Optics
Modulation of Spin Angular Momentum of Emission in Symmetric 1D Plasmonic Crystals by Cathodoluminescence
Yuxin Yang, Izzah Machfuudzoh, Qiwen Tan et al. (+1 more)
The
spin angular momentum (SAM) of light has become a cornerstone of numerous photonic applications, including optical communication and
chiral photonics. Because SAM is inherently associated with circularly polarized light (CPL), the ability to modulate CPL in a controlled and efficient manner is essential not only for advancing fundamental studies of light-matter interactions but also for enabling next-generation photonic technologies. However, such modulation is commonly realized by structurally
chiral systems, which inherently limits the feasibility of dynamic tuning. Here, we demonstrate that one-dimensional plasmonic
crystals (1D PlCs), despite their structural
symmetry, can serve as a platform for controllable CPL generation. By employing an electron beam in scanning transmission electron microscopy (STEM), we coherently excite transition radiation and emission from 1D PlC modes. Their interference produces energy- and momentum- (emission angle-) resolved CPL, which clearly reveals its dispersion and spatial dependence at the nanoscale, providing direct guidance for its manipulation and offering insights into the design of plasmonic devices including the phase information. Furthermore, interference with surface plasmon polariton scattering at the structural boundary enables the efficiency modulation of CPL generation via the excitation position along the terrace.
Read the full abstract ▾
All authors Yuxin Yang, Izzah Machfuudzoh, Qiwen Tan, Takumi Sannomiya
Fluid Dynamics
Unified Hydrodynamic Analogue of Aharonov-Bohm and Lense-Thirring Effects
Aditya Singh, Joseph Samuel, Chien-chia Liu et al. (+3 more)
We show that surface waves in a draining-bathtub
vortex provide a hydrodynamic realization of both Aharonov-Bohm phase shifts and Lense-Thirring frame dragging within a single system. A static time transformation maps the flat (2+1)-dimensional wave equation onto the convected shallow-water equation, yielding an effective vector potential set by the background flow. In this geometry, the circulation defines a global phase holonomy that controls wave structure. Traveling waves exhibit wavefront dislocations characteristic of Aharonov-Bohm scattering, while standing-wave superpositions produce nodal patterns that rotate at an angular velocity fixed by the circulation, providing a direct analogue of frame dragging. For noninteger circulation, the problem is naturally defined on the universal cover, ensuring single-valued partial-wave solutions. Experiments on a controlled
vortex confirm these predictions and establish a laboratory platform in which topological phase and inertial effects, central to gauge and gravitational physics, emerge from a measurable velocity field.
Read the full abstract ▾
All authors Aditya Singh, Joseph Samuel, Chien-chia Liu, Luiza Angheluta, Andrés Concha, Mahesh Bandi
Data Analysis and Statistics · Cross-listed from cs.AI
The CriticalSet problem: Identifying Critical Contributors in Bipartite Dependency Networks
Sebastiano A. Piccolo and Andrea Tagarelli
Identifying critical nodes in complex networks is a fundamental task in graph mining. Yet, methods addressing an all-or-nothing coverage mechanics in a bipartite dependency network, a graph with two types of nodes where edges represent dependency relationships across the two groups only, remain largely unexplored. We formalize the CriticalSet problem: given an arbitrary bipartite graph modeling dependencies of items on contributors, identify the set of k contributors whose removal isolates the largest number of items. We prove that this problem is NP-hard and requires maximizing a supermodular set function, for which standard forward greedy
algorithms provide no approximation guarantees. Consequently, we model CriticalSet as a coalitional game, deriving a closed-form centrality, ShapleyCov, based on the Shapley value. This measure can be interpreted as the expected number of items isolated by a contributor's departure. Leveraging these insights, we propose MinCov, a linear-time iterative peeling
algorithm that explicitly accounts for connection redundancy, prioritizing contributors who uniquely support many items. Extensive experiments on synthetic and large-scale real
datasets, including a Wikipedia graph with over 250 million edges, reveal that MinCov and ShapleyCov significantly outperform traditional baselines. Notably, MinCov achieves near-optimal performance, within 0.02 AUC of a
Stochastic Hill Climbing metaheuristic, while remaining several orders of magnitude faster.
Read the full abstract ▾
Physics and Society
Weighted complement graphs of spatial networks with functional connections reveal nodes with high potential for new links
Tina Šfiligoj and Oded Cats
In this study, we take a systematic look at the unrealised part of public transport networks (PTNs) with functional connections. We consider their complement graphs and study their structure. The complement graph $\bar G$ of an unweighted graph $G$ is a straightforward concept, yielding a graph on the same set of nodes, and an edge exists in $\bar G$ if and only if it is not present in $G$. In contrast, a weighted complement graph cannot be uniquely determined. However, if we consider PTNs with travel times as edge weights, there are physical constraints on the possible weight ranges. We propose a method to construct weighted complement graphs of operational PTN graph representations based on the geographical distances between nodes (representing stops) and assign weights to edges based on distance, combined with network-specific distributions of effective velocities and waiting times. We observe that the most central nodes in the weighted complement graph do not correspond to the least central nodes in the original network but are, remarkably, those in the geographical centre of the network that lack topological connectedness. Testing against null models on a
dataset of 31 metro networks worldwide confirms that this is a fundamentally spatial effect.
Read the full abstract ▾
Chemical Physics · Cross-listed from cond-mat.stat-mech
How to quantify long-time rotational motion in molecular systems
Romain Simon, Hadrien Bobas, François Villemot et al. (+2 more)
We show that all existing methods quantifying rotational motion in molecular fluids eventually have severe limitations in systems undergoing complex rotational motion characterized by slow, heterogeneous, or intermittent dynamics. This impacts in particular the study of rotational dynamics in molecular supercooled
liquids near their glass transition, as well as discussions of the decoupling between rotational and translational motion and violations of the Debye-Stokes-Einstein relation. We present a brief overview of existing methods and explain why none of them can accurately capture the
evolution of rotational dynamics from a diffusive fluid to an arrested solid, thus resolving inconsistent literature results. We then introduce an empirical method that efficiently solves all issues. We
benchmark our method devising a family of continuous time random walk models for rotational dynamics. Our method correctly quantifies the statistics of free and caged rotational motion, as well as non-Gaussian and non-Fickian rotational dynamics, and should allow a better characterization of dynamic heterogeneity in the rotational motion of supercooled molecular fluids.
Read the full abstract ▾
All authors Romain Simon, Hadrien Bobas, François Villemot, Jean-Louis Barrat, Ludovic Berthier
Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Data-Driven Thermal and Mechanical Modeling of Defective Covalent Organic Frameworks
Aleksander Szewczyk, Leonardo Medrano Sandonas, David Bodesheim et al. (+2 more)
Covalent Organic Frameworks (COFs) are versatile two-dimensional (2D) materials for flexible electronics, catalysis, and sensing, owing to their tunable architectures and large surface areas. However, like most materials, COFs inevitably contain synthesis-induced defects, which-similar to
graphene-can strongly influence intrinsic properties, such as thermal transport and mechanical strength. To address this challenge, we have assessed the performance of a set of machine learning interatomic potentials (MLIP) capable of efficient large-scale simulations of COFs with
quantum accuracy. In doing so, QCOF models (
Quantum COF) were developed by tuning the state-of-the-art MACE architecture on an extensive
dataset of non-
equilibrium COF conformations generated from high-fidelity density functional theory calculations. The accuracy, computational efficiency,
memory footprint, and transferability to unseen chemical environments of these models were benchmarked against general-purpose MACE models and their fine-tuned variants. Our results show that an invariant QCOF model with a small descriptor dimensionality and cutoff outperforms all other models in most validation tasks, including scalability to large systems, force prediction in defective COFs, and
phonon dispersion calculations. The best-performing QCOF model was then used to run large-scale simulations of thermal conductivity for defective CTF-1 and COF-LZU1 systems via non-
equilibrium MD, revealing a more pronounced sensitivity of CTF-1 to structural defects. Stress-strain curves were also investigated, showing that the mechanical response remains nearly invariant at low defect densities, while asymmetric behaviour emerges at large strains. This work thus provides a foundation for the design of robust
quantum-informed MLIP for large-scale property simulations of defective of extended network materials.
Read the full abstract ▾
All authors Aleksander Szewczyk, Leonardo Medrano Sandonas, David Bodesheim, Bohayra Mortazavi, Gianaurelio Cuniberti
Optics
Designing interferometers within a single optical beam
Bereneice Sephton, Rakhi Thomas, Carlo Schiano et al. (+8 more)
Interferometry provides highly sensitive access to optical phase and is central to much of modern metrology and phase imaging methods. Conventional implementations, however, often face trade-offs between mechanical stability and experimental or computational complexity. Here, we present a general framework for designing custom interferometers within a single optical beam by exploiting structured light. This approach yields compact, robust common-path configurations that bypass the need for complex post-processing and can easily be integrated into existing setups. We demonstrate the versatility of this concept by designing a range of interferometers, each tailored by the structured mode, and implement them through active and passive modal conversion optics, proving its adaptability to different experimental requirements. To showcase the practical utility of our framework, we apply it to quantitative phase imaging over a variety of physical samples, showing excellent agreement with atomic force microscopy
benchmarks. Furthermore, we emphasise the flexibility of our structured light interferometers by mapping phase objects to a choice of either amplitude or polarisation, the latter providing a direct route toward real-time phase-
retrieval. This cost-effective approach offers a practical, high-throughput solution for phase-sensitive metrology across fields such as fundamental physics, biology, and material science.
Read the full abstract ▾
All authors Bereneice Sephton, Rakhi Thomas, Carlo Schiano, Francesco Reda, I Komang Januariyasa, Filippo Cardano, Bruno Piccirillo, Marcella Salvatore, Stefano Luigi Oscurato, Corrado de Lisio, Vincenzo D'Ambrosio
Computational Physics
A Thin Sheet Volume Integral Equation Solver for Simulation of Bianisotropic Metasurfaces
Sebastian Celis Sierra, Meruyert Khamitova, Ran Zhao et al. (+2 more)
A thin-sheet (TS) volume integral equation (VIE) formulation incorporating generalized sheet transition conditions (GSTCs) is presented for the simulation of three-dimensional (3D) bianisotropic metasurfaces. The metasurface is represented as an equivalent thin sheet, with its constitutive tensors derived from the GSTC susceptibility tensors. Invoking the thin-sheet approximation, the governing VIEs are reduced to surface integral equations (SIEs), in which tangential and normal flux density components are treated as distinct sets of unknowns and discretized using Rao-Wilton-Glisson and pulse basis functions, respectively. In contrast to conventional GSTC approaches based on conventional SIEs, which represent only tangential fields, the proposed framework rigorously enforces the bianisotropic GSTCs, including normal field interactions, while retaining the flux-based VIE character of the formulation. Numerical examples, including a comparison with an SIE-GSTC solver that neglects the normal susceptibility components, demonstrate the accuracy and robustness of the proposed TS-VIE-GSTC solver for polarization rotation on planar and curved sheets, perfect reflection, beam steering with spatially varying susceptibilities, multi-directional attenuation, and oblique phase-shift transformation.
Read the full abstract ▾
All authors Sebastian Celis Sierra, Meruyert Khamitova, Ran Zhao, Sadeed Bin Sayed, Hakan Bagci
Optics
Gaussian pulse scattering by a chiral spherical shell
Hector M. Iga-Buitron, Tom G. Mackay and Akhlesh Lakhtakia
Theory was formulated for scattering by a coated
chiral sphere of a plane wave of arbitrary polarization state with amplitude modulated by a Gaussian pulse. The spherical core and the concentric shell of the sphere were composed of two different homogeneous materials, both isotropic
chiral. Calculations of energy efficiencies for extinction, total scattering, and absorption were carried out for the shell material with experimentally determined constitutive parameters, the core being vacuous. All three energy efficiencies depend on the relative thickness of the shell and the circular polarization state of the carrier plane wave.
Read the full abstract ▾
Fluid Dynamics · Cross-listed from cond-mat.soft
Continuum granular flow model with restitution-derived viscoelastic damping
Bodhinanda Chandra, Sachith Dunatunga and Ken Kamrin
This work presents a unified viscoelastic-viscoplastic continuum framework for modeling rate-dependent granular flows across regimes. The formulation incorporates two distinct rate-dependent mechanisms, namely micro-inertia and viscoelastic dissipation, within a single continuum description. A central contribution is an explicit link between the coefficient of restitution and a continuum viscosity, derived from an analysis of wave attenuation in granular assemblies, thereby establishing a direct connection between particle-scale collision physics and macroscopic damping. This relation is introduced while retaining inertia-dependent plastic flow governed by the classical $\mu(I)$ rheology. The constitutive model is constructed by meticulously partitioning elastic and plastic responses within the model and corresponding stress-update routine, such that viscous dissipation governs wave propagation and collisional processes without altering the plastic flow rule. The framework is implemented within the material point method to simulate transient processes involving large deformations, material separation, and subsequent reconsolidation. A range of numerical examples, including steady, transient, vibrational, and impact-driven flows, demonstrates that the model captures wave propagation,
diffusion, and rate-dependent granular behavior within a unified continuum setting.
Read the full abstract ▾
Optics
Reconfigurable ultrafast perovskite polariton logic gates via nonlinear dynamics
Yuyang Zhang, Zhuoya Zhu, Xin Zeng et al. (+14 more)
Exciton-polaritons provide a great platform for developing ultrafast all-optical logic gates for
quantum and optical chips. However, progress toward practical polariton logic remains limited due to incomplete logical functionality on a single device. Herein, we present a single-device perovskite polariton platform enabling reconfigurable, ultrafast logic gates with functional completeness. The device consists of an optically trapped perovskite microwire, generating well-controlled non-
equilibrium polariton condensation states for multiple logic operation channels. By tailoring the power of signal and gate beams, the same device is programmed to execute three basic Boolean functions (AND,OR,and NOT) and a high-order XOR function with a high on/off ratio of 21 dB, and a fast response time 6.7 ps. The reconfigurability arises from the selective activation of different nonlinear responses of polariton condensates, including amplification, seeding state transitions, and nonlinear interaction. These results provide valuable insights for advancing
exciton-polariton logic gates.
Read the full abstract ▾
All authors Yuyang Zhang, Zhuoya Zhu, Xin Zeng, Shuai Zhang, Xinyi Deng, Tian Lan, Changhai Zhu, Kwok Kwan Tang, Qinglin Jia, Yuexing Xia, Yiyang Gong, Wenna Du, Feng Li, Rui Su, Xuekai Ma, Xinfeng Liu, Qing Zhang
Computational Physics
Enabling Biomolecular Simulations with Neural Network Potentials in GROMACS
Lukas Müllender, Berk Hess and Erik Lindahl
Neural network potentials (NNPs) are rapidly changing the landscape of state-of-the-art molecular dynamics (MD) simulations. To make full use of this development, the community needs flexible, easy-to-use interfaces firmly integrated with existing methodologies. To address this, we here present an interface for hybrid machine learning/molecular mechanics (ML/MM) simulations implemented in the widely used MD code GROMACS. The interface enables NNPs trained in the PyTorch framework to contribute energies and forces during MD simulations, either for selected subsets or entire molecular systems. By defining a flexible set of model inputs and outputs, the interface is agnostic to specific NNP architectures and can accommodate a wide range of descriptor-based and message-passing models. In particular, the design integrates NNP inference seamlessly into the extensive GROMACS molecular simulation ecosystem, providing users with the capability to straightforwardly combine NNPs with existing advanced sampling and free energy workflows. We demonstrate the capabilities of the interface using several representative applications, including enhanced sampling of peptide torsional free energy landscapes, absolute solvation free energy calculations, and
protein–ligand simulations. We also run performance
benchmarks on water boxes for several different NNP architectures. Our interface is available in recent GROMACS releases, and we believe it will provide a practical foundation for incorporating machine learning potentials into production MD simulations of biomolecular systems.
Read the full abstract ▾
Physics and Society
Disorder Crossover in Urban-Front Growth
Martin Hendrick, Maximilian Trique and Gabriele Manoli
Urban expansion fronts display a robust local roughness exponent together with strongly dispersed growth and nonuniversal dynamic exponents. We show that this coexistence can arise from a disorder-controlled crossover in projected-front growth. Introducing a minimal Eden model, in which geographic constraints act as quenched dilution and coalescence as quenched local acceleration, we demonstrate that the resulting front enters a long disorder-dominated preasymptotic regime, whose scaling near threshold is set by ordinary two-dimensional percolation. In this regime, the local roughness remains close to $1/2$, while the large-scale exponents vary broadly with disorder and acceleration. These results provide a minimal explanation of urban-front roughening and suggest a more general mechanism for
stochastic growth in heterogeneous media.
Read the full abstract ▾
Computational Physics · Cross-listed from cs.CE
JAX-BEM: Gradient-Based Acoustic Shape Optimisation via a Differentiable Boundary Element Method
James Hipperson, Jonathan Hargreaves and Trevor Cox
Engineering structures are increasingly designed using numerical optimisation. However, traditional optimisation methods can be challenging with multiple objectives and many parameters. In machine learning, stable training of artificial neural networks with millions or billions of parameters is achieved using automatic differentiation frameworks such as JAX and Pytorch. Because these frameworks provide accelerated numerical linear
algebra with automatic gradient tracking, they also enable differentiable implementations of numerical methods to be built. This facilitates faster gradient-based optimisation of geometry and materials, as well as solution of inverse problems. We demonstrate JAX-BEM, a differentiable Boundary Element Method (BEM) solver, showing that it matches the error of existing BEM codes for a
benchmark problem and enables gradient-based geometry optimisation. Although the demonstrated examples are for acoustic simulations, the concept could be readily extended to electromagnetic waves.
Read the full abstract ▾
Plasma Physics
Collisionless Phase Mixing Mimics Diffusive Transport in Radiation Belt Observations
Adnane Osmane, Xin An, Anton Artemyev et al. (+3 more)
Since the dawn of the space age, observations of energetic particles in planetary radiation belts have been interpreted within a diffusive transport framework, even though the dominant processes that populate and deplete these belts-such as injections and moon-driven absorption-produce highly structured, spatially localized particle distributions. This exposes a fundamental question: how can coherent phase-space structures evolving under collisionless dynamics give rise to observational signatures consistent with
diffusion-based transport? Here we show that
diffusion-like behaviour inferred from radiation belt observations can arise solely from an observational phase-mixing effect, independent of
stochastic wave-particle transport. As orbiting spacecraft sweep across neighbouring drift shells while trapped particles undergo electromagnetic drifts, measurements inevitably sample regions with slightly different drift frequencies. This converts localized drift-phase structures into rapidly decorrelating temporal signals, making them observationally indistinguishable from those produced by
stochastic wave-particle processes. We derive the associated correlation function analytically and show that the effective lifetime of these structures is only a few drift periods. Consequently, even highly localized injections rapidly lose coherence, preventing spacecraft from resolving fine-scale structure in the distribution function. These results show that collisionless dynamics can produce observational signatures that mimic diffusive transport on timescales shorter than those expected from radial transport, biasing inferred transport rates and long-term flux predictions. This calls for a reassessment of
diffusion-based interpretations from sparse in-situ measurements of radiation belts at Earth, across the
solar system, and in the recently discovered radiation belts of ultra-cool brown
dwarfs.
Read the full abstract ▾
All authors Adnane Osmane, Xin An, Anton Artemyev, Oliver Allanson, Jay Albert, Miroslav Hanzelka
Plasma Physics
The virial expansion of the Hydrogen equation of state in comparison to PIMC simulations: the quasiparticle concept, IPD, and ionization degree
Gerd Röpke, Chengliang Lin, Werner Ebeling et al. (+1 more)
The properties of
plasmas in the low-density limit are described by virial expansions. Analytical expressions are known for the lowest virial coefficients from Green's function approaches.Recently, accurate path-integral Monte Carlo simulations were performed for the hydrogen
plasma at low densities by Filinov and Bonitz [Phys. Rev. E 108 (2023)055212], which made a comparison of the virial expansions and the derivation of interpolation formulas possible. The exact expression for the second virial coefficient is used to test the accuracy of the PIMC simulations and the range of application of the virial expansions.To describe
plasmas in a wider range of density and temperature, the concept of quasiparticles is considered. Medium modifications of free and bound states are obtained from the spectral function. Mean-field effects are presented, such as exchange terms, Pauli blocking and screening. The density expansions of the quasiparticle shifts is considered. The combination of PIMC simulations with
benchmarks from exact virial expansion results allows us to obtain precise results for the EoS in the low-density range. At low densities, the results are compared with the Saha equation to introduce the medium-dependent ionization potential. The relation to the Beth-Uhlenbeck formula and concepts such as the Mott effect, ionization potential depression (IPD), and ionization degree are discussed. The limits of current PIMC results for hydrogen
plasmas are shown. Further improvements of the PIMC simulations are required to compare with analytical
benchmarks.
Read the full abstract ▾
All authors Gerd Röpke, Chengliang Lin, Werner Ebeling, Heidi Reinholz
Optics
Optical hopfions with arbitrary two winding numbers
Xinji Zeng, Jinwen Wang, Yun Chen et al. (+10 more)
Hopfions, as three-dimensional topologically nontrivial structures described by poloidal and toroidal winding numbers, hold promise as robust information carriers in spintronics, functional materials, and optical communications. Although they have been experimentally realized in various physical systems, such realizations have been restricted to low orders, with the winding numbers lacking tunability. Here, using optical fields as our platform, we outline how to make tunable hopfions in any order with any winding number. We use tailored superpositions of Laguerre-Gaussian modes in free-space as our construction, achieving effective control for arbitrary-order poloidal and toroidal winding numbers, which we demonstrate up to orders 5 and 3, respectively, for a new state-of-the-art. The resulting
torus-
knot structures are visualized experimentally via polarization filaments, confirming the designed topological textures. Our work reports an exotic optical
topologies observed in free space, provides a systematic route hopfions of any order, with implications for topological photonics, optical communications, and analogies in
magnetic and condensed-matter systems.
Read the full abstract ▾
All authors Xinji Zeng, Jinwen Wang, Yun Chen, Guang Liu, Zhenyu Guo, Yongkun Zhou, Xin Yang, Chengyuan Wang, Dong Wei, Haixia Chen, Yijie Shen, Andrew Forbes, Hong Gao
Optics
Microwave noise downconversion in interband cascade laser frequency combs
Grzegorz Gomółka, Florian Pilat, Benedikt Schwarz et al. (+6 more)
Chip-scale
semiconductor laser frequency combs offer remarkable prospects for compact and power-efficient optical sensors. For the
laser to be suitable for typical comb applications, its degree of coherence must first be assessed from a microwave self-mixing signal. Unfortunately, such measurements require scarcely available high-speed photodetectors with multi-GHz bandwidths and
radio-frequency electronics. However, in this work, we demonstrate a simplified approach to comb coherence assessment for interband cascade
lasers based on a relationship between easily-accessible MHz-frequency (baseband) noise and the multi-GHz-frequency intermode beat note. The downconversion of microwave noise to near-DC frequencies is found to originate intrinsically from the
laser, which simultaneously acts as a frequency mixer due to electrical nonlinearities and a phase-to-amplitude noise converter due to the linewidth enhancement factor. Correlation between the electrical signals is explored in both frequency and time domains. Since this phenomenon is potentially universal in
semiconductor lasers, it creates a new opportunity for frequency comb characterization, which may be particularly valuable in wavelength regions where fast photodetectors have limited availability.
Read the full abstract ▾
All authors Grzegorz Gomółka, Florian Pilat, Benedikt Schwarz, Chul Soo Kim, Mijin Kim, Chadwick L. Canedy, Igor Vurgaftman, Jerry R. Meyer, Łukasz A. Sterczewski
Geophysics
Ohmic and viscous damping of inner core translational oscillations
Paolo Personnettaz, David Cébron, Nathanaël Schaeffer et al. (+2 more)
Large earthquakes can trigger translational oscillations of Earth's inner core (Slichter modes), yet their damping remains uncertain. Using simulations, we quantify viscous and Ohmic dissipation in the fluid outer core. Earth's rotation splits the motion into one polar and two equatorial modes. We explore all three and derive scaling laws for the quality factor with each dissipation mechanism. Viscous effects are negligible, confined to a thin layer at the inner core boundary. Ohmic dissipation dominates, with decay times of 3-16 years. Equatorial modes damp at least twice as fast as the polar mode. Our results suggest that Slichter modes can persist for years. Their continued non-detection is therefore more likely due to weak excitation than rapid damping.
Read the full abstract ▾
All authors Paolo Personnettaz, David Cébron, Nathanaël Schaeffer, Renaud Deguen, Mioara Mandea
Geophysics · Cross-listed from cs.LG
A Green-Integral-Constrained Neural Solver with Stochastic Physics-Informed Regularization
Mohammad Mahdi Abedi, David Pardo and Tariq Alkhalifah
Standard physics-informed neural networks (PINNs) struggle to simulate highly oscillatory Helmholtz solutions in heterogeneous media because pointwise minimization of second-order PDE residuals is computationally expensive, biased toward smooth solutions, and requires artificial absorbing boundary layers to restrict the solution. To overcome these challenges, we introduce a Green-Integral (GI) neural solver for the acoustic Helmholtz equation. It departs from the PDE-residual-based formulation by enforcing wave physics through an integral representation that imposes a nonlocal constraint. Oscillatory behavior and outgoing radiation are encoded directly through the integral kernel, eliminating second-order spatial derivatives and enforcing physical solutions without additional boundary layers. Theoretically, optimizing this GI loss via a neural network acts as a spectrally tuned preconditioned iteration, enabling convergence in heterogeneous media where the classical Born series diverges. By exploiting FFT-based convolution to accelerate the GI loss evaluation, our approach substantially reduces GPU
memory usage and training time. However, this efficiency relies on a fixed regular grid, which can limit local resolution. To improve local accuracy in strong scattering regions, we also propose a hybrid GI+PDE loss, enforcing a lightweight Helmholtz residual at a small number of nonuniformly sampled collocation points. We evaluate our method on seismic
benchmark models characterized by structural contrasts and subwavelength heterogeneity at frequencies up to 20Hz. GI-based training consistently outperforms PDE-based PINNs, reducing computational cost by over a factor of ten. In models with localized scattering, the hybrid loss yields the most accurate reconstructions, providing a stable, efficient, and physically grounded alternative.
Read the full abstract ▾
Optics
Analytic Inverse Design of Temporal Metamaterials via Space-Time Duality
Giuseppe Castaldi, Marino Coppolaro, Massimo Moccia et al. (+3 more)
Temporal metamaterials, created by modulating the refractive index in time, offer powerful means of controlling wave propagation but still lack a systematic design methodology. Here, we develop an analytic inverse-design framework rooted in space-time duality and the established theory of one-dimensional spatial inverse scattering. By prescribing reflection (backward-wave) and transmission (forward-wave) responses in rational-function form, we obtain closed-form refractive-index modulations that are guaranteed to be physically admissible. This approach avoids iterative optimization and provides direct analytic control of the modulation. We illustrate the method with syntheses of mathematical operators, such as derivatives and integrals, as well as Chebyshev- and Butterworth-type filters, and validate the results through finite-difference time-domain simulations. Our findings establish a general route to temporal media with tailored functional and spectral responses, enabling applications in wave-based information processing, programmable filtering, and amplification schemes inspired by photonic time
crystals.
Read the full abstract ▾
All authors Giuseppe Castaldi, Marino Coppolaro, Massimo Moccia, Carlo Rizza, Nader Engheta, Vincenzo Galdi
Classical Physics
Taylor-SWFT: fast discrete Statistical Wave Field Theory using Taylor expansion for late reverberation Work under review
Marius Rodrigues, Louis Lalay, Roland Badeau et al. (+2 more)
Dynamic room acoustic simulation aims to render the acoustic effects of an environment in real time while accounting for potentially moving sources and receivers. In this context, the efficient synthesis of the long-term room response, also known as late reverberation, remains challenging because of the intricate relationship between room geometry and acoustic behavior. This paper introduces Taylor-SWFT, an efficient implementation of key results from Statistical Wave Field Theory (SWFT) for the geometry-aware dynamic synthesis of late reverberation. The method is evaluated on the
Benchmark for Room Acoustical Simulation (BRAS) and achieves competitive performance compared with classical approaches, while substantially reducing computational cost.
Read the full abstract ▾
All authors Marius Rodrigues, Louis Lalay, Roland Badeau, Gaël Richard, Mathieu Fontaine
Atomic Physics
Revisiting the luminescence properties of Pr3+: YAG within the framework of an extended approach of Judd-Ofelt theory
Maxence Lepers, G. Hovhannesyan, Y. Guyot et al. (+2 more)
We show in this article the improvements which can be obtained in the description of the luminescence properties of Pr3+ doped materials by using an extension of the Judd-Ofelt theory in order to relax some strong selection rules and approximations of the standard formalism and to better account for the influence of the 4f5d excited electronic configuration. The demonstration is made by re-examining the case of Pr3+:YAG, a well known luminescent and
laser crystal with a very low energy 4f5d absorption band. Our extension thus provides a better agreement between calculated and measured absorption intensities, especially for the hypersensitive 3 H4 $\rightarrow$ 3 P2 transition. A comparison is made with the results obtained in the case of Pr3+:ZBLAN, a
laser fluoride glass with much higher 4f5d absorption levels. Our investigation also gives the opportunity, in the case of Pr3+:YAG, to provide more complete and more reliable absorption and emission data than reported in the past literature and to exploit these data to better address the question of
laser operation at various emission wavelengths. It is thus demonstrated that
laser operation should be possible with improved
laser performance at 488 nm, 616 nm and 744 nm, as it was already achieved in the past, but also at 566 nm and 931 nm by using appropriate
laser cavities and
laser mirrors.
Read the full abstract ▾
All authors Maxence Lepers, G. Hovhannesyan, Y. Guyot, R. Moncorgé, M. Velazquez
History and Philosophy of Physics · Cross-listed from math-ph
The Geometry Underlying the Quantum Harmonic Oscillator
Alexander D. Popov
We consider two-dimensional harmonic oscillator in the complex Bargmann-Fock-Segal representation with $T^*{\mathbb R}^{2}={\mathbb C}^2$ as classical phase space. We show that the eigenfunctions $\psi_n$ of the
quantum Hamiltonian correspond to complex radial coordinates in the reduced phase space ${\mathbb C}^2/{\mathbb Z}_n\subset{\mathbb C}^2$. They describe ${\mathbb Z}_n$-invariant motion of particle along a circle $S^1$ in lens space $S^3/{\mathbb Z}_n\subset{\mathbb C}^2/{\mathbb Z}_n$, where ${\mathbb Z}_n$ is the cyclic group of rotation by an angle $2\pi/n$ on the circle $S^1$, $n=1,2,...\,$. Thus the general solution of the Schrödinger equation carries information about an infinite number of admissible classical states $\psi_n$ that can be mapped to other states after lifting into the
quantum bundle. We show that in the Kepler/hydrogen atom problem there is a similar correspondence between classical and
quantum states.
Read the full abstract ▾
Atomic and Molecular Clusters · Cross-listed from quant-ph
Scalable surface ion trap design for magnetic quantum sensing and gradiometry
Qirat Iqbal and Altaf Hussain Nizamani
Magnetic quantum sensors based on trapped ions utilize properties of
quantum mechanics which have optimized precision and beat current limits in sensor technology. Trapped ions are highly sensitive in a large span of signal ranging from DC or static B-field to the radiofrequency range in 100s of MHz and can attain the sensitivity in the range of pT to sub pT . They are tuneable to frequencies of interest and can be used as a lock-in frequency detector. This modelling and simulation based study presents an innovative design of Surface Paul Traps, enabling the use of trapped ions as ultra-sensitive sensors for
magnetic field detection and precise measurement of
magnetic field gradients at a sub-millimeter spatial resolution. The novel design features multiple trapping regions, allowing for the mapping of
magnetic fields across various ion-trapping zones. The study demonstrates groundbreaking advancements in ion manipulation and confinement through innovative chip architecture.
Read the full abstract ▾
Computational Physics · Cross-listed from cond-mat.stat-mech
Fractals of Simple Random Walks in Two Dimensions: A Monte Carlo Study
Jiang Zhou, Ziru Deng and Pengcheng Hou
We present a Monte Carlo study of the fractal geometry of clusters formed by discrete-time simple random walks (sRW) of $L^2$ steps on a periodic square $L\times L$
lattice. We verify with high precision that the asymptotic behavior of the cluster mass follows $M/L^2 \simeq (\ln L)^{-1} [\frac{\pi}{2}+b (\ln L)^{-2}]$, with $b\approx -(\pi/2)^{-2}$, demonstrating marginal “logarithmic fractals". We further determine the fractal dimension of the hull to be $d_{\rm hull}=1.333\,29(14)=4/3$, in excellent agreement with the prediction of Schramm-Loewner
evolution ($\rm SLE_{8/3}$) for the Brownian frontier universality class. More importantly, we analyze the chemical distance $S$ spanning the cluster and obtain strong evidence that it asymptotically scales as $S\sim L(\ln L)^{1/4}$, lying exactly on the theoretical upper bound for the chemical distance for level-set percolation clusters on the two-dimensional Gaussian free field. Our numerical results show that the sRW cluster exhibits a conformally invariant external frontier and contains highly efficient asymptotically linear connective paths.
Read the full abstract ▾
Physics and Society · Cross-listed from cs.MA
Role of diversity in team performance: the case of missing expertise, an agent based simulation
Tamás Kiss
Theory and empirical research on management teams' influence on firm performance have witnessed continuous development, and by now incorporate numerous details. Classic, experiment-based studies examining social systems collect vast amount of data, but often times investigate only the first one or two modes of the distribution of measured variables, and experience difficulty in analyzing the effect of context. For example, in functional diversity research, management teams are described by measures incorporating complex distributions of capabilities of individual managers and teams of managers. To investigate the effect of hidden distributions, and the effect of functional diversity composition on team communication and performance, we developed an
agent-based model, and conducted a series of simulation experiments. Modeling results show that depending on the context, such as communication scheme among interacting
agents, or their functional composition, intrapersonal functional diversity (IFD), and dominant function diversity (DFD) might enhance or reduce performance and communication among
agents. Furthermore, simulation results also suggest that a third measure is required alongside IFD and DFD capturing the aggregate expertise of the team to comprehensively account for empirical findings.
Read the full abstract ▾
Instrumentation and Detectors
Liquid argon purification and purity monitoring: apparatus and first results
Wenzhao Wei, I-see Warisa Jaidee, Spencer Dockal et al. (+14 more)
We report results from a 13-liter purified
liquid argon test stand at Wellesley College in Massachusetts, USA. The system includes a single-pass
liquid-phase purification column that can achieve sub-part-per-billion
impurity levels. The
liquid argon purity is measured with a double-gridded purity monitor to assess the electron lifetime. Measurements demonstrate an O2-equivalent
impurity concentration of $0.21 \pm 0.05$ ppb (stable over a 20-hour duration), corresponding to an electron lifetime of 1.6 ms at a drift field of 500 V/cm. This test stand supports ongoing detector R&D on charge and light readout for
liquid argon time projection chambers, such as Q-Pix and other cold electronics systems.
Read the full abstract ▾
All authors Wenzhao Wei, I-see Warisa Jaidee, Spencer Dockal, Vyara Tsvetkova, Genevieve Bui, Tenaya Chen Lin, Lucia Epstein, Ava Faubus, Neneh M. T. Hambraeus, Sunshine B. Lyon, Diana Lopez, Natalie McGee, Piper J. Migden, Cleo Nicollin, Meenakshi Unnithan, Jonathan Asaadi, James B.R. Battat
Optics
Scalable Photonic Neural Networks via Surrogate Scattering-Matrix Inverse Design
Azka Maula Iskandar Muda and Uğur Teğin
Inverse-designed nanophotonic media are a promising platform for compact optical neural networks, but training them end to end is expensive because each adjoint iteration couples the full-wave solver to the
dataset minibatch, so the number of electromagnetic simulations scales with both the network depth and the batch size. We introduce a two-stage surrogate workflow that decouples task learning from electromagnetic realization. In the first stage, the trainable optical block is represented as a passive complex
matrix with bounded singular values and the classification task is solved directly in
matrix space at negligible cost. In the second stage, the selected target operator is transferred to a fabrication-aware freeform device through an adjoint problem driven by a Frobenius-norm transmission residual and a reflection penalty, which removes the minibatch dependence from the full-wave loop and yields a smoother loss landscape than intensity-domain cross-
entropy. We further introduce a banded-router architecture composed with a fixed evanescent-coupling region, which exploits the bandwidth-additive property of
matrix products to realize dense effective operators within a design region roughly half as long as a fully local router would require. The framework is validated on three tasks. On MedMNIST, the realized all-optical classifier reproduces the surrogate accuracy within $0.6$ percentage points after only 20 adjoint epochs. On RSSCN7, the banded router plus evanescent stage improves test accuracy by more than 15 percentage points over a linear readout baseline. A Yin-Yang task confirms that the same framework supports nonlinear decision boundaries. These results indicate that surrogate-guided inverse design is a practical route to training compact photonic processors with simulation budgets orders of magnitude smaller than direct geometry-to-task pipelines.
Read the full abstract ▾
Physics and Society
Identifying dynamical network markers of financial market instability
Mariko I. Ito, Hiroyuki Hasada, Yudai Honma et al. (+3 more)
Market instability has been extensively studied using mathematical approaches to characterize complex trading dynamics and detect structural change points. This study explores the potential for early warning of
market instability by applying the Dynamical Network Marker (DNM) theory to order placement and execution data from the Tokyo Stock Exchange. DNM theory identifies indicators associated with critical slowing down – a precursor to critical transitions – in high-dimensional systems of many interacting elements. In this study,
market participants are identified using virtual server IDs from the trading system, and multivariate time series representing their trading activities are constructed. This framework treats each participant as an interacting element, thereby enabling the application of DNM theory to the resulting time series. The results suggest that early warning signals of large price movements can be detected on a daily time scale. These findings highlight the potential to develop practical DNM-based early-warning systems for large price movements by further refining
forecasting horizons and integrating multiple time series capturing different aspects of trading behavior.
Read the full abstract ▾
All authors Mariko I. Ito, Hiroyuki Hasada, Yudai Honma, Takaaki Ohnishi, Tsutomu Watanabe, Kazuyuki Aihara