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Physics Physics

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Sunday 23 November

Fluid Dynamics

End-pinching and inertial-capillary reopening in viscoplastic ligaments at low Ohnesorge number

Shu Yang, Fahim Tanfeez Mahmood and C. Ricardo Constante-Amores

Capillary retraction of liquid ligaments is well understood for Newtonian fluids, whereas viscoplastic effects remain comparatively unexplored. Here, we consider Herschel-Bulkley fluids, which incorporate both yield stress and shear-rate-dependent viscosity, thereby introducing a spatially varying effective viscosity that is absent in simpler yield-stress models (e.g., Bingham models). We focus on the low-viscosity regime, where droplet detachment in Newtonian fluids is controlled by the end-pinching mechanism. Using fully resolved axisymmetric simulations, we show that viscoplasticity and shear-rate-dependent rheology reorganize the routes by which a retracting ligament may pinch off, escape break-up or stay motionless due to large yield stress. We identify two distinct routes by which a retracting Herschel-Bulkley ligament can escape end-pinching. In the shear-thickening regime, increased local viscosity during neck thinning leads to larger vorticity detachment from the curved neck, which opposes the capillary singularity. In the strongly shear-thinning regime, reopening is governed by curvature-induced pressure gradients. We show that this latter mechanism persists in the Newtonian limit of vanishing viscosity, yielding a purely inertial-capillary pathway for reopening. While previous Newtonian studies report end-pinching down to Ohnesorge number $Oh_K \approx 10^{-4}$, suggesting break-up as the asymptotic low-viscosity outcome (Anthony et al. 2019), our results demonstrate that a purely inertial-capillary reopening mechanism can arise as $Oh_K \to 0$, indicating that end-pinching is not the route in the inviscid limit.
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Optics

Topological interface modes in aperiodic subwavelength resonator chains

Habib Ammari, Jiayu Qiu and Alexander Uhlmann

We consider interface modes in block disordered subwavelength resonator chains in one dimension. Based on the capacitance operator formulation, which provides a first-order approximation of the spectral properties of dimer-type block resonator systems in the subwavelength regime, we show that a two-fold topological characterization of a block disordered resonator chain is available if it is of dominated type. The topological index used for the characterization is a generalization of the Zak phase associated with one-dimensional chiral-symmetric Hamiltonians. As a manifestation of the bulk-edge correspondence principle, we prove that a localized interface mode occurs whenever the system consists of two semi-infinite chains with different topological characters. We also illustrate our results from a dynamic perspective, which provides an explicit geometric picture of the interface modes, and finally present a variety of numerical results to complement the theoretical results.
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Optics

Attosecond-resolved quantum fluctuations of light and matter

Matan Even Tzur, Chen Mor, Noa Yaffe et al. (+10 more)

Until recently, attosecond optical spectroscopy and quantum optics evolved along non-overlapping directions. In attosecond science, attosecond pulses have been regarded as classical waves, applied to probe electron dynamics on their natural time scale. Here, we transfer fundamental concepts of quantum optics into attosecond physics, enabling control of both the properties of the XUV attosecond pulses and the quantum fluctuations of matter on attosecond time scales. By combining bright squeezed vacuum (BSV) with a strong laser field to drive high-harmonic generation, we transfer the quantum properties of the BSV onto the resulting XUV attosecond pulses. Applying advanced attosecond interferometry, we reconstruct the quantum state of the XUV high harmonics and their associated attosecond pulses with attosecond precision. Finally, we resolve the squeezing of the electron's wavepacket during one of the most fundamental strong-field phenomena - field induced tunneling. The ability to measure and control quantum correlations in both electrons and XUV attosecond pulses establishes a foundation for attosecond quantum electrodynamics, manipulating the quantum state of electrons and photons with sub-cycle precision.
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All authors Matan Even Tzur, Chen Mor, Noa Yaffe, Michael Birk, Andrei Rasputnyi, Omer Kneller, Ido Nisim, Ido Kaminer, Maria Chekhova, Michael Krueger, Misha Ivanov, Nirit Dudovich, Oren Cohen

Optics · Cross-listed from nlin.PS

Stable multipole solitons in defocusing saturable media with an annular trapping potential

Xiaoli Lang, Boris A. Malomed and Liangwei Dong

We systematically investigate the existence, stability, and propagation dynamics of multipole-mode (necklace-shaped) solitons in the two-dimensional model of an optical medium with the defocusing saturable nonlinearity and an annular potential trough. Various families of stable multipole solitons trapped in the trough, from dipole, quadrupole, and octupole ones to multi-lobe complexes, are found. The existence domain remains invariant with the increase of the potential's depth. Solitons with a large number N of lobes are stable in a wide parameter region, up to N=48 and even farther. Actually, stable multipole solitons of an arbitrarily high order N can be found, provided that the trough's radius is big enough. The power of stable multipoles is essentially larger in comparison to previously studied models. It is demonstrated analytically and numerically that the application of a phase torque initiates stable rotation of the multipole complexes. Thus, we put forward an effective scheme for the stabilization of multipole solitons with an arbitrary high number of lobes, including rotating ones, which offers new possibilities for manipulating complex light beams.
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Medical Physics

Comprehensive Multimodal and Multiscale Analysis of Alzheimer Disease in 5xFAD Mice: Optical Spectroscopies, TEM, Neuropathological, and Behavioral Investigations

Dhruvil Solanki, Ishmael Apachigawo, Sazzad Khan et al. (+8 more)

Alzheimer disease (AD) is considered one of the leading causes of death in the United States, and there is no effective cure for it. Understanding the neuropathological mechanisms underlying AD is essential for identifying early, reliable biomarkers and developing effective therapies. In this paper, we report on a comprehensive multimodal study of AD pathology using the 5xFAD mouse model. We employed light-scattering techniques, Partial Wave Spectroscopy (PWS) and Inverse Participation Ratio (IPR), to detect nanoscale structural alterations in brain tissues, nuclear components, and mitochondria. To support the light-scattering experiments, behavior, and histopathological studies were conducted. These analyses revealed significant increases in structural heterogeneity and mass density fluctuations in the brains of 5xFAD mice compared with Non-transgenic controls. Behavioral assessment demonstrated memory impairment in 5xFAD mice, reflected by a reduced recognition index. Histopathological analysis further revealed increased amyloid beta plaques and microglia activation in the hippocampus and cortex of 5xFAD mice compared with Non-transgenic controls. An increase in structural disorder within brain tissues can be attributed to higher mass density fluctuations, likely arising from macromolecular rearrangement driven by amyloid beta aggregation and neuroinflammatory responses as the disease progresses. Our findings suggest that PWS and IPR-derived metrics provide sensitive biophysical indicators of early cellular and subcellular disruption, offering potential as quantitative biomarkers for the detection and progression of AD.
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All authors Dhruvil Solanki, Ishmael Apachigawo, Sazzad Khan, Santanu Maity, Fatemah Alharthi, Samia Nasim, Mohammad Alizadeh Poshtiri, Fnu Sweety, Jiangfeng Xiao, Mohammad Moshahid Khan, Prabhakar Pradhan

Instrumentation and Detectors

Radiation tolerance test and damage of single-crystal CVD Diamond sensor under high fluence particles

Jialiang Zhang, Shuo Li, Yilun Wang et al. (+7 more)

Single-crystal chemical vapor deposition (CVD) diamond is a promising material for radiation detectors operating in extreme environments, owing to its outstanding radiation hardness. As nuclear and high-energy physics applications demand particle detectors that withstand higher radiation fluences, understanding the damage thresholds and degradation mechanisms of diamond-based detectors is essential. In this study, single-crystal CVD diamond sensors were exposed to fast neutron irradiation at fluences up to $3.3\times10^{17}$ ${n/cm^2}$. Modules exhibited stable output confirming potential for application in future high-dose radiation environments. The dominant defects were identified as point defects including <100> self interstitials, vacancies, and lattice disorder. Macroscopic defects including nanocavities and cracks were observed with areal densities approaching $10^7$ $cm^{-2}$. The impact of 100 MeV proton irradiation on diamond detector response was quantified by extracting a damage constant of $k^{100 MeV}_{proton}=(1.452\pm0.006)\times10^{-18}cm^2/(p\cdot\mu m)$ from a linear carrier drift degradation model. The mean free path of carriers was found to exhibit saturation behavior beyond a fluence of $4\times10^{16}$ ${p/cm^2}$ under 100 MeV proton irradiation. Monte Carlo together with molecular dynamics simulations were performed to assess irradiation induced defect and its influence on carrier transport. By considering saturation effects and defect-interaction corrections, we develop an enhanced carrier-drift degradation model that accurately captures detector response under high-dose irradiation. Furthermore, the simulation framework was applied to evaluate damage induced by protons and pions on diamond at various energies, yielding results that show better agreement with experimental data than conventional NIEL based estimates.
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All authors Jialiang Zhang, Shuo Li, Yilun Wang, Shuxian Liu, Guojun Yu, Zifeng Xu, Lifu Hei, Fanxiu Lv, Lei Zhang, Ming Qi

General Physics

Discrete Action, Graph Evolution, and the Hierarchy of Symmetries: A Rigorous Construction of Temporal Layers $C1 \to C2 \to C3 \to C4$

Medeu Abishev and Daulet Berkimbayev

Postulating a minimal discrete quantum of action $S=\hbar$ and a simple rule for the growth of an oriented graph, we construct a strict hierarchy of temporal layers $C N$ with discrete periods $\tau_N=N\hbar/E$. Each layer is specified by its configuration space, symplectic structure, update rule, and emergent symmetry. At $C1$ the state is represented by a single oriented edge with $U(1)$ phase $e^{i E t/\hbar}$. The transition $C1 \to C2$ splits the edge into two independent flows, which yields canonical pairs $(x_a,p_a)$, local $U(1)$ invariance, and an effective $(2{+}1)$ metric with signature $(+--)$. The closure $C2 \to C3$ produces $SU(3)$ connections and an Einstein-Yang-Mills type action. We show that these structures follow from discrete-action principles, and that stochastic graph growth naturally provides mechanisms for decoherence and spontaneous symmetry breaking.
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Fluid Dynamics

Field Inversion Machine Learning for Time-Resolved Unsteady Flows in Airfoil Dynamic Stall

Zilong Li, Lean Fang, Anupam Sharma et al. (+1 more)

While many existing machine learning studies have focused on augmenting Reynolds averaged Navier Stokes (RANS) turbulence models for steady or time averaged unsteady flows, this paper takes a first step toward extending such augmentation to time resolved unsteady flows. An unsteady field inversion and machine learning (FIML) method is developed, in which a temporally evolving correction field (beta) is incorporated into the production term of a RANS turbulence model. The inverse problem is solved by optimizing the spatial temporal distribution of beta to minimize the regularized prediction errors. The resulting optimized beta field is then used to train a multi layer neural network that learns the time dependent relationship between local flow features and beta. The approach is demonstrated using the unsteady flow over a NACA0012 airfoil undergoing dynamic stall. Results show that the unsteady FIML model, trained using only the time series of drag data at a given pitch rate, can accurately reproduce the spatial temporal evolution of reference drag, lift, pitching moment, surface pressure, and velocity fields at both identical and different pitch rates. The unsteady FIML is integrated into the open source DAFoam framework, enabling a pathway toward developing accurate and generalizable RANS turbulence models for time resolved unsteady flows.
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All authors Zilong Li, Lean Fang, Anupam Sharma, Ping He

Physics Education · Cross-listed from cs.AI

Developing an AI Course for Synthetic Chemistry Students

Zhiling Zheng

Artificial intelligence (AI) and data science are transforming chemical research, yet few formal courses are tailored to synthetic and experimental chemists, who often face steep entry barriers due to limited coding experience and lack of chemistry-specific examples. We present the design and implementation of AI4CHEM, an introductory data-driven chem-istry course created for students on the synthetic chemistry track with no prior programming background. The curricu-lum emphasizes chemical context over abstract algorithms, using an accessible web-based platform to ensure zero-install machine learning (ML) workflow development practice and in-class active learning. Assessment combines code-guided homework, literature-based mini-reviews, and collaborative projects in which students build AI-assisted workflows for real experimental problems. Learning gains include increased confidence with Python, molecular property prediction, reaction optimization, and data mining, and improved skills in evaluating AI tools in chemistry. All course materials are openly available, offering a discipline-specific, beginner-accessible framework for integrating AI into synthetic chemistry training.
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Chemical Physics

Analytical Excited-State Gradients and Derivative Couplings in TDDFT with Minimal Auxiliary Basis Set Approximation and GPU Acceleration

Zhichen Pu, Xiaojie Wu, Yuanheng Wang et al. (+5 more)

Calculating excited-state gradients and derivative couplings using time-dependent density functional theory (TDDFT) remains a computationally demanding task. An efficient variant, TDDFT with resolution of the identity and a minimal auxiliary basis (TDDFT-ris), has been developed to accelerate excitation energy calculations. However, the formulation and implementation of analytical derivatives for this method have not yet been reported. In this work, we present an implementation of analytical excited-state gradients and derivative couplings within the TDDFT-ris framework. Benchmark calculations on medium-sized organic molecules demonstrate a two- to three-fold speedup for both gradients and derivative couplings compared to standard TDDFT. The accuracy of the TDDFT-ris approach is assessed for gradient-dependent applications, including geometry optimizations, emission energy calculations, and the localization of minimum-energy crossing points. Overall, the TDDFT-ris method provides reliable approximations for most cases, with noticeable errors mainly occurring in derivative couplings between nearly degenerate states.
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All authors Zhichen Pu, Xiaojie Wu, Yuanheng Wang, Cheng Fan, Wen Yan, Zehao Zhou, Yi Qin Gao, Qiming Sun

Optics

Roadmap: Emerging Platforms and Applications of Optical Frequency Combs and Dissipative Solitons

Dmitry Skryabin, Arne Kordts, Richard Zeltner et al. (+31 more)

The discovery of optical frequency combs (OFCs) has revolutionised science and technology by bridging electronics and photonics, driving major advances in precision measurements, atomic clocks, spectroscopy, telecommunications, and astronomy. However, current OFC systems still require further development to enable broader adoption in fields such as communication, aerospace, defence, and healthcare. There is a growing need for compact, portable OFCs that deliver high output power, robust self-referencing, and application-specific spectral coverage. On the conceptual side, progress toward such systems is hindered by an incomplete understanding of the fundamental principles governing OFC generation in emerging devices and materials, as well as evolving insights into the interplay between soliton and mode-locking effects. This roadmap presents the vision of a diverse group of academic and industry researchers and educators from Europe, along with their collaborators, on the current status and future directions of OFC science. It highlights a multidisciplinary approach that integrates novel physics, engineering innovation, and advanced researcher training. Topics include advances in soliton science as it relates to OFCs, the extension of OFC spectra into the visible and mid-infrared ranges, metrology applications and noise performance of integrated OFC sources, new fibre-based OFC modules, OFC lasers and OFC applications in astronomy.
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All authors Dmitry Skryabin, Arne Kordts, Richard Zeltner, Ronald Holzwarth, Victor Torres-Company, Tobias Herr, Fuchuan Lei, Qi-Fan Yang, Camille-Sophie Brès, John F. Donegan, Hai-Zhong Weng, Delphine Marris-Morini, Adel Bousseksou, Markku Vainio, Thomas Bunel, Matteo Conforti, Arnaud Mussot, Erwan Lucas, Julien Fatome, Yuk Shan Cheng, Derryck T. Reid, Alessia Pasquazi, Marco Peccianti, M. Giudici, M. Marconi, A. Bartolo, N. Vigne, B. Chomet, A. Garnache, G. Beaudoin, I. Sagnes, Richard Burguete, Sarah Hammer, Jonathan Silver

Computational Physics

Generation of Granular Deposition Interfaces using conditional Generative Adversarial Network (cGAN)

Seyed Feyzelloh Ghavami Mirmahalle, Seyed Ehsan Nedaaee Oskoee and Maniya Maleki

This work aims at generating 1D interface profiles of granular deposition by a conditional generative adversarial network (cGAN). Our cGAN model employs a U-Net generator and a ResNet discriminator that, in competition with each other, produce granular interfaces. The network is trained on dynamic simulation data from the LAMMPS granular package. Different fluids (water, acetone, and hexane) were used for the medium of the deposition cell to check the model performance in different growing conditions. The same model with the same hyperparameters was trained on data from different media separately. The ML-generated interfaces are compared with those of dynamic simulations, and a large number of interfaces are then produced to obtain more stable statistical properties of granular deposition. This way, the computationally extensive molecular dynamics simulation is substituted by the AI model. The statistical trend of interface growth is diagrammed, and the generated interfaces are also analyzed in terms of statistical features. Keywords: Conditional Generative Adversarial Networks, ResNet, U-Net, Granular Deposition, Interface Growth.
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Saturday 22 November

Optics

Influence of the radial number of Laguerre-Gaussian vortex beams on their propagation in a turbulent medium

D. D. Reshetnikov and A. S. Losev

The paper considers the propagation of Laguerre-Gaussian beams in a turbulent gas medium. As demonstrated by numerical modelling and the decomposition of Laguerre-Gaussian modes according to the basis of orthogonal Zernike polynomials, disparities in the stability of Laguerre-Gaussian modes with differing radial and azimuthal numbers are evident. The demonstration is made of the minimization of the distortion of the transverse beam profile with an increase in the radial number.
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Space Physics · Cross-listed from cs.DC

Towards a future space-based, highly scalable AI infrastructure system design

Blaise Agüera y Arcas, Travis Beals, Maria Biggs et al. (+6 more)

If AI is a foundational general-purpose technology, we should anticipate that demand for AI compute – and energy – will continue to grow. The Sun is by far the largest energy source in our solar system, and thus it warrants consideration how future AI infrastructure could most efficiently tap into that power. This work explores a scalable compute system for machine learning in space, using fleets of satellites equipped with solar arrays, inter-satellite links using free-space optics, and Google tensor processing unit (TPU) accelerator chips. To facilitate high-bandwidth, low-latency inter-satellite communication, the satellites would be flown in close proximity. We illustrate the basic approach to formation flight via an 81-satellite cluster of 1 km radius, and describe an approach for using high-precision ML-based models to control large-scale constellations. Trillium TPUs are radiation tested. They survive a total ionizing dose equivalent to a 5 year mission life without permanent failures, and are characterized for bit-flip errors. Launch costs are a critical part of overall system cost; a learning curve analysis suggests launch to low-Earth orbit (LEO) may reach $\lesssim$\$200/kg by the mid-2030s.
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All authors Blaise Agüera y Arcas, Travis Beals, Maria Biggs, Jessica V. Bloom, Thomas Fischbacher, Konstantin Gromov, Urs Köster, Rishiraj Pravahan, James Manyika

Fluid Dynamics

Hybrid RANS-LES simulation of transverse fuel injection in a Mach-10 scramjet engine

Nick Plewacki, Benjamin Kale, Manu Kamin et al. (+1 more)

Hypersonic flight poses unique propulsion challenges, requiring engines that maintain thrust, efficiency, and stability across a wide range of operating conditions. These engines must transition smoothly between flight regimes and altitudes. Scramjets (supersonic combustion ramjets) play a key role in addressing these challenges. Recent advancements in high-fidelity computational fluid dynamics (CFD) tools allow researchers to explore novel designs and improve the feasibility of hypersonic travel. In this work, we analyze a radical-farming type scramjet engine mounted at the University of Queensland's T4 Wind Tunnel at Mach 10. We use the Improved Delayed Detached Eddy Simulation (IDDES) model, which combines Reynolds-Averaged Navier-Stokes (RANS) and Large Eddy Simulation (LES) in different flow regions. A novel integrated modeling strategy is introduced, coupling the inlet, fuel injectors, combustor, and nozzle for full-scale engine analysis. Hydrogen combustion is modeled using a Finite Rate Chemistry (FRC) approach with a 12-species, 27-reaction mechanism to capture shock-induced chemical kinetics across equivalence ratios of $\phi = 0.5$ to $0.9$. The Takeno flame index analysis reveals multiple combustion regimes, with ignition occurring in the partially premixed regime. This is supported by Chemical Explosive Mode Analysis (CEMA), which identifies regions of high chemical sensitivity, correlating with observed hot pockets and providing insights into autoignition and flame stabilization mechanisms. The combination of IDDES and FRC improves the transport of hydrogen to hot pockets, producing combustion patterns that match experimental results. This work establishes a framework to address critical challenges in future air-breathing propulsion systems.
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All authors Nick Plewacki, Benjamin Kale, Manu Kamin, Luis Bravo

Optics

Multi-port programmable silicon photonics using low-loss phase change material Sb$_2$Se$_3$

Thomas W. Radford, Idris A Ajia, Latif Rozaqi et al. (+7 more)

Reconfigurable photonic devices are rapidly emerging as a cornerstone of next generation optical technologies, with wide ranging applications in quantum simulation, neuromorphic computing, and large-scale photonic processors. A central challenge in this field is identifying an optimal platform to enable compact, efficient, and scalable reconfigurability. Optical phase-change materials (PCMs) offer a compelling solution by enabling non-volatile, reversible tuning of optical properties, compatible with a wide range of device platforms and current CMOS technologies. In particular, antimony tri-selenide ($\text{Sb}_{2}\text{Se}_{3}$) stands out for its ultra low-loss characteristics at telecommunication wavelengths and its reversible switching. In this work, we present an experimental platform capable of encoding multi-port operations onto the transmission matrix of a compact multimode interferometer architecture on standard 220~nm silicon photonics using in-silico designed digital patterns. The multi-port devices are clad with a thin film of $\text{Sb}_{2}\text{Se}_{3}$, which can be optically addressed using direct laser writing to provide local perturbations to the refractive index. A range of multi-port geometries from 2$\times$2 up to 5$\times$5 couplers are demonstrated, achieving simultaneous control of up to 25 matrix elements with programming accuracy of 90% relative to simulated patterns. Patterned devices remain stable with consistent optical performance across the C-band wavelengths. Our work establishes a pathway towards the development of large scale PCM-based reconfigurable multi-port devices which will allow implementing matrix operations on three orders of magnitude smaller areas than interferometer meshes.
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All authors Thomas W. Radford, Idris A Ajia, Latif Rozaqi, Priya Deoli, Xingzhao Yan, Mehdi Banakar, David J Thomson, Ioannis Zeimpekis, Alberto Politi, Otto L. Muskens

Fluid Dynamics

A Modified Suspension-Balance Model for Deformable Particle Suspensions: Application to Blood Flows with Cell-Free Layer

Hugo A Castillo-Sánchez, Weston Ortiz, Richard Martin et al. (+3 more)

We propose a modified suspension balance model (SBM) for the flow of red blood cells (RBCs) and other deformable particle suspensions in confined geometries. Specifically, the method includes the hydrodynamic lift force generated by deformable particles interacting with walls leading to a cell-free layer. The lift force is added to the SBM to drive RBCs migrating away from the wall. Using the modified SBM (MSBM), we simulate blood flows through microvascular channels and tubes. The method is able to capture the transient development of the cell-free layer (CFL) and the corresponding hematocrit and velocity profiles with the development of the CFL. The CFL thickness and hemorheological hallmarks in microcirculation, such as the Fahraeus Effect and the Fahraeus-Linqvist Effect, are captured in good agreement with existing experimental and direct numerical results of blood flows. This work establishes a novel continuum computational framework that can efficiently capture the microstructural heterogeneity and non-Newtonian flow behavior of concentrated deformable particle suspensions under confinement.
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All authors Hugo A Castillo-Sánchez, Weston Ortiz, Richard Martin, Rukiye Tuna, Rekha R Rao, Z Leonardo Liu

Physics and Society

A Mathematical Model of Opinion Dynamics with Application to Vaccine Denial

Daniel Cicala, Yi Jiang, Jane HyoJin Lee et al. (+2 more)

Public health outcomes can be heavily influenced by the landscape of public opinion; hence, it is important to understand how that landscape changes over time. For one, opinions on public health issues are responsive to official pronouncements, whether from the governmental or professional medical establishments. Additionally, in today's world of high speed communication, opinion can also be highly responsive to the broadcast opinions of "influencers" whose large numbers of followers assure them of a broad reach. To understand the opinion landscape in a general sense, we develop an ordinary differential equation model for opinion change that is based primarily on attraction to the opinions of prominent sources. The individual opinion change model is then used to develop a Fokker-Planck-type partial differential equation model for the overall opinion landscape. This model is shown to have a stable equilibrium solution, and the dependence of the equilibrium solution on key model parameters is illustrated with examples based on opinion regarding vaccination.
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All authors Daniel Cicala, Yi Jiang, Jane HyoJin Lee, Kristin Kurianski, Glenn Ledder

Fluid Dynamics

Measuring fluxes between wave and geostrophic features in rotating non-hydrostatic flows with variable stratification

Jeffrey J. Early, Gerardo Hernández-Dueñas, Leslie M. Smith et al. (+2 more)

A challenge in physical oceanography is quantifying the energy content of waves and balanced flows and the fluxes that connect these reservoirs with their sources and sinks. Methodological limitations have prevented decompositions for realistic flows with non-hydrostatic motions and variable stratification. We present a framework that separates the flow into wave and geostrophic components using the principle that waves have no Eulerian available potential vorticity signature. Starting from new expressions for available energy and potential vorticity conservation, we construct a basis of wave and geostrophic modes, complete and orthogonal with respect to quadratic approximations of the conserved quantities. Using the resulting non-hydrostatic projection operators, the nonlinear equations of motion are expressed as coupled wave and geostrophic equations, quantifying cascade and transfer fluxes of wave and geostrophic energy. We apply the method to non-hydrostatic mid-ocean simulations with geostrophic mean-flow, near-inertial, and tidal forcing. From these experiments, we construct source-sink-reservoir diagrams for exact and quadratic fluxes, quantifying the fluxes between geostrophic and wave components. Because the cascade fluxes obey total energy conservation, we construct energy flow diagrams within the wave and geostrophic reservoirs and diagnose nonlocal transfers. The simulations show a geostrophic inverse cascade, a forward wave cascade, and a direct transfer of geostrophic to wave energy, with no indication of a forward geostrophic cascade. The mean-flow-only simulation shows weak spontaneous wave emission during spin-up, which diminishes to zero. Finally, we evaluate the decomposition by comparing linearized and fully conserved available potential vorticity, finding that errors become significant at scales below 15\,km.
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All authors Jeffrey J. Early, Gerardo Hernández-Dueñas, Leslie M. Smith, Cimarron Wortham, M.-Pascale Lelong

Applied Physics · Cross-listed from cond-mat.mtrl-sci

Tuning Breakdown-to-Coercive Field Ratio in Ultra-Thin Al1-xScxN Films via Reactive Nitrogen Atmosphere

Yinuo Zhang, Walter J. Smith, Giovanni Esteves et al. (+3 more)

Al1-xScxN has attracted significant interest due to its large remnant polarization and low processing temperature when compared to other ferroelectric material systems. However, device dielectric failure before ferroelectric switching remains a critical limitation for AlScN-based memory devices. With the continuing trend toward device miniaturization, expanding the operating window is essential for next-generation memory development. In this work, we optimized the breakdown field (EBD) and coercive field (EC) in ultra-thin Al1-xScxN films by controlling defect density via adjustment of nitrogen gas flow during sputter deposition. The characteristic breakdown field, EBD, was evaluated using Weibull statistics, yielding optimal characteristic breakdown fields of 12.47 MV/cm (EBD+) and -12.63 MV/cm (EBD-) for samples deposited under 27.5 sccm N2 flow. The minimum EC was achieved at a nitrogen flow of 25 sccm and increased for higher gas flows, a trend that is opposite to previous reports in much thicker films. The highest EBD over EC ratio of 2.25 occurred at 27.5 sccm, effectively expanding the operational window. Using a combination of X-ray diffraction and photoluminescence spectroscopy to study changes in crystal orientation and defects, device performance can be tuned by controlling the point defect concentration in the ultra-thin film via adjusting the sputtering N2 process gas flow rate.
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All authors Yinuo Zhang, Walter J. Smith, Giovanni Esteves, Eric A. Stach, Thomas E. Beechem, Roy H. Olsson III

Physics and Society

Evaluating Parametric Car-Following Models in Naturalistic Congestion: Insights in Driver Behavior and Model Limitations

Huaidian Hou, Arpan Kusari and Brian T.W. Lin

Car-Following is a broadly studied state of driving, and many modeling approaches through various heuristics and engineering methods have been proposed. Congestion is a common traffic phenomenon also widely investigated, both from macroscopic and microscopic perspectives. Yet, current literature lack a unified evaluation of Car-Following models with naturalistic congestion data. This paper compares the performance of five parametric Car-Following models: IDM, ACC, Gipps, OVM, and FVDM, using a rich naturalistic congestion dataset. The five models in question is found to perform similarly when optimized over the same RMSNE metric. Sub-sequences of Car-Following where models noticeably disagree with driver behavior is noticed and separately investigated. A review of corresponding front-facing and cabin video data reveals distraction and driving with momentum as potential reasons for model-reality difference. We further show that drivers often employ coasting and idle creep under Car-Following in different speed ranges, which existing parametric models fail to capture. Finally, time-series clustering is performed and analysis of result clusters align with empirical findings. Our findings highlight the necessity to consider vehicle dynamical properties including coasting and idle creep abilities, which drivers take extensive use of under low speed congestions. Future research could integrate such parameters with traditional parametric models to improve congestion modeling performance. We also suggest future research into investigating temporal correlations between clustered blocks to reveal behavioral transition patterns exhibited by drivers in congestions. Source code for this study can be found on Github.
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2511.18135 · 22 Nov · Presented at the 104th Transportation Research Board Annual Meeting, Washington D.C., 2025. Paper on TRB Archive: https://annualmeeting.mytrb.org/FileUpload/FullPaper?ID=61095&SessionID=23204&ConferenceID=13. Source code available at https://github.com/DanielHou315/Car_Following_Eval

Abstract PDF $DATA ×1$VID ×1

Physics and Society

Open networks in discrete time: Passing vs blocking behavior

Amirhossein Nazerian, MAlbor Asllani, Melvyn Tyloo et al. (+1 more)

This paper presents a unified framework for analyzing the input-output behavior of discrete time complex networks viewed as open systems. Importantly, we focus on systems that are inherently modeled in discrete time-such as opinion dynamics, Markov chains, diffusion on networks, and population models-reflecting their natural formulation in many real-world contexts. By an open network, we mean one that is coupled to its environment, through both external signals that are received by designated input nodes and response signals that are released back into the environment via a separate set of output nodes. We develop a general framework for characterizing whether such networks amplify (pass) or suppress (block) the external inputs. Our approach combines the transfer function of the network with the discrete time controllability Gramian, using the H2-norm to quantify signal amplification. We introduce a computationally efficient network index based on the Gramian trace and eigenvalues, enabling scalable comparisons across network topologies. Application of our method to a broad set of empirical networks, spanning biological, technological, and ecological domains, uncovers consistent structural signatures associated with passing or blocking behavior. These findings shed light on how the network architecture and the particular selection of input and output nodes shape information flow in real-world systems, with broad implications for control, signal processing, and network design.
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All authors Amirhossein Nazerian, MAlbor Asllani, Melvyn Tyloo, Francesco Sorrentino

Fluid Dynamics

Electroosmotic lubrication flow in constricted microchannels with a compliant wall and DLVO interactions

Subhajyoti Sahoo and Ameeya Kumar Nayak

We develop a nonlinear model for electroosmotic transport in a constricted microchannel with a compliant lower wall, with applications to soft microfluidics, bio-inspired sensing, and energy harvesting. The formulation couples electroosmotic slip-driven flow under a globally constrained electric field with pressure-driven lubrication and elastic wall deformation, modeled as a clamped Kirchhoff-Love plate. Short-range intermolecular stresses are incorporated through an extended Derjaguin-Landau-Verwey-Overbeek framework combining electrostatic double-layer repulsion and van der Waals attraction, enabling us to probe the nonlinear coupling between intermolecular forces, wall deformation, and electroosmotic flow in compliant microchannels. The flow is governed by six nondimensional parameters: wall compliance, geometric curvature, electrostatic and van der Waals strengths, scaled Debye length, and Dukhin number. Asymptotic analysis clarifies the role of these parameters in limiting regimes. In the stiff-wall limit, electroosmotic slip acts as a uniform offset to the pressure-driven flow. Fully coupled spectral collocation simulations confirm the asymptotic predictions and capture nonlinear feedback between pressure, deformation, and intermolecular stresses. Three regimes emerge: a stiff-wall regime with negligible deformation, a deformation-limited regime in which elastic narrowing strongly suppresses flux, and a repulsion-limited regime where DLVO forces cap wall deflection and prevent collapse. These results show how elasticity, geometry, and molecular forces jointly regulate electroosmotic lubrication and provide scaling rules for the design of compliant electrokinetic channels operating under nanometric confinement.
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Optics

Mesh of Spatiotemporal Optical Vortices with Programmable Intensity Nulls

Jinxin Wu, Dan Wang, Qingqing Liang et al. (+4 more)

Light carrying transverse orbital angular momentum (T-OAM) in the form of spatiotemporal optical vortices (STOVs) is opening new degrees of freedom for structured light manipulation. Such spatiotemporal wavepackets hold significant potential for optical trapping, analog optical computing, studying photonic symmetry and topology, among others. Up to now, synthesizing of such vortices is limited in one dimension, either in temporal or spatial domain. In this work, we propose and experimentally demonstrate a two-dimensional flexible mesh of spatiotemporal optical vortices (M-STOV) with programmable intensity nulls, and analyze their diffraction patterns for detection. Furthermore, we extend the spectral range of M-STOV via second-harmonic generation while examining the transfer of OAM in this nonlinear process. This study establishes a foundational framework for designing higher dimensional spatiotemporal vortex fields and promises a high-capacity information carrier based on ST optical vortices.
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All authors Jinxin Wu, Dan Wang, Qingqing Liang, Jianhua Hu, Jiahao Dong, Jijun Feng, Yi Liu

Computational Physics · Cross-listed from quant-ph

Noise-Adaptive Quantum Circuit Mapping for Multi-Chip NISQ Systems via Deep Reinforcement Learning

Atiye Zeynali and Zahra Bakhshi

The transition from monolithic to distributed multi-chip quantum architectures has fundamentally altered the circuit compilation landscape, introducing challenges in managing temporal noise variations and minimizing expensive inter-chip operations. We present DeepQMap, a deep reinforcement learning framework that integrates a bidirectional Long Short-Term Memory based Dynamic Noise Adaptation (DNA) network with multi-head attention mechanisms and Rainbow DQN architecture. Unlike conventional static optimization approaches such as QUBO formulations, our method continuously adapts to hardware dynamics through learned temporal representations of quantum system behavior. Comprehensive evaluation across 270 benchmark circuits spanning Quantum Fourier Transform, Grover's algorithm, and Variational Quantum Eigensolver demonstrates that DeepQMap achieves mean circuit fidelity of $0.920 \pm 0.023$, representing a statistically significant 49.3% improvement over state-of-the-art QUBO methods ($0.618 \pm 0.031$, $t_{98} = 4.87$, $p = 0.0023$, Cohen's $d = 2.34$). Inter-chip communication overhead reduces by 79.8%, decreasing from 2.34 operations per circuit to 0.47. The DNA network maintains noise prediction accuracy with coefficient of determination $R^2 = 0.912$ and mean absolute error of 0.87%, enabling proactive compensation for hardware fluctuations. Scalability analysis confirms sustained performance across 20-100 qubit systems, with fidelity remaining above 0.87 even at maximum scale where competing methods degrade below 0.60. Training convergence occurs 8.2$\times$ faster than baseline approaches, completing in 45 minutes versus 370 minutes for QUBO optimization. Very large effect sizes validate practical significance for near-term noisy intermediate-scale quantum computing applications.
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Fluid Dynamics

Subspace Acceleration for Efficient Nonlinear Water Wave Simulation

Rasmus Kleist Hørlyck Sørensen, Margherita Guido, Allan Peter Engsig-Karup et al. (+1 more)

Efficient simulation of nonlinear and dispersive free-surface flows governed by the incompressible Navier-Stokes equations remains a central challenge in ocean and coastal engineering. The computational bottleneck arises from solving a time-dependent discretized Poisson problem at every time step to enforce divergence free flow. This is crucial to ensure conservation of mass and requires solving long sequences of time-dependent linear systems typically using iterative methods, such as the preconditioned Krylov subspace methods. In this work, we investigate new subspace acceleration techniques for improving initial guesses to reduce the number of iterations required by iterative solvers, with a focus on nonlinear wave propagation problems. We extend the original subspace acceleration method by incorporating the complete history of previous solutions through an exponentially weighted formulation. This approach eliminates the need for repeated sketching and orthonormalization, resulting in a more efficient and scalable strategy to generate better initial guesses. Our method is implemented within a high-order finite-difference framework using a method-of-lines formulation and a low-storage Runge-Kutta time integration scheme. We demonstrate that subspace acceleration significantly reduces the number of GMRES iterations when solving the Poisson equation in nonlinear water wave simulations. Performance is evaluated on two benchmark problems: nonlinear stream function wave propagation and harmonic wave generation over a submerged bar. In both cases, the new approach achieves substantial improvements in computational efficiency without compromising accuracy. Although demonstrated using high-order finite difference methods, the technique is discretization independent and broadly applicable to incompressible free-surface flow solvers.
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All authors Rasmus Kleist Hørlyck Sørensen, Margherita Guido, Allan Peter Engsig-Karup, Daniel Kressner

Chemical Physics · Cross-listed from quant-ph

Fewest switches surface hopping with decoherence in the Marcus inverted regime: correct rates but wrong thermal populations

Manas Nagda, Priyam Kumar De and Amber Jain

Fewest switches surface hopping (FSSH) is a well benchmarked dynamical method for simulating nonadiabatic systems. In particular, the literature shows that for the spin-Boson model Hamiltonian, FSSH with appropriate corrections usually captures the detailed balance well and obtains rate constants within a factor of 2 compared to numerically exact results. In this study, we show that in the deep inverted Marcus regime, the augmented-FSSH (AFSSH, one version that includes decoherence) yields reasonably accurate rate constants but incorrect thermal populations over a broad range of parameters. We present an analytical derivation to understand the AFSSH behavior, and therefore, show that AFSSH obtains correct rate constants owing to the resonance of the time derivative coupling with the exothermicity, but obtains an incorrect thermal population owing to the self-consistency issue. The presented derivation provides an analytical expression for the quantum correction factor for AFSSH simulations in the Marcus inverted regime.
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Plasma Physics

Three Dimensional Effects on Proton Acceleration with Grooved Hydrocarbon Targets

Imran Khan, Mohammad Yasir and Vikrant Saxena

Recently, using two-dimensional particle-in-cell simulations, it has been demonstrated that in laser based proton acceleration with micro-structured targets, a single rectangular groove on the target front offers significant proton cut-off enhancement with linearly polarised laser pulses. In the present work, three-dimensional investigations are carried out to identify notable differences between cylindrical and cuboidal groove geometries both of which correspond to a rectangular groove in a two-dimensional case. In particular, a waveguide model is employed to analyse the effect of the groove geometry and extensive three-dimensional particle-in-cell simulations are performed to demonstrate the distinct behaviour of laser pulse and electrons for cylindrical and cuboidal grooves. Further, the effect of a circular polarisation of the incident laser pulse on the spectra of accelerated protons is studied. It is shown that contrary to our initial expectations, cylindrical symmetry and circular polarisation do not play well together and cause as much as 15$\%$ decay in proton cut-off energies as compared to the case of cylindrical symmetry and linear polarisation.
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Chemical Physics

Quantifying the Spin-Orbital Entanglement in $5d^1$ Quantum Materials

V. García-Rojas and J. F. Pérez-Torres

The spin-orbital entanglement in $5d^1$ transition metal ions embedded in double perovskites, where anomalous effective magnetic dipole moments are frequently observed, is quantified by the spin-orbital von Neumann entropy $\Delta S_{\rm vN}^{\rm SO}$. The framework is grounded on the relativistic crystal field theory, and is illustrated through a series of quantum materials: $A_2{\rm TaCl}_6$ ($A = {\rm K}, {\rm Rb}$), $A_2{\rm MgReO}_6$ ($A = {\rm Ca}, {\rm Sr}, {\rm Ba}$) and ${\rm Ba_2NaOsO_6}$, all analyzed in their paramagnetic phases, alongside the ${\rm ReF_6}$ molecular system. The entropies are derived from measurements of the optical $d$-$d$ transitions $\Gamma_7(t_{2g})\leftarrow\Gamma_8(t_{2g})$ and $\Gamma_8(e_g)\leftarrow\Gamma_8(t_{2g})$, and of the effective magnetic dipole moment $\mu_{\rm eff}$. It is demonstrated that, regardless of the system, the Kramers doublet $\Gamma_7(t_{2g})$ exhibits no spin-orbital von Neumann entropy. The entropies obtained for the relativistic crystal field states $\Gamma_8(t_{2g})$ and $\Gamma_8(e_g)$ uncover that, a larger effective magnetic dipole moment can be attributed to a grater spin-orbital entanglement, yet paradoxically not to a larger spin-orbit coupling constant.
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Accelerator Physics

Space-Charge Effects During Half-Integer Resonance Crossing in the CERN PSB

Tirsi Prebibaj, Fanouria Antoniou, Foteini Asvesta et al. (+2 more)

The survival of charged particles in synchrotrons requires avoiding setting the beam on machine resonances, the most dangerous of which are the integer and half-integer. Nevertheless, operationally, the transverse tunes may change dynamically, crossing these resonances, and resulting in unwanted beam quality degradation and beam loss. For high intensity beams the process of resonance crossing is even more critical as space charge, in addition to the incoherent effects, may generate also coherent effects on the beam envelope dynamics. The interplay of the speed of resonance crossing, the space charge incoherent tune spread, and half-integer resonance width are fundamental for the beam behavior. In this paper we study the crossing of the half-integer resonance $2Q_y=9$ in the CERN Proton Synchrotron Booster~(PSB) for a range of parameters using a coasting beam. We take advantage of the newly commissioned PSB to investigate the beam response experimentally. The experimental findings are also discussed with the support of simulations.
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All authors Tirsi Prebibaj, Fanouria Antoniou, Foteini Asvesta, Hannes Bartosik, Giuliano Franchetti