Plasma Physics
Observation of stopping power reduction at strong ion-plasma coupling
Yun Liu, Jieru Ren, Zhigang Deng et al. (+30 more)
Ion stopping in dense
plasma is crucial for
stellar evolution and fusion ignition. However, its behavior in the strong ion-
plasma coupling regime beyond the linear limit has long remained elusive, due to formidable experimental challenges. Here we report the first experimental investigation of ion stopping at an unprecedented coupling parameter exceeding unity, achieved by sending
laser-accelerated short-pulse and intense quasi-monoenergetic carbon ions ($\sim$583 keV/u, C$^{5+}$) into a uniform, long-lived, well-characterized dense
plasma target ($T_e$ $\approx$ 17 eV, $n_e$ $\approx$ 4$\times$10$^{20}$ cm$^{-3}$). By simultaneously measuring ion energy loss and charge-state
evolution, we eliminated key experimental ambiguities arising from charge-state determination. Our results clearly show a reduction in stopping power compared with predictions from standard linear dielectric response or binary collision models, and they agree well with the hybrid calculation of molecular dynamics with
quantum corrections. The importance of nonlinear screening effects arising from many-body interactions and
quantum effects due to the wave nature of electrons was demonstrated at strong coupling. This work establishes a definitive high-fidelity experimental
benchmark for collisional dynamics in the strong-coupling regime. It offers critical insight for accurate modeling of energy transport in inertial confinement fusion and astrophysical
plasmas.
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All authors Yun Liu, Jieru Ren, Zhigang Deng, Wei Qi, Bubo Ma, Wenqing Wei, Shizheng Zhang, Xuyang Luo, Ziqian Zhao, Mingzhe Yang, Yifang Gao, Xueguang Ren, Jianxing Li, Dieter H. H. Hoffmann, Xing Wang, Zhongfeng Xu, Shaoyi Wang, Quanping Fan, Bo Cui, Weiwu Wang, Sixin Wu, Yue Yang, Zhurong Cao, Zongqing Zhao, Yuqiu Gu, Leifeng Cao, Bin He, Shaoping Zhu, Olga Rosmej, Rui Cheng, Guoqing Xiao, Weimin Zhou, Yongtao Zhao
Medical Physics
A Positron Range Correction with Texture Preservation Framework in PET Imaging
Nerea Encina-Baranda, Yifan Zheng, Jorge Cabello et al. (+5 more)
Positron range (PR) blurring is a fundamental resolution limitation in PET imaging with high-energy positron emitters such as 82Rb, causing contrast loss and spill-out effects across heterogeneous tissue interfaces. We propose PRC-TP, a positron range correction (PRC) framework with explicit texture preservation that decouples deterministic resolution recovery from
stochastic texture restoration. A nnFormer-based neural network (NN) was trained on patient-derived Monte Carlo simulations to map PR-degraded 82Rb reconstructions to PR-free references using attenuation maps as anatomical context. However, this NN also significantly removed the noise in the images, which could impact some texture analysis methods or make the images look unrealistic. An auxiliary Noise2Noise model estimates that smoothing effect, enabling texture extraction and transfer to the PR-corrected prediction through Model-consistent Texture Re-Injection (MTRI). In simulated patients, PRC-TP preserved contrast recovery close to ground truth (GT) (98.96-99.04%) while restoring noise and CNR closer to the reference. The function-based MTRI formulation achieved near unity global texture amplitude agreement with GT (0.997 +/- 0.011), reducing the input texture amplitude bias (0.951 +/- 0.011). Radiomics analysis showed improved agreement with GT across texture-sensitive feature families. A clinical 82Rb evaluation showed trends consistent with simulations, including comparable contrast-ratio increase (10.18% vs. 10.99%) and restoration of texture suppressed by PRC. These results support PRC-TP as a practical framework for resolution recovery with acquisition-consistent texture preservation in PET imaging. Submitted to IEEE TRPMS.
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All authors Nerea Encina-Baranda, Yifan Zheng, Jorge Cabello, Robert. J. Paneque-Yunta, Cindy. M. Solano-Cordero, Alejandro Lopez-Montes, Maurizio Conti, Joaquin. L. Herraiz
Chemical Physics
Local and Charge-Transfer Excitation of Pentacene-Buckminsterfullerene complexes
Ala Aldin M.Hani M. Darghouth, Omar A.Shareef, Firas A. AL-Lolage et al. (+1 more)
The charge transfer state, the local excited state on pentacene, and the local excited state on buckminsterfullerene have been studied for four models of the pentacene-buckminsterfullerene organic
solar cell. These models have different interface configurations between the donor and the acceptor. The study has been done by using different functionals and time-dependent density functional theory-namely, the long range-separated hybrid with coulomb-attenuating method approach (CAM-B3LYP functional), the popular B3LYP (Becke, three-parameter, Lee- Yang-Parr) exchange-correlation functional, and the density functional tight binding (DFTB) method. The charge transfer state energy obtained by using CAM-B3LYP without optimally tuned range-separated hybrid parameters are very close to those obtained by using a many-body dispersion-corrected, optimally tuned range-separated hybrid functional (OPT-wB97XD). Both the B3LYP functional and the DFTB method fail to describe correctly the charge transfer energy for all models. Each of them is underestimating around 1 eV compared with range-separated hybrid functional.
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All authors Ala Aldin M.Hani M. Darghouth, Omar A.Shareef, Firas A. AL-Lolage, Mark E. Casida
Fluid Dynamics
Non-normal weakly nonlinear analysis: asymptotic consistency and non-universality
Matthew McCormack, Gregory P. Chini and Rich R. Kerswell
Non-normality can induce large transient growth in linearly stable systems. Determining whether this growth triggers a transition in the underlying nonlinear system, however, requires understanding the interaction between non-normality and nonlinearity. Here, we develop a weakly nonlinear theory for linearly-stable, non-normal systems subject to harmonic forcing, enabling a systematic analysis of this interaction. Following Ducimetière et al. (J. Fluid Mech., vol. 947, 2022, A43), we define a formal small parameter $\varepsilon$ as the reciprocal of the system's maximum linear amplification. However, we ensure asymptotic consistency by providing a framework that naturally adapts to the underlying structure of the system. The approach is applied to a harmonically forced channel flow and to a two-dimensional model mimicking the structure of the Orr-Sommerfeld-Squire equations. Unlike classical weakly nonlinear analysis near bifurcation points, the resulting amplitude equations are non-universal. In fact, a single linear mode amplified by the non-normality can nonlinearly excite a multi-modal and multi-frequency response at leading-order, which is system- or even regime-specific. Nevertheless, the method yields asymptotically consistent amplitude equations that capture this complexity provided a limit in which $\varepsilon\rightarrow0$ can be identified. As the forcing amplitude increases, the reduced equations capture stable nonlinear states emerging from the laminar flow, their subsequent bifurcations, and their eventual collision with the boundary of their basin of attraction. Thus, the amplitude equations can capture subcritical transitions driven by forcing and varied initial conditions and enable the identification of critical parameters beyond which no stable weakly nonlinear state exists.
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Applied Physics
Physics-governed executable modelling of triboelectric nanogenerators
Hongfa Zhao, Baiqiao Wang, Tiancong Zhao et al. (+7 more)
Predictive modelling of triboelectric nanogenerators (TENGs) remains fragmented across analytical theories, finite-geometry solvers and disconnected simulation workflows. These disparate approaches must be unified into an executable framework to advance quantitative TENG research.Here we introduce a charge-defined modelling framework and implement it as TENG-CLAW, a physics-governed platform for traceable TENG simulation. The framework establishes a self-consistent electrostatic hierarchy in which triboelectric charges, pre-charging charges and compensating electrode charges serve as defining state variables.This hierarchy connects the infinite plate analytical limit for near-uniform fields with finite-geometry numerical formulations required for edge-dominated devices. Built on this basis, TENG-CLAW converts user-defined research requests into physically admissible simulation tasks, so that generated outputs are tied to explicit charge states, boundary conditions, solver routes and reusable artifacts across spatial, temporal, field-level, comparative and reporting workflows. This work establishes a rigorous computational basis for interpreting TENG mechanisms and provides reproducible research infrastructure for simulation and physics-guided device design.
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All authors Hongfa Zhao, Baiqiao Wang, Tiancong Zhao, Chun Jin, Hanlin Zhou, Mingrui Shu, Minyi Xu, Liwei Lin, Wenbo Ding, Zhong Lin Wang
Optics
Photons in Media: A Second-Quantization Scheme Based on a Dirac-like Equation
Lili Yang, Longlong Feng and Pengming Zhang
We develop a second-quantization framework for
photons based on the optical Dirac equation of source-free Maxwell theory in generic media. In this formulation, the electromagnetic field is recast as a four-component spinor-like wave function that admits both positive-energy and negative-energy solutions, which are naturally interpreted as
photon and antiphoton states. By expanding the field in terms of single-
photon eigenmodes, we construct a consistent quantization scheme in which the
photon field operators obey bosonic commutation relations, in close analogy with the Dirac quantization of electrons. In structured media, the optical Dirac equation acquires effective mass and coupling terms induced by the dielectric tensor, analogous to an electronic Dirac-type structure. This allows
photon propagation in media to be interpreted in terms of boosted spinor states and provides a unified description of
vacuum and medium-modified dispersion relations. The framework further reveals a natural
quantum-mechanical origin of transverse
spin in structured electromagnetic fields, including evanescent waves, where
spin components perpendicular to the propagation direction emerge from the underlying helicity structure. In the context of optical Dirac theory, this work presents a
quantum field-theoretic description of
photons in both
vacuum and media, offering a new perspective on
photon quantization,
spin-orbit interaction, and light-matter coupling in structured optical systems.
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Accelerator Physics
Transverse Emittance and Emittance Measurements
Gero Kube
Transverse emittance is one of the central figures of merit for charged-particle beams because it connects the microscopic phase-space distribution to macroscopic accelerator performance. This report introduces the trace-space description of emittance, relates it to the Courant-Snyder formalism and the second-moment beam
matrix, and then follows the experimental logic behind common diagnostics. Emphasis is placed on how profile measurements, masks, drifts, quadrupole scans, and transverse deflecting structures convert otherwise inaccessible angular or slice information into measurable beam sizes.
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Accelerator Physics
Powder Spreading and Layer Deposition in Metal Powder Bed Fusion
Antonello Astarita
Powder spreading and layer deposition are fundamental stages of Powder Bed Fusion (PBF) technologies and play a critical role in determining process stability and final component quality. This chapter examines the mechanisms governing powder-bed formation, highlighting the interactions between powder characteristics, process parameters, and machine architecture. Particular
attention is devoted to the influence of particle size distribution, morphology, cohesion, flowability, layer thickness, recoater velocity, and environmental conditions on powder-bed quality. The resulting powder-bed is discussed as a process state variable whose characteristics, including packing density, surface coverage, effective layer thickness, and spatial homogeneity, directly affect energy absorption, melt-pool stability, defect formation, and mechanical performance. The chapter also reviews the application of the Discrete Element Method (DEM) for modelling powder spreading phenomena and quantifying powder-bed quality metrics. Finally, the role of powder reuse, lifecycle management, and future developments involving process monitoring, digital twins, and data-driven optimization strategies is discussed, emphasizing the growing importance of powder engineering in advanced metal additive manufacturing.
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Optics
Large-Area Patternable Solar-Powered Bistable Organic Crystalline Film for Nonlinear Optical Communication
Ankur Khapre, Avulu Vinod Kumar, Haseeba Nasreen Punathil et al. (+5 more)
Reversible control of
crystal symmetry offers a powerful route to programmable optical functionality. However, achieving solid-state bistability between centrosymmetric and non-centrosymmetric crystalline phases remains a formidable challenge; examples of materials that enable stable switching of second-order nonlinear optical (NLO) responses are exceptionally rare. Here we report a
solar-powered,
symmetry-bistable organic material based on the photoisomerizable molecule (E/Z)-2-(4-(4-bromophenyl)thiazol-2-yl)-3-(4- (dimethylamino)phenyl)acrylonitrile (E/Z-BTDPA). The crystallizable E- and Z-isomers adopt distinct molecular packing arrangements that reversibly toggle between these states, controlling second-order NLO activity. The E-form exhibits strong second-harmonic generation (SHG), whereas the Z-form is SHG-inactive and displays twophoton luminescence. This bistable behavior is retained in flexible thin films, where sunlight-driven photoisomerization enables reversible photoswitching of the second-order electric susceptibility (ḩi} 2), large-area optical patterning, and real-time NLO communication via waveform generation and text-string transcription at telecommunication wavelengths. This sustainable strategy bypasses rigid inorganic architectures, establishing photoinduced
symmetry bistability as a scalable paradigm for all-optical computing and advanced communication networks.
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All authors Ankur Khapre, Avulu Vinod Kumar, Haseeba Nasreen Punathil, Biswajit Kumar Barman, Bedanta Kumar Deka, Shilpa Mangalassery, Sri Ram G Naraharishetty, Rajadurai Chandrasekar
Chemical Physics
Reaction-Network-Level Discovery of Ammonia Synthesis Catalysts via Ten-Million-Scale Generative Exploration
Ruili Li, Rui Qi, Shuoqi Zhang et al. (+5 more)
Catalyst discovery for ammonia synthesis is inherently a reaction-network challenge because catalytic performance is governed not by a single adsorbed intermediate, but by a surface's orchestrated compatibility with multiple distinct intermediates across competing dissociative and associative pathways. However, navigating ultra-large chemical spaces under such multi-intermediate constraints remains a formidable bottleneck for conventional screening workflows. Here, we report a reaction-network-level catalyst discovery framework driven by ten-million-scale generative exploration. By coupling adsorbate-specific generative
Transformers with high-throughput machine learning potentials, we systematically map the structure-property landscapes of four critical intermediates (N*, NH*, NNH*, and HNNH*). Scale-dependent overlap analysis shows that the full four-intermediate compatibility space remains strongly under-sampled at conventional 105-106 generative scales, emerging exclusively under ten-million-scale exploration. By generating approximately 15 million configurations per adsorbate, followed by structural compression and machine-learning-potential predictions, we identified 279 highly potential target materials. This sparse compatibility space successfully recovers traditional Fe- and Ru-based motifs while uncovering previously unexplored catalyst families. Representative DFT calculations validate pathway-dependent mechanisms: Fe-V emerges as a dissociative-pathway lead by significantly lowering the initial N2 dissociation barrier, whereas Al-Pd-Zr efficiently stabilizes associative intermediates as an associative-pathway lead. These findings establish multi-intermediate reaction-network compatibility as a robust criterion for discovering advanced catalysts from multi-million generative chemical spaces.
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All authors Ruili Li, Rui Qi, Shuoqi Zhang, Qingli Tang, Qingqing Mao, Ritankar Das, Beien Zhu, Yi Gao
Optics
Chaos Generation and Control with Molecular Optomechanical System
Hui-Hui Xu, Jian-zhuang Wu, Lei-Bo Deng et al. (+2 more)
Chaos is central to secure communication and physical random-number generation. Conventional cavity-optomechanical implementations, however, usually rely on weak single-
photon optomechanical coupling and low-frequency mechanical modes, so access to deterministic chaotic dynamics often requires large driving power and careful suppression of thermal noise. Here we theoretically study a hybrid molecular optomechanical system formed by coupling a plasmonic nanocavity to a whispering-gallery-mode (WGM) microcavity. The plasmonic nanocavity provides terahertz-scale single-
photon optomechanical coupling to a molecular vibration, while the WGM resonator offers a low-loss photonic channel that mitigates the short plasmon lifetime. By integrating the semiclassical equations of motion and evaluating the largest Lyapunov exponent, we map the nonlinear dynamical regimes in the parameter spaces of WGM detuning, plasmon–WGM coupling, and plasmon–vibration optomechanical coupling. We show that increasing the plasmon–vibration coupling drives the system from self-sustained oscillations to chaos through a period-doubling cascade. At moderate coupling strengths, isolated chaos windows can be opened or closed by tuning the WGM detuning and the inter-cavity coupling. These results identify molecular optomechanics as a controllable room-temperature platform for on-chip chaotic light generation and random-signal applications.
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All authors Hui-Hui Xu, Jian-zhuang Wu, Lei-Bo Deng, E Wu, Yong-Hong Ma
Fluid Dynamics · Cross-listed from cond-mat.soft
Hydrodynamic Phase Separation and Morphological Evolution in Chiral Active-Passive Mixtures
Mayurakshi Deb and Rajesh Singh
The collective behavior of passive particles within
chiral active matter has emerged as a significant area of soft matter research. However, most existing studies focus on systems where chirality is imposed by external torques rather than intrinsic activity. In this work, we study emergent dynamics in a suspension of active spinners and passive colloids by computing many-body hydrodynamic interactions via Ewald summation. By systematically exploring a broad range of area fractions and rotational velocities, we identify distinct phase-separation regimes sensitive to the system's kinematic parameters. Specifically, we report the emergence of unique structural morphologies, including the formation of passive particle
vortices surrounding phase-separated active spinners and the development of large-scale active-passive bands. We characterize the underlying dynamics by analyzing the temporal
evolution of characteristic length scales and the non-
equilibrium velocity distributions of the passive particles. Our findings provide new insights into the role of long-range hydrodynamic couplings in governing the self-organization of non-
equilibrium condensed matter.
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Optics · Cross-listed from cond-mat.mtrl-sci
Coherent seeding and control of dynamical ferroelectricity by phonon anharmonicity
Junhan Huang, Yongkang Ju, Xinbo Wang et al. (+12 more)
Optical control of
quantum materials has progressed along two separate directions: creating non-
equilibrium states inaccessible at
equilibrium, and coherently controlling ultrafast dynamics with multi-pulse protocols. Ferroelectricity is especially attractive in this context because its order parameter, macroscopic polarization, directly links inversion-
symmetry breaking to functional response. Yet light-induced ferroelectricity has so far been confined to
quantum paraelectrics near the ferroelectric instability, where critical fluctuations obscure the formation of a homogeneous ferroelectric state and complicate its deterministic coherent control. Unifying these capabilities – preparing a
symmetry-broken state and then coherently steering its functionality – remains a central challenge. Here we show that intense terahertz excitation of a soft
phonon mode induces a ferroelectric state in centrosymmetric PbTe, a thermoelectric material with strong
lattice anharmonicity but no ferroelectric transition at finite temperature. The light-induced
symmetry-broken state can be realized up to about 100 K, without relying on local dipolar fluctuations. Experiment and theory together reveal that terahertz-driven anharmonic coupling between degenerate transverse optical
phonons underlies this ferroelectric induction. Furthermore, we demonstrate coherent amplification and suppression of the induced polarization via a double-pulse-excitation protocol. These results establish terahertz-driven anharmonic mode coupling as a general strategy for controlling mode-mediated functionalities in
quantum materials, opening a route to ultrafast information processing.
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All authors Junhan Huang, Yongkang Ju, Xinbo Wang, Li Yue, Hao Wang, Qiaomei Liu, Tianchen Hu, Yuchen Cui, Liyu Shi, Shangfei Wu, Sijie Zhang, Dong Wu, Peizhe Tang, Tao Dong, Nan-Lin Wang
Geophysics
Tensor Train Decomposition-based 3D Implicit Full Waveform Inversion with Multi-scale Structural Similarity
Liangsheng He, Chao Song, Tiansheng Chen et al. (+2 more)
Three-dimensional full waveform inversion (3DFWI) is a powerful technique for reconstructing high-resolution subsurface velocity models. However, its application is often limited by high
memory requirements, computational costs, and sensitivity to cycle skipping. To overcome these challenges, we propose a novel tensor train (TT) decomposition-based 3D implicit full waveform inversion framework (TT-3DIFWI) combined with a multi-scale structural similarity (M-SSIM) objective function. In this framework, the 3D velocity model is represented by TT decomposition as a product of a series of low-rank core tensors. Then, three axis-specific implicit neural network representations (INR) based on one-dimensional vector coordinates as input are constructed to predict these core tensors, rather than directly predicting the velocity model. This INR reparameterization method based on TT decomposition can significantly reduce the
memory consumption of INR training while maintaining the accuracy and resolution of the 3D velocity model reconstruction. Meanwhile, the low-rank structure of TT decomposition also ensures the structural consistency of the reconstruction velocity, thereby improving the accuracy and continuity of the inversion result. Furthermore, the M-SSIM objective function can compare the multi-scale structural differences between predicted and observed data, and utilize the ultra-low frequency features to reduce cycle skipping. Numerical experiments on synthetic and challenging land
datasets demonstrate that TT-3DIFWI with M-SSIM achieves accurate and continuous velocity reconstruction, even with poor initial models or missing low-frequency data.
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All authors Liangsheng He, Chao Song, Tiansheng Chen, Tao Liu, Cai Liu
Optics
Free-Running Waveguide-Integrated Single-Photon Avalanche Detectors for Visible Light
Aswin Alexander, Anirudh R. Ramaseshan, Soe M. Thar et al. (+4 more)
Waveguide-integrated single-
photon avalanche detectors (SPADs) are essential components of integrated photonics platforms for scalable extreme-low-light applications without the use of cryogenics. Here, we demonstrate an integrated SPAD for visible light operating at room temperature in a free-running mode without gating. The device is based on a doped silicon diode end-fire-coupled to a silicon nitride (SiN) photonic integrated
circuit (PIC). We investigate a range of lateral and vertical doping profile designs, and operate the devices with a simple current-mode passive quenching
circuit. The optimal device is a laterally-doped p-i-n+ SPAD with a maximum
photon detection efficiency (PDE) of 1.95 +/- 0.32% for input light at 685 nm wavelength, when reverse-biased at an excess of 1.5 V beyond the breakdown voltage of 15.0 V. We identify promising avenues for improving device performance, which would enable such integrated SPADs to be an attractive choice for cutting-edge integrated photonics solutions in
quantum technologies, low-light imaging, and high-speed communications at visible wavelengths.
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All authors Aswin Alexander, Anirudh R. Ramaseshan, Soe M. Thar, Thomas Y. L. Ang, Jing Zhou, Alexander Ling, Victor Leong
Physics and Society · Cross-listed from cs.AI
AI Scientists as Engines of Discovery: A Case for Development within Reformed Institutions
Raul Jimenez, Boris Bolliet, Francisco Villaescusa-Navarro et al. (+7 more)
Agentic artificial intelligence (AI) systems are beginning to assist, accelerate, and partially automate scientific discovery, performing tasks that span literature synthesis, code generation, data analysis, hypothesis proposal, and model criticism. We argue that this transition is qualitative rather than incremental, and that suitably designed multi-
agent systems may evolve from passive computational tools into “AI scientists” that can expand the hypothesis-generating and verification capacity of science. Such systems must be developed and deployed within a scientific ecosystem fit for purpose: institutions must be redesigned for verification, accountability, interpretability, and dual-use safety. We sketch how multi-
agent architectures, illustrated by the prototype framework Denario, accelerate the discovery cycle and traverse model spaces beyond human reach; examine what this implies for authorship, peer review, and the enduring role of human scientists; and close with recommendations for governing AI as an epistemic actor rather than a mere instrument.
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All authors Raul Jimenez, Boris Bolliet, Francisco Villaescusa-Navarro, Rabih Zbib, Benjamin Wandelt, David N. Spergel, Thomas Meier, Jessica Montgomery, Hana Aliee, Licia Verde
Optics
Low-threshold efficient N${_2^+}$ lasing driven by sub-cycle soliton dynamics in a hollow waveguide
Tiandao Chen, Zhiyuan Huang, Jinyu Pan et al. (+12 more)
The phenomenon of N${_2^+}$ lasing, observed in femtosecond-
laser filamentation, attract considerable interests in recent several years, with great application potentials in fields of remote sensing and ultrafast spectroscopy. Efficient N${_2^+}$ lasing at relatively-low pump energies and with high beam quality, while being highly-demanded for applications, remains, however, quite challenging in practical experiments. Here, we demonstrate a new route of generating low-threshold N${_2^+}$ lasing with unprecedently-high efficiency, which is enabled by
soliton dynamics in a gas-filled hollow-tapered-capillary system. High-order-
soliton compression of a 12-fs, 10-${\mu}$J-level pump pulse forms a sub-cycle asymmetric transient that tunnel-ionizes N${_2}$ to N${_2^+}$ and, through direct, single-
photon resonant excitation, creates population inversion between the ground state ${X^2\Sigma_g^+}$ and the excited state ${B^2\Sigma_u^+}$${-}$a dynamic process distinct from the widely adopted three-state coupling picture${-}$and remarkably at unexpectedly low pump energy. In the experiments, we obtained 100-nJ-level N${_2^+}$ lasing pulses at 391 nm with conversion efficiencies up to 3.3$\times$10$^{-3}$, at pump energies of less than 50 ${\mu}$J. These results represent improvement of more than one orders of magnitude in both generation efficiency and lasing threshold, compared with prevailing filamentation-based schemes. Our study bridges two generally-disparate fields (sub-cycle
soliton dynamics and N${_2^+}$ lasing), and paves the way for narrow-band, high-beam-quality lasing pulses that may find wide applications in advanced spectroscopy and nonlinear pump-probe experiments.
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All authors Tiandao Chen, Zhiyuan Huang, Jinyu Pan, Donghan Liu, Pengtao Wang, Xinglin Zeng, Jinxin Zhan, Jiapeng Huang, Wenbin He, Xin Jiang, Huailiang Xu, Yi Liu, Meng Pang, Yuxin Leng, Ruxin Li
Fluid Dynamics
Non-monotonic variations in pressure drop and chaos in viscoelastic fluid flows through an ordered microporous medium
A. Chauhan and C. Sasmal
Several recent experimental studies have revealed non-monotonic variations in elastic
turbulence-induced chaotic flow behaviour and pressure drop during the flow of viscoelastic fluids through a microporous medium. The present numerical study aims to investigate and hypothesise about the physical mechanisms governing these complex flow behaviours in an ordered microporous medium consisting of cylindrical micropillars arranged in a staggered configuration. We propose that birefringent strands of high elastic stress, generated by the stretching and
alignment of
polymer molecules within the porous structure, play the dominant role in controlling the non-monotonic variations in chaos and pressure drop. At low Weissenberg numbers, these stress strands develop gradually, mainly downstream of the micropillars, whereas beyond a critical Weissenberg number, they begin to fluctuate strongly, leading to chaotic flow dynamics. However, at even higher Weissenberg numbers, the strands become larger and stronger, eventually interconnecting between neighbouring micropillars, causing the flow to reorganise into a nearly steady, ordered state similar to that observed at low Weissenberg numbers. On the other hand, the pressure drop in the system consists of a mean contribution, obtained from statistically stationary flow quantities, and a fluctuating contribution. While the mean component increases monotonically with the Weissenberg number, the fluctuating component varies non-monotonically, leading to a similar trend in the total pressure drop. Moreover, the non-monotonic chaotic behaviour strongly depends on the solid volume fraction of the porous medium, which alters both the critical Weissenberg number for instability onset and the range over which the non-monotonic behaviour persists.
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Fluid Dynamics
A Conservative Time-Accurate Local Time-Stepping DG Scheme Based on a Weakly Compressible Model for Unsteady Low-Mach-Number Flows
Shihao Liu, Keli Zhang, Yuning Luan et al. (+1 more)
This paper presents a conservative high-order discontinuous Galerkin (DG) method featuring time-accurate local time stepping for simulating low-Mach-number unsteady flows, based on a weakly compressible formulation. In this model, pressure is defined solely as a function of density, eliminating the need for a global pressure Poisson equation typical of incompressible solvers while preserving the locality and conservation of compressible schemes. This makes it suitable for low-speed unsteady flows and aeroacoustics. The spatial discretization uses a strong-form nodal DG spectral element method (DGSEM) on Gauss-Lobatto-Legendre points. Inviscid fluxes are handled by numerical fluxes tailored to the weakly compressible system; specifically, a two-rarefaction approximate Riemann solver is developed for the constant-sound-speed barotropic equation of state. Viscous terms employ the incomplete interior penalty Galerkin (IIPG) method. For time integration, a continuous extension Runge-Kutta (CERK) scheme constructs
cell-local predictor
polynomials for continuous-in-time volume reconstructions. Face fluxes are split into interior and common contributions: the former matches the volume quadrature, while the latter uses piecewise Gaussian quadrature from continuous predictors. This split preserves discrete summation-by-parts cancellation and ensures conservative inter-element flux exchange.
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All authors Shihao Liu, Keli Zhang, Yuning Luan, Kai Liu
Computational Physics · Cross-listed from cond-mat.str-el
Isometrization of Tensor Network States via Gauge Propagation
Zhiyu Jiang and Hiroshi Ueda
We introduce a gauge-propagation approach for approximately converting generic tensor-network states into an isometric tensor-network form with a prescribed orthogonality center. In one dimension, this propagation is exact because the non-isometric factor produced by a QR or singular-value decomposition is supported on a single virtual bond. In higher-dimensional networks, however, a local step can have several outgoing directions, and the residual factor is generally not separable into independent single-bond contributions. We address this local obstruction by approximating a local tensor, or a contracted local cluster, by structured terms consisting of an isometric factor multiplied by a tensor product of output-leg factors. The isometric factor is retained at the current site or cluster, while the output-leg factors are absorbed into neighboring tensors along the propagation directions. This construction applies to general local input-output partitions for which the input-side dimension is no smaller than the output-side dimension and provides a local truncation criterion for gauge propagation.
Benchmarks on random tensors show that the proposed decomposition is effective in the low-term regime and that the residual decreases for larger local clusters. For the loop-gas tensor representation of the Kitaev
spin liquid, two structured terms reduce the local residual to numerical precision, and the same cluster refinement further lowers the leading-term truncation error and reduces error accumulation during gauge propagation on a finite honeycomb network. These results identify a propagation-compatible local decomposition as a useful building block for approximate isometrization and as a potential initializer or preconditioner for variational isoTNS
algorithms.
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Plasma Physics
Evaluation of spatiotemporal tungsten density profiles using Unresolved Transition Arrays in the Large Helical Device
R. Nishimura, T. Oishi, I. Murakami et al. (+12 more)
Tungsten spectroscopic studies have been conducted in the Large Helical Device with a pellet injection technique. Spatiotemporal profiles of tungsten density were evaluated using a space-resolved spectrometer, for
plasmas with an electron temperature of below 1 keV and electron density of $10^{19}-10^{20}$ $m^{-3}$. Slice & Stack, a method for reconstructing emissivity, was applied to a line at 191.7 Å , which is a part of the Unresolved Transition Array (UTA) spectrum at 90-250 Å. Tungsten density was obtained using
photon emission coefficients of $\mathrm{W}^{17+} - \mathrm{W}^{27+}$, evaluated from collisional-radiative model. The tungsten pellet injected from outside the
plasma was first ablated in the edge
plasma and subsequently diffused throughout the
plasma. This behavior is typical of pellet injection experiments. Furthermore, after an event triggered by NBI breakdown, tungsten accumulated in the core
plasma. The radiation power was estimated from the evaluated tungsten density profile and cooling factor
dataset, and compared with bolometer measurement. This sequence of processes would be useful for validating atomic data of tungsten ions in low-to-intermediate charge states.
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All authors R. Nishimura, T. Oishi, I. Murakami, D. Kato, H. A. Sakaue, S. Gupta, H.Ohashi, C. Suzuki, M. Goto, Y. Kawamoto, R.T. Ishikawa, T. Kawate, K. Mukai, B.J. Peterson, H. Takahashi
Optics
Autonomous Generation of Metamaterial Databases Based on Multimodal Agents
Shilong Qin, Zhicai Yu, Xuan Zheng et al. (+6 more)
Artificial intelligence (AI) is revolutionizing material research and discovery. However, its development in metamaterials is bottlenecked by a shortage of high-quality and executable structure-response databases, which are locked within scientific literatures as a mixture of text and images. Converting the rapidly growing body of scientific literatures into executable and reusable databases for machine-driven discovery is still a fundamental challenge. Here, we propose MetaDataGenAgent, a
multimodal multi-
agent framework that autonomously converts unstructured scientific literatures directly into metamaterial structure-response databases. MetaDataGenAgent establishes a complete literature-to-simulation pipeline through the coordinated operation of specialized
agents for
multimodal parameter extraction, physics-guided validation,
topology-aware structural analysis, and solver-executable encoding. The framework introduces a closed-loop plan-execute-reflect mechanism that enables dynamic task decomposition, iterative validation, and feedback-driven model construction. Experimental results validate that MetaDataGenAgent can generate high-fidelity structure-response data for representative meta-atoms, which are further used to realize diverse electromagnetic functions, including far-field beam deflection, near-field
holographic imaging and topologically protected surface-wave transport. By establishing an autonomous route from scientific literatures to AI-ready databases, the framework provides a general and efficient strategy that could be extended to a broad range of data-scarce scientific domains, including photonics, materials science, chemistry, computational science, and scientific automation.
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All authors Shilong Qin, Zhicai Yu, Xuan Zheng, Yan Zhang, Aodi Yang, Kezhan Zhao, Qi Cheng Chen, Jian Wei You, Tie Jun Cui
History and Philosophy of Physics · Cross-listed from math-ph
Why Hadamard states?
Eleanor March
In QFT on curved spacetime, the Hadamard condition is often presented as a necessary condition on 'physically reasonable' states of the
quantum field, and plays a central role in many theoretical and foundational applications - ranging from proofs of the renormalizability of Wick
polynomials to derivations of the Hawking temperature. Yet despite this, the philosophical and foundational underpinnings of the Hadamard condition remain murky. I critically discuss existing motivations for the Hadamard condition in the literature, before arguing in favour of an alternative motivation for the Hadamard condition, according to which it is best understood as a necessary and sufficient condition for the existence of a well-defined operator product of a certain form on a sufficiently large space of observables of the
quantum field, satisfying a variety of further conditions. This clarifies the role and status of the Hadamard condition, including its relationship to the equivalence principle, to well-definedness of physical quantities such as Wick
polynomials and the expectation value of the stress-energy operator, and the sense in which Hadamard states are '
vacuum-like'.
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Computational Physics · Cross-listed from cs.NE
Evolutionary Optimization Reveals Structural Constraints on Reservoir Architecture for Spatiotemporal Chaos
Nima Dehghani
Biological systems maintain function in fluctuating environments by transforming past stimulation into internal dynamical states that support future-oriented responses. Reservoir computing provides a computational analogue, but standard formulations often treat the recurrent substrate as a fixed random network and train only the readout. Here we ask how the substrate itself changes when reservoir architecture is placed under evolutionary selection for prediction. Using the Kuramoto–Sivashinsky equation as a testbed for spatiotemporal chaos, we evolved reservoirs over five construction hyperparameters: size, connectivity degree, spectral radius, input scaling, and readout regularization.
Evolution reduced prediction error at the population level, extended the low-error forecast horizon, and organized the design space along a diminishing-return size–efficiency frontier. Structural analyses showed that evolved reservoirs remained within a conserved
stochastic-block-model-like spectral envelope while refining low-
eigenvalue modes, locking modularity to an intermediate band, and
pruning connection cost within that band. Pareto analysis showed that elite reservoirs occupied a horizontal floor in the cost–modularity plane, indicating that accuracy and efficiency were achieved jointly rather than through a simple trade-off. These findings show that evolutionary optimization does not merely improve prediction, but exposes interpretable structural constraints on the recurrent substrate: it stabilizes a task-suitable dynamical class and refines the architectural degrees of freedom most relevant for prediction. Evolutionary reservoir computing therefore provides a bio-inspired framework for studying how predictive demands shape adaptive dynamical networks.
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Computational Physics · Cross-listed from cs.LG
One-Step Flow Matching for Generative Modeling of Path-Dependent Physical Fields
Yijing Zhou and Jasmin Jelovica
Physical simulations for intricate geometries with path-dependent constitutive models face difficulties due to the enormous computational cost they require. Recently, the emergence of generative AI models, which succeed in image and
video synthesis tasks, has provided a promise to further improve simulations. Although U-Net-based denoising
diffusion probabilistic models (DDPMs) have been adopted for elastic stress field generation, they typically require hundreds of sampling steps, and applications of generative models to path-dependent, e.g. plastic, stress fields remain very limited. In this work, we propose a novel flow matching (FM) model based on a
transformer backbone for high-resolution path-dependent stress field generation with
stochastic loading-unloading paths and geometry. The proposed model operates within the latent space of a variational autoencoder (VAE) and formulates the simulation of plastic fields as a
video synthesis task, directly generating the stress fields across all time steps. Meanwhile, we design a non-Gaussian source distribution for flow matching, such that crossings among conditional transport paths are reduced during training. This enables our model to generate satisfactory samples in one step without relying on
distillation. In addition, we introduce
token-level loading
embeddings and two auxiliary networks to further enhance the model performance in path-dependent simulation. The results demonstrate that, even with a limited training
dataset, our model can accurately generate high-resolution path-dependent fields. It is much more computationally efficient than finite element analysis, providing a speedup of 6 to 7 times over FEM on CPUs and approximately two orders of magnitude speedup on consumer-grade GPUs.
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Optics · Cross-listed from cond-mat.mes-hall
Modulating radiative heat and momentum transfer via the thermal Purcell effect
Liyao Jiao, Yaohua Liu and Gaomin Tang
The thermal Purcell effect describes the modification of the local density of states of the fluctuating electromagnetic field induced by a Fabry-Pérot cavity, leading to the enhancement or suppression of radiative transport quantities. Using fluctuational electrodynamics, we investigate nonequilibrium radiative heat, linear-momentum, and angular-momentum exchange between a magneto-optic nanoparticle and a Fabry-Pérot cavity. Analytical expressions for the spectral densities reveal that
geometric confinement modifies the electromagnetic local density of states, producing distinct behaviors for different transport quantities. Specifically, sub-wavelength confinement enhances radiative heat and angular-momentum transfer, but suppresses the lateral force. Additionally, interference between cavity modes causes all transfer quantities to oscillate spatially with particle position. At the cavity center, mirror
symmetry enforces a parity decomposition of electromagnetic fluctuations resulting in a vanishing lateral force, whereas heat transfer and torque remain finite through combined even and odd modal contributions. These results demonstrate that cavity engineering provides selective control over nanoscale energy and momentum transfer via structured electromagnetic fluctuations.
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Computational Physics · Cross-listed from eess.SY
Development, Validation, and Benchmarking of a Multidisciplinary Semi-Analytical Model for Wave Energy Converters
Rebecca McCabe, Madison Dietrich and Maha Haji
Wave energy converters (WECs) require system-level techno-economic analysis to balance power production, cost, and survivability. Existing simulation tools are either too computationally costly for large-scale optimization or too narrow in disciplinary scope to support integrated design studies. This work presents MDOcean, a novel open-source WEC simulation framework for rapid early-stage design exploration, parametric analysis, and multidisciplinary optimization. MDOcean integrates hydrodynamics, dynamics, structures, and economics in a computationally efficient architecture based on analytical and semi-analytical methods that substantially reduce runtime while maintaining near-numerical accuracy. The framework includes an eigenfunction-based linear hydrodynamic solver, a quasi-linearized frequency-domain dynamics engine capable of modeling drag and saturation nonlinearities, a structural sizing module incorporating realistic yield, ultimate, buckling, storm, and fatigue design criteria, and a simple cost model for techno-economic assessment. Particular emphasis is placed on the linearized pseudo-spectral optimal control formulation, which extends frequency-domain constraint-handling approaches with a unified describing-function and analytical quadratically-constrained quadratic program framework. This formulation efficiently treats nonlinearities and constraints while preserving compatibility with optimization and frequency-domain analysis techniques. Validation and benchmarking demonstrate that MDOcean's 151 ms runtime is orders of magnitude faster than leading WEC simulation tools while maintaining agreement with higher-fidelity baselines to within a few percent in most cases. The framework also provides insight into limiting behaviors, scaling laws, subsystem interactions, and key tradeoffs governing WEC design and techno-economic performance.
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Applied Physics · Cross-listed from quant-ph
Protecting Qubits from Purcell Decay via Permanent Dipoles
Alex Krasnok
Reading out a
qubit often requires coupling it to a resonator, but that same resonator can also give the
qubit an extra path to decay. Here, we study a way to reduce this loss using a built-in permanent electric dipole. The dipole shifts the cavity field in different directions for the
qubit ground and excited states. This shift makes the relevant wave functions overlap less, which weakens the transverse
qubit–cavity exchange that causes Purcell decay. In a simplified displaced rotating-wave model, this exchange vanishes at $\eta=\sqrt{2}$. In the full transverse model, this exact zero is lifted, but strong suppression remains at a larger dipole-induced displacement. Using dressed open-system decay rates, we find an operating point where the cavity-mediated decay is strongly reduced while the longitudinal readout signal remains finite. For the
benchmark studied here, at fixed pointer separation, the normalized lifetime increases from $\kappa T_1=11.1$ to $47.3$, and the estimated single-shot readout error drops from $0.21$ to $0.07$. These results show that permanent electric dipoles can provide an internal, channel-selective form of Purcell protection.
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