract: Structural investigations conducted using transmission electron microscopy (TEM) on LuH2 synthesized under atmospheric pressure (AP-LuH2) and nitrogen-doped LuH2 synthesized under high pressure (HP-LuH2) have revealed numerous microstructural phenomena. Both materials show a clear superstructure modulation with wave vector, q^* = 1/4 (2-20), and this modulation can be well interpreted by the displ… ▽ More Structural investigations conducted using transmission electron microscopy (TEM) on LuH2 synthesized under atmospheric pressure (AP-LuH2) and nitrogen-doped LuH2 synthesized under high pressure (HP-LuH2) have revealed numerous microstructural phenomena. Both materials show a clear superstructure modulation with wave vector, q^* = 1/4 (2-20), and this modulation can be well interpreted by the displacements of Lu atoms. Further investigations on the nitrogen-doped HP-LuH2 materials reveal the appearance of high-density antiphase boundaries, in particular, domain walls of a few atomic layer thickness without structural modulation can be observed, suggesting possible interface properties could be detected in this system. In-situ TEM observations of AP-LuH2 suggest that no evident structural phase transition occurs between 94 K and 673 K. △ Less

Submitted 26 September, 2023; originally announced September 2023.

Comments: 8 pages, 7 figures

Observation of Hybrid-Order Topological Pump in a Kekule-Textured Graphene Lattice

Authors: Tianzhi Xia, Yuzeng Li, Qicheng Zhang, Xiying Fan, Meng Xiao, Chunyin Qiu

Abstract: Thouless charge pumping protocol provides an effective route for realizing topological particle transport. To date, the first-order and higher-order topological pumps, exhibiting transitions of edge-bulk-edge and corner-bulk-corner states, respectively, are observed in a variety of experimental platforms. Here, we propose a concept of hybrid-order topological pump, which involves a transition of b… ▽ More Thouless charge pumping protocol provides an effective route for realizing topological particle transport. To date, the first-order and higher-order topological pumps, exhibiting transitions of edge-bulk-edge and corner-bulk-corner states, respectively, are observed in a variety of experimental platforms. Here, we propose a concept of hybrid-order topological pump, which involves a transition of bulk, edge, and corner states simultaneously. More specifically, we consider a Kekulé-textured graphene lattice that features a tunable phase parameter. The finite sample of zigzag boundaries, where the corner configuration is abnormal and inaccessible by repeating unit cells, hosts topological responses at both the edges and corners. The former is protected by a nonzero winding number, while the latter can be explained by a nontrivial vector Chern number. Using our skillful acoustic experiments, we verify those nontrivial boundary landmarks and visualize the consequent hybrid-order topological pump process directly. This work deepens our understanding to higher-order topological phases and broadens the scope of topological pumps. △ Less

Submitted 7 September, 2023; originally announced September 2023.

Comments: 5 figures

Ultrafast Radiographic Imaging and Tracking: An overview of instruments, methods, data, and applications

Authors: Zhehui Wang, Andrew F. T. Leong, Angelo Dragone, Arianna E. Gleason, Rafael Ballabriga, Christopher Campbell, Michael Campbell, Samuel J. Clark, Cinzia Da Vià, Dana M. Dattelbaum, Marcel Demarteau, Lorenzo Fabris, Kamel Fezzaa, Eric R. Fossum, Sol M. Gruner, Todd Hufnagel, Xiaolu Ju, Ke Li, Xavier Llopart, Bratislav Lukić, Alexander Rack, Joseph Strehlow, Audrey C. Therrien, Julia Thom-Levy, Feixiang Wang , et al. (3 additional authors not shown)

Abstract: Ultrafast radiographic imaging and tracking (U-RadIT) use state-of-the-art ionizing particle and light sources to experimentally study sub-nanosecond dynamic processes in physics, chemistry, biology, geology, materials science and other fields. These processes, fundamental to nuclear fusion energy, advanced manufacturing, green transportation and others, often involve one mole or more atoms, and t… ▽ More Ultrafast radiographic imaging and tracking (U-RadIT) use state-of-the-art ionizing particle and light sources to experimentally study sub-nanosecond dynamic processes in physics, chemistry, biology, geology, materials science and other fields. These processes, fundamental to nuclear fusion energy, advanced manufacturing, green transportation and others, often involve one mole or more atoms, and thus are challenging to compute by using the first principles of quantum physics or other forward models. One of the central problems in U-RadIT is to optimize information yield through, e.g. high-luminosity X-ray and particle sources, efficient imaging and tracking detectors, novel methods to collect data, and large-bandwidth online and offline data processing, regulated by the underlying physics, statistics, and computing power. We review and highlight recent progress in: a.) Detectors; b.) U-RadIT modalities; c.) Data and algorithms; and d.) Applications. Hardware-centric approaches to U-RadIT optimization are constrained by detector material properties, low signal-to-noise ratio, high cost and long development cycles of critical hardware components such as ASICs. Interpretation of experimental data, including comparisons with forward models, is frequently hindered by sparse measurements, model and measurement uncertainties, and noise. Alternatively, U-RadIT make increasing use of data science and machine learning algorithms, including experimental implementations of compressed sensing. Machine learning and artificial intelligence approaches, refined by physics and materials information, may also contribute significantly to data interpretation, uncertainty quantification, and U-RadIT optimization. △ Less

Submitted 4 September, 2023; v1 submitted 21 August, 2023; originally announced August 2023.

Comments: 52 pages, 32 figures; Overview of ultrafast radiographic imaging and tracking as a part of ULITIMA 2023 conference, Mar. 13-16,2023, Menlo Park, CA, USA

Report number: Los Alamos Report number LA-UR-23-29338

Journal ref: Nuclear Inst. and Methods in Physics Research, A 1057 (2023) 168690

Hydrogen isotope separation using graphene-based membranes in liquid water

Authors: Xiangrui Zhang, Hequn Wang, Tiantian Xiao, Xiaoyi Chen, Wen Li, Yihan Xu, Jianlong Lin, Zhe Wang, Hailin Peng, Sheng Zhang

Abstract: Hydrogen isotope separation has been effectively achieved using gaseous H2/D2 filtered through graphene/Nafion composite membranes. Nevertheless, deuteron nearly does not exist in the form of gaseous D2 in nature but in liquid water. Thus, it is a more feasible way to separate and enrich deuterium from water. Herein we have successfully transferred monolayer graphene to a rigid and porous polymer… ▽ More Hydrogen isotope separation has been effectively achieved using gaseous H2/D2 filtered through graphene/Nafion composite membranes. Nevertheless, deuteron nearly does not exist in the form of gaseous D2 in nature but in liquid water. Thus, it is a more feasible way to separate and enrich deuterium from water. Herein we have successfully transferred monolayer graphene to a rigid and porous polymer substrate PITEM (polyimide tracked film), which could avoid the swelling problem of the Nafion substrate, as well as keep the integrity of graphene. Meanwhile, defects in large area of CVD graphene could be successfully repaired by interfacial polymerization resulting in high separation factor. Moreover, a new model was proposed for the proton transport mechanism through monolayer graphene based on the kinetic isotope effect (KIE). In this model, graphene plays the significant role in the H/D separation process by completely breaking the O-H/O-D bond, which can maximize the KIE leading to prompted H/D separation performance. This work suggests a promising application of using monolayer graphene in industry and proposes a pronounced understanding of proton transport in graphene △ Less

Submitted 25 December, 2022; originally announced December 2022.

Comments: 10 pages, 4 figures (6pages, 6figures for SI)

Place & Play SERS: sample collection and preparation-free surface-enhanced Raman spectroscopy

Authors: Yasutaka Kitahama, Pablo Martinez Pancorbo, Hiroki Segawa, Machiko Marumi, Ting-Hui Xiao, Kotaro Hiramatsu, William Yang, Keisuke Goda

Abstract: The ability to perform sensitive, real-time, in situ, multiplex chemical analysis is indispensable for diverse applications such as human health monitoring, food safety testing, forensic analysis, environmental sensing, and homeland security. Surface-enhanced Raman spectroscopy (SERS) is an effective tool to offer the ability by virtue of its high sensitivity and rapid label-free signal detection… ▽ More The ability to perform sensitive, real-time, in situ, multiplex chemical analysis is indispensable for diverse applications such as human health monitoring, food safety testing, forensic analysis, environmental sensing, and homeland security. Surface-enhanced Raman spectroscopy (SERS) is an effective tool to offer the ability by virtue of its high sensitivity and rapid label-free signal detection as well as the availability of portable Raman spectrometers. Unfortunately, the practical utility of SERS is limited because it generally requires sample collection and preparation, namely, collecting a sample from an object of interest and placing the sample on top of a SERS substrate to perform a SERS measurement. In fact, not all analytes can satisfy this requirement because the sample collection and preparation process may be undesirable, laborious, difficult, dangerous, costly, or time-consuming. Here we introduce "Place & Play SERS" based on an ultrathin, flexible, stretchable, adhesive, biointegratable gold-deposited polyvinyl alcohol (PVA) nanomesh substrate that enables placing the substrate on top of an object of interest and performing a SERS measurement of the object by epi-excitation without the need for touching, destroying, and sampling it. Specifically, we characterized the sensitivity of the gold/PVA nanomesh substrate in the Place & Play SERS measurement scheme and then used the scheme to conduct SERS measurements of both wet and dry objects under nearly real-world conditions. To show the practical utility of Place & Play SERS, we demonstrated two examples of its application: food safety testing and forensic analysis. Our results firmly verified the new measurement scheme of SERS and are expected to extend the potential of SERS by opening up untapped applications of sensitive, real-time, in situ multiplex chemical analysis. △ Less

Submitted 5 February, 2023; v1 submitted 24 December, 2022; originally announced December 2022.

Comments: 12 pages, 7 figures