Fluid Dynamics
Applying contact angles based on a continuously moving contact line in 2D VOF simulations
Tianyang Han, Jieyun Pan, Chongsen Huang et al. (+4 more)
A height-function-based numerical approach is developed for enforcing contact angles on flat and curved solid surfaces within two-dimensional volume-of-fluid simulations. This method incorporates the contact line position into the
curvature estimation in the contact line
cell, where the interface normal is constrained to the prescribed angle to ensure smooth contact line motion. On flat solid surfaces, the proposed model achieves higher accuracy than the conventional vertical height-function method for enforcing very small and very large contact angles. Moreover, it extends naturally to curved solid surfaces represented by the embedded boundary method, enabling the imposition of arbitrary contact angles without inducing significant spurious currents near the contact line. Numerical validations confirm the accuracy and robustness of the proposed method, demonstrating its applicability to multiphase flows involving complex wall geometries and contact-line dynamics.
Read the full abstract ▾
All authors Tianyang Han, Jieyun Pan, Chongsen Huang, Jie Zhang, Mingjiu Ni, Stéphane Popinet, Stéphane Zaleski
Biological Physics · Cross-listed from cond-mat.soft
Non-reciprocal visual perception and polar alignment drive collective states in chiral active particles
Diganta Bhaskar, Abhishek Chaudhuri and Anil Kumar Dasanna
Self-propelled particles rarely move in straight lines; environmental interactions, shape asymmetry, and intrinsic torques generically induce curved or fluctuating trajectories. In biological and synthetic systems, this
curvature often coexists with directional sensing and non-reciprocal interactions. Motivated by this, we explore the collective dynamics of
chiral intelligent active Brownian particles (iABPs) that combine polar
alignment with
vision-based sensing. By varying the ratio of
alignment to visual maneuverability, the
vision angle, and the reduced chirality $(\omega/D_r)$, we construct a phase diagram exhibiting diverse collective states: spinners,
vortices, ripples, worm-like swarms, rotary clusters, and irregular aggregates. Chirality critically governs their morphology: high chirality yields dilute phases, while moderate to low chirality produces cohesive yet dynamic patterns. Ripple loops emerge as a distinct state, characterized by expanding ring-like motion driven by outward torques and sustained only when both particle number and visual maneuverability are large. Structural and dynamical measures, including polarization, pair correlations, mean-square displacement, and orientation correlations, reveal clear signatures distinguishing these phases. Overall, our results show how chirality, non-reciprocal perception, and
alignment together generate collective states inaccessible to non-
chiral systems, with implications for
chiral active matter in biological and synthetic contexts.
Read the full abstract ▾
Applied Physics
Harmonic-Recycling Rectification Based on Novel Compact Dual-Band Resonator
Pengde Wu, Hao Wu, Yi-Dan Chen et al. (+3 more)
Harmonic generation during
radio frequency (RF)-dc conversion causes performance degradation of a microwave rectifying
circuit. To suppress and recycle the harmonic power, this letter proposes a novel compact dual-band resonator (DBR) based on a microstrip coupled transmission line. It presents open-
circuits at the second and third harmonic frequencies, which effectively block the higher order harmonic for power recycling. The conventional input cascading filters for harmonic rejection can be eliminated, simplifying the
circuit topology and reducing loss. Theoretical analyses were carried out and corresponding equations were formulated for the proposed DBR. For validation, two rectifying
circuits with/without the DBR operating at 2.2 GHz were fabricated and tested. Using the proposed DBR at 10 dBm RF power, the suppression of the second and third harmonic powers is enhanced by 18.4 and 7.6 dB, respectively. Besides, an improvement of RF-dc power conversion efficiency (PCE) was observed; specifically, PCE reached 73.2% at 10 dBm compared to 71.6% obtained from an equivalent rectifier.
Read the full abstract ▾
All authors Pengde Wu, Hao Wu, Yi-Dan Chen, Zhi Hua Ren, Yuhua Cheng, Changjun Liu
Instrumentation and Detectors
Ion Temperature Inference from Neutron Counting in Maxwellian Deuterium Plasmas
Allison J. Radich, Vlad Grecu, Patrick J. F. Carle et al. (+7 more)
A method is presented for inferring the deuterium fuel ion temperature from
neutron counts measured with fast
liquid scintillators in conditions where the ion velocity distribution is Maxwellian. Local
neutron count rates at each scintillator position are combined to estimate total
neutron yield from the
plasma, where absolute detection efficiency is determined via MCNP
neutron scattering simulation based on a 3D model of the experiment structure. This method is particularly advantageous for Magnetized Target Fusion applications as it yields a time-resolved diagnostic and does not require direct line-of-sight to the
plasma or collimation of the
neutrons. The instrumentation configuration, pulse-shape discrimination and pile-up correction
algorithms, detector calibration, and ion temperature calculation method with uncertainty characterization are discussed. An application of the method to General Fusion's
Plasma Injector~3 (PI3) spherical tokamak device is demonstrated and the results are compared to an Ion Doppler spectroscopy ion temperature diagnostic.
Read the full abstract ▾
All authors Allison J. Radich, Vlad Grecu, Patrick J. F. Carle, Myles Hildebrand, Stephen J. Howard, Colin P. McNally, Meritt Reynolds, Akbar Rohollahi, Ryan E. Underwood, Sara Weinstein
Biological Physics
Quantum tunnelling-integrated optoplasmonic nanotrap enables conductance visualisation of individual proteins
Biao-Feng Zeng, Zian Wang, Yuxin Yang et al. (+17 more)
Biological electron transfer (ET) relies on
quantum mechanical tunnelling through a dynamically folded
protein. Yet, the spatiotemporal coupling between structural fluctuations and electron flux remains poorly understood, largely due to limitations in existing experimental techniques, such as ensemble averaging and non-physiological operating conditions. Here, we introduce a
quantum tunnelling-integrated optoplasmonic nanotrap (QTOP-trap), an optoelectronic platform that combines plasmonic optical trapping with real-time
quantum tunnelling measurements. This label-free approach enables single-molecule resolution of
protein conductance in physiological electrolytes, achieving sub-3 nm spatial precision and 10-{\mu}s temporal resolution. By synchronising optoelectronic measurements, QTOP-trap resolves
protein-specific conductance signatures and directly correlates tertiary structure dynamics with conductance using a "
protein switch" strategy. This methodology establishes a universal framework for dissecting non-
equilibrium ET mechanisms in individual conformational-active
proteins, with broad implications for bioenergetics research and biomimetic
quantum device design.
Read the full abstract ▾
All authors Biao-Feng Zeng, Zian Wang, Yuxin Yang, Xufei Ma, Liang Xu, Yi Shen, Long Yi, Yizheng Fang, Ye Tian, Zhenrong Zheng, Yudong Cui, Ji Cao, Ge Bai, Weixiang Ye, Pan Wang, Cuifang Kuang, Joshua B. Edel, Aleksandar P. Ivanov, Xu Liu, Longhua Tang
Fluid Dynamics
Complete Matched Asymptotic Expansions for Velocity Statistics in Turbulent Channels
Peter A. Monkewitz
Complete high fidelity matched asymptotic expansions (abbreviated MAE) are developed for the first and second order
turbulence statistics in channel flow from 11 direct numerical simulations (DNS). To put the crucial identification of overlaps on a solid footing, a simple a priori test is devised, which only requires a DNS or experimental profile and the presumed overlap of the MAE for the quantity in question. This test fully supports the form c0 - c1 Y^1/4 of the overlaps for the stream-wise and cross-stream normal stresses <uu> and <ww>, which has been advocated by Chen and Sreenivasan (2022, 2023, 2025) and Monkewitz (2022, 2023). The first MAE analysis of the wall-normal stress <vv> then reveals an overlap of the form c0 - c1 Y^5/4 , which is extensively documented. Finally, the logarithmic indicator function Xi = y dU/dy for the mean velocity overlap is reanalyzed, with focus on its spatial oscillations. The latter are compared in the concluding section to the spatial oscillations of <uu>, together with further observations.
Read the full abstract ▾
Applied Physics
Optically Transparent Meta-Grating Embedded in Rear Windshields for Automotive Radar Detection
Sergey Geyman, Dmytro Vovchuk, Denis Kolchanov et al. (+9 more)
Radar plays a crucial role in automotive safety by enabling reliable object detection, thereby assisting drivers and, prospectively, serving as one of the primary sensors in autonomous driving. The radar visibility of a road participant depends on its radar cross-section (RCS). While RCS is an inherent property, enhancing it, similar to using reflective vests for optical visibility, can significantly improve radar detection through cooperative target design. However, modern vehicles are not designed for this purpose, and embedded reflectors are not utilized due to the industry's conservative approach and the limited space available on the vehicle's exterior. Rear windshields offer a vast unused area, but they must still serve their primary function and remain transparent. We propose utilizing this area by
embedding a reflecting surface that accounts for the interrogation scenario geometry and the angular tilt of the rear windshield, ensuring the wave is retroreflected back to the radar. The surface is realized as an array of thin conductive wires with a periodicity that provides in-phase excitation for the design incidence angle. Given that automotive radars operate in the millimeter-wave regime (77-81 GHz), large-scale surfaces with sub-millimeter manufacturing accuracy are required. This is achieved by imprinting conductive inks, composed of silver nanoparticles and binders, into grooves in the glass. The fabricated 10x10 sq. sm. sample, with around 90% optical transparency, demonstrates an RCS of 8 sq. m., surpassing the typical RCS of a car. Extrapolating this performance to the entire rear window with an embedded meta grating, a typical RCS of 1000 sq. m. can be achieved, thereby enhancing the detectability range by nearly an order of magnitude. Smart windows enable advanced applications in wireless communication, such as automotive scenarios, IoT, and many others.
Read the full abstract ▾
All authors Sergey Geyman, Dmytro Vovchuk, Denis Kolchanov, Mykola Khobzei, Vladyslav Tkach, Hagit Gilon, Eyal Cohen, Eran Yunger, Vjaceslavs Bobrovs, Aviel Glam, Ofer Amrani, Pavel Ginzburg
Biological Physics · Cross-listed from cond-mat.mes-hall
The transmembrane potential across a charged nanochannel subjected to asymmetric electrolytes
Ramadan Abu-Rjal and Yoav Green
The transmembrane voltage, $V$, which is the potential drop required to nullify the electrical current ($i=0$), is a key characteristic of water desalination and energy harvesting systems that utilize macroscopically large nanoporous membranes, as well as for physiological ion channels subjected to asymmetric salt concentrations. To date, existing analytical expressions for $V_{i=0}$ have been limited to simple scenarios or under simplifying assumptions. In this work, we derive two expressions for $V_{i=0}$. First, we consider the much simpler scenario of two species. Then, we can consider an electrolyte comprised of an arbitrary number of species. The difference in the models is that the latter solution utilizes an ad-hoc assumption of a linear concentration profile, while the former solution does not require such an ad-hoc assumption. We analyze both models and show how to reduce them to several known models. We also verify both models with numerical simulations of the one-dimensional Poisson-Nernst-Planck equations. We show how the interplay between
diffusion coefficients and ionic valencies significantly varies the system response and why it is essential to account for all system parameters. Ultimately, this model can be used to improve experimental interpretation of ion transport measurements
Read the full abstract ▾
Atmospheric and Oceanic Physics
Warming-driven rise in soil moisture entropy signals destabilization of the Asian Water Tower
Yiran Xie, Teng Liu, Xuan Ma et al. (+6 more)
The Tibetan Plateau (TP), known as the "Asian Water Tower," is currently undergoing a rapid wetting trend. While this moisture increase is often viewed as beneficial for water availability, it remains unclear whether the hydrological system itself is becoming more resilient or drifting toward instability. Here, we apply an
entropy-based framework to quantify the changing structural organization of the TP's soil moisture system. We show that from 2000 to 2024, regional wetting has driven a long-term decline in
entropy, reflecting an increase in system order and stability due to enhanced hydrological buffering capacity. This stability is modulated by the El Niño-Southern Oscillation (ENSO), which regulates regional heterogeneity via a distinct spatial dipole. Crucially, however, CMIP6
climate projections reveal an alarming reversal: future warming triggers a rise in
entropy. This transition signals a loss of systemic resilience, characterized by intensified spatial disorder and potential abrupt regime shifts by the mid-century. Our findings suggest that while current wetting provides a stabilizing buffer, continued warming is projected to amplify spatial heterogeneity, thereby destabilizing the Asian Water Tower, with significant risks for downstream water security.
Read the full abstract ▾
All authors Yiran Xie, Teng Liu, Xuan Ma, Yingshuo Lyu, Xu Wang, Yatong Qian, Yongwen Zhang, Ming Wang, Xiaosong Chen
Optics · Cross-listed from astro-ph.GA
Spheroidal core-mantle particle absorption, scattering, and polarisation in the long-wavelength limit
Ant Jones and Nathalie Ysard
The numerical calculation of optical properties (extinction, absorption, scattering and polarisation efficiencies) is often time-consuming for non-spherical and inhomogeneous particles. Where possible analytical methods are therefore to be preferred. We provide an analytical tool to derive the optical properties of mantled spheroidal particles, of arbitrary axis ratio, in the long wavelength limit (a << lambda), where the mantle form may be confocal, co-axial or of constant depth with respect to the particle core. We have developed an analytical approach to spheroidal core/mantle particle optical property calculations. The analytical method compares well with DDSCAT numerical calculations and, under limited circumstances, with those made using the Bruggemann effective medium theory (EMT).The analytical method presented here provides a useful tool to explore the optical and polarisation properties of core/mantle spheroidal particles at long wavelengths (lambda >~ 8mu) and is simpler and faster to implement than corresponding numerical methods. We caution against the use of EMT methods in approximating the optical properties of core/mantle particles.
Read the full abstract ▾
Fluid Dynamics
Scalar mixing in non-Markovian homogeneous isotropic synthetic turbulence
Pratyush S. Awasthi, Joaquim P. Jossy, Amitabh Bhattacharya et al. (+1 more)
We show that non-Markovianity of the velocity field is an essential property of turbulent mixing. We demonstrate this via passive scalar mixing by synthetically generated
stochastic velocity fields. Including a separate velocity decorrelation time scale for each spatial scale (random sweeping) yields an essentially non-Markovian velocity field with a finite time
memory decaying as -5 (for a decaying spectrum) instead of an exponential decay (Markovian), which is obtained by including a constant time scale for all spatial scales, irrespective of the filtering function. We characterize the Lagrangian mixing statistics of both the Markovian and non-Markovian synthetic fields and compare them against a corresponding incompressible direct numerical simulation (DNS). We also study diffusive passive scalar mixing in the Schmidt number range Sc<1 using the DNS and the synthetic fields. While both the synthetic fields recover the -17/3 scalar spectrum for low Schmidt numbers, the mean gradients in a decaying simulation, as well as the production and dissipation of scalar variance in a statistically stationary simulation, are severely underpredicted by the Markovian fields compared to the non-Markovian fields. Throughout, we compare our results with companion 3D DNS to show the necessity of non-Markovianity in synthetic fields to capture mixing dynamics.
Read the full abstract ▾
All authors Pratyush S. Awasthi, Joaquim P. Jossy, Amitabh Bhattacharya, Prateek Gupta
Applied Physics · Cross-listed from cond-mat.mtrl-sci
Sol-Gel-Derived NiO/ZnO Thin Films with Single and Heterostructure Layers for Electrochemical Energy Storage
Miss Nourin Nurain Amina, Md Noushad Hossain, Muhammad Shahriar Bashar et al. (+2 more)
NiO/ZnO-based thin films, including single-layer and
heterostructure configurations, were synthesized to investigate the influence of stacking order on their electrochemical performance for supercapacitor applications. To improve the relatively low capacitive performance of ZnO compared to NiO, NaCl was introduced as a dopant. All films were deposited using a non-
vacuum spin-coating method on fluorine-doped tin
oxide (FTO) substrates, chosen for their excellent electrical conductivity and stability as electrode materials. The surface morphology and structural parameters were examined using scanning electron microscopy (SEM) and X-ray diffraction (XRD), respectively. Optical properties were analyzed via UV-Vis spectroscopy, revealing direct band gaps in the range of 3.17-3.31 eV for ZnO and Na-ZnO, and wider gaps up to 3.81 eV for NiO. Electrochemical performance was evaluated using cyclic voltammetry (CV), galvanostatic charge-discharge (GCD), and electrochemical impedance spectroscopy (EIS) in a three-electrode configuration with 1 M KOH as the electrolyte. Among the electrodes, the single-layer NiO film exhibited the highest specific capacitance of 1.391 Fg^{-1}. In contrast, the NiO/ZnO
heterostructure demonstrated a synergistic effect, resulting in enhanced charge storage and achieving a maximum specific capacitance of 1.627 Fg^{-1} at a current density of 2.0 mA cm^{-2}. Furthermore, sodium doping significantly improved the capacitance of ZnO. Overall, the results highlight the potential of sol-gel-derived
oxide heterostructures and doped thin films as cost-effective and scalable electrode materials for supercapacitors in portable electronics and energy storage systems.
Read the full abstract ▾
All authors Miss Nourin Nurain Amina, Md Noushad Hossain, Muhammad Shahriar Bashar, Munira Sultana, Md. Salahuddin Mina
Fluid Dynamics
Wave turbulence of inertia–gravity waves: a theory for the oceanic spectrum
Michal Shavit, Oliver Bühler and Jalal Shatah
We present a derivation using kinetic wave theory of the two-dimensional empirical Garrett–Munk spectrum for ocean internal waves, valid at all frequencies including near-inertial frequencies. This is based directly on the governing equations for a two-dimensional Boussinesq system with constant stratification and rotation. Our results improve on previous work by side-stepping the use of canonical variables, by taking full account of the Coriolis parameter in a non-hydrostatic dispersion relation, by filtering the balanced flow component from the dynamics, by using the conservation laws for energy and two components of pseudomomentum to bring the collision integral into a very simple form, by giving precise convergence conditions for the collision integral, and by finding the unique scale-invariant turbulent wave spectrum that corresponds to turbulent fluxes from small to large wavenumbers. The last step was achieved in the limit of small but nonzero Coriolis parameter. Key results are that any nonzero Coriolis parameter regularizes the singular nature of the non-rotating problem and that the homogeneity properties of the dispersion relation and of the interaction coefficients alone already imply that the spectrum is separable in vertical wavenumber and frequency. Within the restrictions of two-dimensional dynamics, this provides a theoretical framework for internal-wave
turbulence consistent with oceanic observations.
Read the full abstract ▾
Optics
Modal Analysis of Gyrotropic Waveguides
Konstantinos Delimaris, Georgios D. Kolezas, Carsten Rockstuhl et al. (+1 more)
We report on the modal analysis of open gyrotropic waveguides (GWs). The GWs consist of a non-circular gyrotropic (i.e., gyroelectric and gyromagnetic) core and an infinitely extending isotropic cladding. To solve this problem, we develop two independent full-wave methods. The first technique is an extended integral equation (EIE) method, an extension of a previously developed EIE used to calculate the propagation constants in composite dielectric-isotropic waveguides. The second technique is a Chebyshev expansion method (CEM). In both implementations, the electric and
magnetic fields in the gyrotropic core are expanded in superpotential-based cylindrical vector wave functions (SUPER-CVWFs), recently developed for the problem of oblique multiple scattering by gyrotropic cylinders. Both techniques allow us to calculate the propagation constants in the general case, without approximations. Various non-circular gyrotropic waveguides are considered. The EIE and CEM results are validated against a commercial finite element solver, and the accuracy and computational performance of both methods are benchmarked. A microwave application is presented where the complex propagation constants of ferrite rods are computed in the presence of an external
magnetic flux density bias. Our work advances the theory of propagation in open waveguides, from dielectric/isotropic to gyrotropic ones, and enables the design of contemporary waveguiding structures.
Read the full abstract ▾
All authors Konstantinos Delimaris, Georgios D. Kolezas, Carsten Rockstuhl, Grigorios P. Zouros
Applied Physics
Physics-informed neural network surrogate modeling of single particle model for lithium-ion batteries
Yi Zhuang, Yusheng Zheng, Yunhong Che et al. (+1 more)
Physics-based models play a key role in battery management, yet face challenges in real-time applications due to the high computational cost of solving coupled algebraic-partial differential equations. To accelerate model simulation, this study
benchmarks three physics-informed neural network (PINN) architectures for modeling the battery single particle model, including two conventional PINN architectures and a DeepONet-based architecture. Both the accuracy and the generalization of these PINNs have been evaluated and compared under various current conditions. Our results highlight the potential of PINNs in modeling battery physics but also reveal limitations of conventional PINN architectures under highly dynamic current conditions. Among them, the
Fourier-enhanced DeepONet achieves superior generalization performance and offers nearly a 10 times speedup compared with numerical solvers. This work provides an example of integrating physics-based models
Read the full abstract ▾
All authors Yi Zhuang, Yusheng Zheng, Yunhong Che, Remus Teodorescu
Applied Physics
Fully Coupled Multiphysics Modelling of Fracture Behaviour in Silicon Particles During Lithiation Delithiation Using the Phase Field Method
Jie Yang and Wei Tan
In this study, a multiphysics model fully coupling mass transport, deformation, phase field, and fatigue damage was developed to investigate the cracking and fracturing behaviours of Si particles during the single lithiation-delithiation cycle and fatigue damage during multiple cycles. The effects of particle diameter, charge rate, and pre-existing notches on the failure behaviour of Si particles were systematically analysed. The results showed that the increase in charge rate, particle diameter, and pre-existing notch length leads to larger cracking rates and faster fracturing of the particle. Then, a validated contour map of Si particle's fracture behaviours was developed. Additionally, the influence of pre-existing notch length and charge rate on fatigue damage was examined, and it was found that longer pre-existing notch length and larger charge rate can shorten the particle's cyclic life. Finally, to alleviate the particle fracture, nanopores were introduced in the particle, and the influence of porosity on the fracture behaviours was investigated. The results showed that nanopores can reduce expansion, dissipate global tensile stresses and elongate the crack propagation path. The developed computational framework established a predictive relationship between stress
diffusion coupling theory and particle-level degradation, guiding future design and manufacturing of failure-resistant Si-based anodes for lithium-ion batteries.
Read the full abstract ▾
Applied Physics
Image Synthesis Using Spintronic Deep Convolutional Generative Adversarial Network
Saumya Gupta, Abhinandan, Venkatesh vadde et al. (+2 more)
The computational requirements of generative
adversarial networks (GANs) exceed the limit of conventional Von Neumann architectures, necessitating energy efficient alternatives such as neuromorphic spintronics. This work presents a hybrid CMOS-spintronic deep convolutional generative
adversarial network (DCGAN) architecture for synthetic image generation. The proposed generative
vision model approach follows the standard framework, leveraging generator and discriminators
adversarial training with our designed spintronics hardware for deconvolution, convolution, and activation layers of the DCGAN architecture. To enable hardware aware spintronic implementation, the generator's deconvolution layers are restructured as zero padded convolution, allowing seamless integration with a 6-bit skyrmion based synapse in a crossbar, without compromising training performance. Nonlinear activation functions are implemented using a hybrid CMOS domain wall based Rectified linear unit (ReLU) and Leaky ReLU units. Our proposed tunable Leaky ReLU employs domain wall position coded, continuous resistance states and a piecewise uniaxial
parabolic anisotropy profile with a parallel MTJ readout, exhibiting energy consumption of 0.192 pJ. Our spintronic DCGAN model demonstrates adaptability across both grayscale and colored
datasets, achieving Fr'echet Inception Distances (FID) of 27.5 for the Fashion MNIST and 45.4 for Anime Face
datasets, with testing energy (training energy) of 4.9 nJ (14.97~nJ/image) and 24.72 nJ (74.7 nJ/image).
Read the full abstract ▾
All authors Saumya Gupta, Abhinandan, Venkatesh vadde, Bhaskaran Muralidharan, Abhishek Sharma
Optics
Programmable ultra-broadband photonic chaos platform enabled by microwave-chaos-driven electro-optic frequency combs
Shiyu Shi, Yiqun Zhang, Mengjie Zhou et al. (+7 more)
Optical chaos holds great promise for secure communication,
LiDAR, and reinforcement learning. However, its scalability has long been constrained by an intrinsic trade-off between bandwidth and the number of parallel chaotic channels. Here, we introduce a programmable "chaos-on-comb" architecture that overcomes this limitation using standard electro-optic components. By heterodyning a delayed-feedback chaotic
laser with a continuous-wave reference, a broadband chaotic microwave signal is generated to simultaneously drive a cascaded electro-optic comb, imprinting chaotic dynamics across all comb lines and merging them into an ultra-broadband chaotic continuum. Then, incorporating spectrum slicing enables flexible extraction of parallel chaotic channels with preserved statistical independence and per-channel programmability. As a result, we demonstrate a single-channel ultra-broadband optical chaos with an effective bandwidth of 543.8 GHz, and a broadband terahertz noise source with an excess noise ratio of 52.99 \pm 2.85 dB to validate its flatness. Furthermore, we employ the uncorrelated parallel chaos for ultrafast photonic decision-making in a 256-armed bandit problem, achieving a favourable power-law scaling exponent of 0.86. Our work paves the way toward programmable, reconfigurable, and application-ready photonic chaos systems.
Read the full abstract ▾
All authors Shiyu Shi, Yiqun Zhang, Mengjie Zhou, Mingfeng Xu, Xianglei Yan, Qiang Chen, Yunxia Yang, Yinghui Guo, Mingbo Pu, Xiangang Luo
Chemical Physics · Cross-listed from quant-ph
Implicitly Restarted Lanczos Enables Chemically-Accurate Shallow Neural Quantum States
Wei Liu and Wenjie Dou
The variational optimization of high-dimensional neural network models, such as those used in neural
quantum states (NQS), presents a significant challenge in machine intelligence. Conventional first-order
stochastic methods (e.g., Adam) are plagued by slow convergence, sensitivity to hyperparameters, and numerical instability, preventing NQS from reaching the high accuracy required for fundamental science. We address this fundamental optimization bottleneck by introducing the implicitly restarted Lanczos (IRL) method as the core engine for NQS training. Our key innovation is an inherently stable second-order optimization framework that recasts the ill-conditioned parameter update problem into a small, well-posed Hermitian
eigenvalue problem. By solving this problem efficiently and robustly with IRL, our approach automatically determines the optimal descent direction and step size, circumventing the need for demanding hyperparameter tuning and eliminating the numerical instabilities common in standard iterative solvers. We demonstrate that IRL enables shallow NQS architectures (with orders of magnitude fewer parameters) to consistently achieve extreme precision (1e-12 kcal/mol) in just 3 to 5 optimization steps. For the F2 molecule, this translates to an approximate 17,900-fold speed-up in total runtime compared to Adam. This work establishes IRL as a superior, robust, and efficient second-order optimization strategy for variational
quantum models, paving the way for the practical, high-fidelity application of neural networks in
quantum physics and chemistry.
Read the full abstract ▾
Instrumentation and Detectors
Simulation of the CYGNO Gaseous TPC Optical Readout
F.D. Amaro, R. Antonietti, E. Baracchini et al. (+41 more)
Gaseous Time Projection Chambers with Optical Readout are sensitive detectors suitable for 3D measurement of low-energy O(1 keV) particles and are proposed for detecting rare events such as Dark Matter particle interactions. The CYGNO collaboration is developing such a detector with a high spatial and energy resolution, leveraging an innovative optical readout system. A reliable simulation of the detector response is needed to properly assess the physics reach of this technique and to better understand the performance of the detector in the development phase. Such a simulation cannot entirely rely on existing software packages; indeed, none of the available tools is capable of properly and reliably treating the different phenomena occurring in the detector, from the primary interaction in the gas volume throughout the whole detector response model, including charge transport, light production and propagation, and the response of the optical sensors. In this paper, we present a modeling of the detector response tuned on the CYGNO Optical TPC case; a description of the method is reported together with comparisons with experimental data from the LIME prototype to demonstrate the simulation performances.
Read the full abstract ▾
All authors F.D. Amaro, R. Antonietti, E. Baracchini, L. Benussi, S. Bianco, C. Capoccia, M. Caponero, L.G.M de Carvalho, G. Cavoto, I.A. Costa, A. Croce, M. D'Astolfo, G. D'Imperio, G. Dho, E. Di Marco, J.M.F. dos Santos, D. Fiorina, F. Iacoangeli, Z. Islam, E. Kemp, H. P. Lima Jr, G. Maccarrone, R.D.P. Mano, D. J. G. Marques, G. Mazzitelli, P. Meloni, A. Messina, C.M.B. Monteiro, R.A. Nobrega, I.F. Pains, E. Paoletti, F. Petrucci, S. Piacentini, D. Pierluigi, D. Pinci, F. Renga, A. Russo, G. Saviano, P.A.O.C. Silva, N. J. C. Spooner, R. Tesauro, S. Tomassini, S. Torelli, D. Tozzi
Optics
Programmable calculus operations in electromagnetic space using space-time-coding metasurface
Hao Tian Shi, Lei Zhang, Rui Yuan Wu et al. (+7 more)
With the rapid advancement of metasurfaces and the increasing demand for programmable metasurfaces to simplify information systems, wave-based computation using metasurfaces has emerged as an attractive research topic. To facilitate the mathematical operations in electromagnetic (EM) space, here we propose a space-time coding metasurface (STCM) system capable of directly performing calculus operations on the spatial energy distributions of EM waves. By exploiting harmonic characteristics induced by time-varying coding, the responses of meta-atoms at specific harmonics can be flexibly controlled, which enables the metasurface system to address more complex tasks. Owing to its programmability, the STCM can dynamically switch functions in real time to accommodate different calculus tasks. To fully leverage the capability of STCM, we not only present the space-time coding sequences for differentiation and integration of EM waves, but also develop and numerically simulate the space-time coding sequences that can independently and simultaneously implement different calculus operations on the same incident EM waves. To experimentally validate the feasibility of the EM calculus operations, proof-of-concept experiments are conducted using a programmable 2-bit STCM. Good agreements among the theory, numerical simulations, and experiments confirm the feasibility of performing calculus operations in the EM space and demonstrate the broad application prospects of STCM in EM wave manipulations, wireless communications, and signal processing.
Read the full abstract ▾
All authors Hao Tian Shi, Lei Zhang, Rui Yuan Wu, Yi Ning Zheng, Xiao Qing Chen, Yuanzhe Li, Shi He, Jun Wei Wu, Qiang Cheng, Tie Jun Cui
Fluid Dynamics
Shuttlecock velocity decay after smash and slice shots in badminton
Eric Collet
This paper reports on the decay in shuttlecock velocity after smash and slice shots performed by elite and international players, based on the analysis of
videos captured on a badminton court with high-speed cameras. The trajectories of feather shuttlecocks show an exponential decay in velocity and an exponential increase in time-of-flight with distance, in accordance with the equation of motion of a shuttlecock subjected to high drag. The initial speed, which can exceed 500 km/h, is reduced by half every 3.35 m, depending on the physical parameters of the shuttlecock characterized by a speed index. The
videos show that plastic shuttlecocks, which are more resistant than feather shuttlecocks, deform at high speeds. The resulting decay of their drag coefficient with increasing speed makes them unsuitable for high-level play. The study also shows that the
spin induced by the slice shots of left-handed players or the reverse slice shots of right-handed players slows the shuttlecock down.
Read the full abstract ▾
Optics
Quaternion optical computing chip for parallel high-dimensional data processing
Songyue Liu, Qi Lu, Yuan Zhong et al. (+6 more)
Optical computing chips have emerged as a transformative computing technology due to their high computational density, low energy consumption, and compact footprint. While real- and complex-valued computing chips have been well developed, their fundamental limitations in representing high-dimensional data significantly constrain their applicability in modern signal processing. Quaternions enable direct operations on three- and four-dimensional data, powering high-dimensional processing in data analytics and artificial intelligence. Here we demonstrate a quaternion optical computing chip (QOCC) for the first time and
benchmark its performance in several typical application scenarios: three-dimensional point cloud processing, RGB chromatic transformation, and quaternion convolutional neural network for color image recognition. The QOCC harnesses high parallelism of light by wavelength-division multiplexing, processing high-dimensional data simultaneously through multiple optical wavelength channels. Compared to the electronic computing counterpart, our QOCC achieves higher computational fidelity (root mean square error < 0.035) and substantially reduced computational load (2/3 lower). It paves the way towards next-generation optical computing, overcoming the limitations of traditional computing systems in high-dimensional data processing.
Read the full abstract ▾
All authors Songyue Liu, Qi Lu, Yuan Zhong, Yuru Li, Meng Xiang, Zhaohui Li, Chao Lu, Yikai Su, Lu Sun
Applied Physics
Driven Dissipation and Stabilization of a Levitated Rotor with Multi-Day Coherence
Mehrdad M. Sourki, Wisdom Boinde, Gautham Anne et al. (+1 more)
We report the experimental observation of nonlinear mode-crossing dissipation and injection-locking-like stabilization in a milligram-scale diamagnetically levitated quartz cube. By optically driving the cube to rotation rate near 360 RPM, we observe that its angular velocity does not decay smoothly but instead decreases in discrete steps whenever the instantaneous rotation frequency crosses one of several higher-order mechanical modes. We observe rotational dissipation times on the order of a few days. When a weak counteracting radiation-pressure torque is applied, the system unexpectedly stabilizes at a constant rotation rate that persists for about two days, constituting the mechanical analogue of injection locking. Our results reveal a new regime of multimode nonlinear dynamics in low-dissipation levitated solids and establish diamagnetic levitation as a platform for exploring non-
Hamiltonian many-mode interactions and mechanically engineered nonlinear attractors and sensors.
Read the full abstract ▾
All authors Mehrdad M. Sourki, Wisdom Boinde, Gautham Anne, Mahdi Hosseini
Physics Education · Cross-listed from cond-mat.dis-nn
Simulating diffusion and disorder-induced localization in random walks and transmission lines
Jake S. Bobowski
We present two complementary simulations that lead to an exploration of Anderson localization, a phenomenon in which wave
diffusion is suppressed in disordered media by interference from multiple scattering. To build intuition, the first models the random walk of classical, non-interacting point-like particles, providing a clear analogy to the way disorder can limit transport. The second examines the propagation of an electromagnetic pulse through a one-dimensional, lossless transmission line with randomly varying propagation constant and characteristic impedance along its length, a system that captures the interference effects essential for true Anderson localization. We evaluate quantitative measures that reveal the transition from normal
diffusion to localization of particles in one case, and the exponential confinement of wave energy in the other. Together, these simulations offer a pair of accessible tools for investigating localization phenomena in an instructional setting.
Read the full abstract ▾
Plasma Physics
Overcoming the space-charge dilemma in low-energy heavy ion beams via a multistage acceleration lens system
M. Nishiura, T. Ido, M. Okamura et al. (+3 more)
Low-energy heavy-ion beams are fundamentally limited by severe space-charge divergence, which constrains the transportable beam current to a few microamperes in conventional electrostatic accelerators. This limitation is particularly critical for high-mass ions, where the generalized perveance increases rapidly because of their low velocity. Here, we demonstrate that this apparent space-charge limit can be overcome by shaping the electrostatic potential configuration of an existing multistage accelerator, thereby transforming the acceleration column itself into a combined acceleration-focusing column. By optimizing the interstage voltage configuration, a strong electrostatic lens effect is superimposed on the accelerating field to counteract space-charge-driven expansion. We formulate a generalized design framework that quantitatively maps the transport 'design window' in terms of beam current, ion mass, and acceleration voltage. For gold ions at 64 keV, this approach enables stable transport of beam currents exceeding 100 microA, more than an order of magnitude higher than the conventional limit. Numerical phase-space analysis shows that this improvement is achieved by prioritizing envelope control over emittance preservation, a trade-off intrinsic to space-charge-dominated regimes. Our results establish a universal and practical guideline for high-current heavy-ion beam transport, relevant to fusion
plasma diagnostics, ion implantation, and massive molecular ion applications.
Read the full abstract ▾
All authors M. Nishiura, T. Ido, M. Okamura, K. Ueda, A. Shimizu, H. Takubo
Fluid Dynamics · Cross-listed from cs.LG
Towards LLM-enabled autonomous combustion research: A literature-aware agent for self-corrective modeling workflows
Ke Xiao, Haoze Zhang, Runze Mao et al. (+2 more)
The rapid
evolution of large
language models (LLMs) is transforming artificial intelligence into autonomous research partners, yet a critical gap persists in complex scientific domains such as combustion modeling. Here, practical AI assistance requires the seamless integration of domain literature knowledge with robust execution capabilities for expertise-intensive tools such as computational fluid dynamics (CFD) codes. To bridge this gap, we introduce FlamePilot, an LLM
agent designed to empower combustion modeling research through automated and self-corrective CFD workflows. FlamePilot differentiates itself through an architecture that leverages atomic tools to ensure the robust setup and execution of complex simulations in both OpenFOAM and extended frameworks such as DeepFlame. The system is also capable of learning from scientific articles, extracting key information to guide the simulation from initial setup to optimized results. Validation on a public
benchmark shows FlamePilot achieved a perfect 1.0 executability score and a 0.438 success rate, surpassing the prior best reported
agent scores of 0.625 and 0.250, respectively. Furthermore, a detailed case study on Moderate or Intense Low-oxygen Dilution (MILD) combustion simulation demonstrates its efficacy as a collaborative research copilot, where FlamePilot autonomously translated a research paper into a configured simulation, conducted the simulation, post-processed the results, proposed evidence-based refinements, and managed a multi-step parameter study to convergence under minimal human intervention. By adopting a transparent and interpretable paradigm, FlamePilot establishes a foundational framework for AI-empowered combustion modeling, fostering a collaborative partnership where the
agent manages workflow orchestration, freeing the researcher for high-level analysis.
Read the full abstract ▾
All authors Ke Xiao, Haoze Zhang, Runze Mao, Han Li, Zhi X. Chen
Atomic Physics · Cross-listed from nlin.PS
Soliton Thouless pumping engineered by inter-site nonlinearities
Tao Jiang and Li-Chen Zhao
We study
soliton Thouless pumping in an extended diagonal Aubry-André-Harper model with on-site nonlinearities and inter-site nonlinearities. We show that the inter-site nonlinearities can make
solitons acquire anomalous transport distances far beyond the ones predicted by the linear bands, and the quantized displacements can be engineered well. We uncover that nonlinear instabilities require lower limits on sweeping rates for
soliton pumping, challenging the common notion that slower modulation enables a more favorable realization of topological transport. The nonlinear interactions between
solitons make multi-
soliton pumping generally lack the robustness characteristic of Thouless pumping as linear systems. Our results provide many possibilities to engineer topological pumping by nonlinearities, and further make a step for applications of
soliton pumping.
Read the full abstract ▾
Applied Physics
Edge Truncation Effect Suppression of Ultrawideband Phased Arrays for Radar Application
Chenglong Fan, Shi-Wei Qu, Shiwen Yang et al. (+1 more)
This letter presents a novel, effective method to suppress the edge truncation effect of ultrawideband tightly coupled dipole linear arrays. To restrain the edge truncation effect within an ultrawideband operating band, a new type of T-shaped metal strip with a resistor is further loaded on the array edges apart from extending the length of the overlapping patches. Besides, the excitation phase of the elements at the array edges is optimized. Full-wave simulation results show that the active standing wave standing ratio of the 2 x 16 tightly coupled dipole linear arrays using the proposed method is significantly optimized to less than 3.5 within a 5:1 [(1.2 to 6) GHz] bandwidth, while scanning up to +/-60{\deg} in the E-plane. The effectiveness of the proposed method is experimentally verified by a 2 x 16 linear array prototype.
Read the full abstract ▾
All authors Chenglong Fan, Shi-Wei Qu, Shiwen Yang, Jun Hu
Medical Physics
Optimization of Magnetic Milli-Spinner for Robotic Endovascular Intervention
Lu Lu, Luca Higgins, Jack Bernardo et al. (+1 more)
Vascular diseases such as atherosclerosis, thrombosis, and aneurysms can lead to life-threatening medical events. Conventional catheter- or guidewire-based interventional devices often struggle to navigate through highly tortuous vasculature. The recently developed multifunctional
magnetic milli-spinner offers a promising wireless solution by integrating a central through-hole and side slits into a cylindrical body with helical fins, enabling rapid and stable
navigation for clot debulking, targeted drug delivery, and aneurysm treatment. Here, we combine computational fluid dynamics simulations with experimental validation to optimize the milli-spinner's structural design for high-velocity propulsion and high-efficiency clot debulking in tubular flow environments. By systematically investigating the effects of through-hole radius, fin number, fin helical angle, and slit dimension on propulsion performance, the optimized milli-spinner achieves swimming velocities of 55 cm/s (175 body lengths per second) in saline water and 44 cm/s (140 body lengths per second) in a fluid with viscosity (3.5 mPa.s) comparable to that of arterial blood at high shear rates, far exceeding existing untethered
magnetic robots in tubular environments (less than 80 body lengths per second). This exceptional velocity enables stable upstream operation against strong physiological flows representative of major arteries and veins, establishing the milli-spinner as a robust untethered
navigation platform for operation in high-flow, tortuous vasculature.
Read the full abstract ▾
All authors Lu Lu, Luca Higgins, Jack Bernardo, Ruike Renee Zhao