Papers

Time-varying electromagnetic media exhibit rich nonstationary wave phenomena, but the symmetry governing reversal of arbitrary temporal modulation sequences has remained unclear. We show that, in lossless, spatially homogeneous media with identical initial and final states, the scattering matrices of ordered and reversed sequences are related by inverse–conjugation, independent of the number of stages. This yields a classification of temporal reciprocity in bi-isotropic media: isotropic and chiral media are channel-preserving, whereas Tellegen media are channel-exchanging despite Lorentz nonreciprocity. Deterministic time rewinding follows directly. Our results provide a framework for predicting and designing temporal scattering responses in photonic media.

The precise realization of molecular electronic devices requires a comprehensive understanding of charge transport mechanisms and the specific interplay between electronic and nuclear degrees of freedom. While average current measurements (I-V characteristics) and conventional Inelastic Electron Tunneling Spectroscopy (IETS) offer valuable insights, they are fundamentally limited by temperature-dependent line-width broadening. This study presents a high-resolution spectroscopic methodology utilizing suspended-wire molecular junctions (SWMJs) based on self-assembled monolayers (SAMs) of 1-decanethiol (C10) and 1,1',4',1”-terphenyl-4-thiol (TPT). By systematically probing the voltage-dependent current noise (${\Delta}I$), we demonstrate that electronic noise spectroscopy circumvents thermal degradation by probing transition rates between vibrational manifolds rather than simple additions of conductance channels, which enables sub-thermal feature mapping. Leveraging a fast-convolution-based Landauer-Büttiker transport model fitted to experimental data, we map complex vibrational manifolds, including high-energy overtones. This allows for the direct extraction of crucial nanoscale molecular parameters, including mode energies, anharmonicities ($x_e$), dissociation energies ($D_e$), and local environment reorganization energies ($E_r$). These parameter-dense noise signatures act as a unique molecular fingerprint, establishing noise spectroscopy as a highly sensitive platform for chemical sensing and discrimination in advanced quantum devices.

Gradient-index (GRIN) media with freeform refractive-index distributions require ray tracing approaches capable of accurately modeling light propagation in complex three-dimensional environments. In this work, we develop a fully three-dimensional ray tracing method for arbitrary freeform GRIN media based on the local application of a set of vectorial relations of geometrical optics. At its core, the method constructs ray trajectories through successive local refractions using the vectorial form of Snell's law, while employing constant optical path length steps that naturally adapt the geometric step size within the medium. Unlike conventional continuous GRIN propagation approaches, the proposed method naturally handles refraction at the boundary of the medium as well as total internal reflection, enabling the treatment of both continuous media and discretized refractive-index distributions composed of isoindicial surfaces. The method is simple to implement and computationally efficient. Validation against an analytical solution demonstrates high accuracy, while applications to freeform GRIN configurations illustrate its capability not only for propagation analysis, but also for the direct design of complex tailor-made optical media.

Nanosized hafnia-zirconia (HfxZr1-xO2) in the form of thin films, multilayers, and nanoparticles is one of the most promising CMOS-compatible ferroelectric materials for advanced electronic memories and logic devices. Using the Landau-Ginzburg-Devonshire free energy functional with trilinear and biquadratic couplings of polar, nonpolar, and antipolar order parameters, we analyze the pyroelectric and electrocaloric properties in an ensemble of spherical core-shell HfxZr1-xO2 nanoparticles. To test the theoretical model, we experimentally measured the temperature dependence of the electric charge accumulated in pressed powders consisting of oxygen-deficient core-shell Hf0.5Zr0.5O2 nanoparticles with an average size of 7 nm. The observed temperature-dependent behavior of the accumulated charge and its derivative are in qualitative agreement with the calculated polarization and pyroelectric coefficient for the ensemble of densely packed spherical core-shell HfxZr1-xO2 nanoparticles; this suggests that the theoretical model captures the physical mechanisms responsible for the experimentally observed charge accumulation. The combined theoretical and experimental results provide a physical foundation for the future development of CMOS-compatible HfxZr1-xO2 nanoparticles for pyroelectric and electrocaloric applications.

Optical imaging in complex samples such as biological tissues is fundamentally challenging due to random light scattering that degrades resolution and contrast. When imaging realistic targets that contain natural dynamics such as flowing blood, the temporal variability introduces an additional obstacle, as the leading computational scattering-compensation methods require the target to remain stationary during a multi-frame acquisition process. Here we show that instead of struggling to perform rapid acquisitions, the target dynamics themselves can serve as an intrinsic information source for scattering compensation, replacing multiple controlled illuminations. The mathematical equivalence between target dynamics and conventional varying illumination patterns allows to demonstrate this approach in coherent holographic imaging and incoherent fluorescence microscopy using established matrix and model-based scattering-compensation techniques. Our general framework enables reconstruction of dynamic scenes with a number of acquisitions equal to the number of reconstructed frames, without the use of any spatial light modulators or illumination control.

A phase-field-based reaction-diffusion corrosion model is developed to predict microbially influenced corrosion (MIC) in metal alloys, with a focus on anaerobic conditions and sulfate-reducing bacteria (SRB). The formulation couples microbial sulfate reduction, sulfate transport, electrochemical kinetics, material dissolution, and mechanical effects. Microbial activity is modelled using a Monod-type expression for sulfate consumption, whereas the mechano-chemical coupling is incorporated through an enhanced mobility relationship that captures the influence of mechanical fields on corrosion kinetics. The model is calibrated against experiments and shows strong agreement in predicting pitting kinetics under SRB activity. Sensitivity analyses quantify the competing roles of microbial kinetics, transport, and thermodynamic driving forces in governing corrosion behaviour. The capability of the formulation to capture both MIC-induced pitting and stress-assisted corrosion across multiple length scales is demonstrated through case studies that include microstructure-sensitive simulations and structural-scale coupling with a cathodic protection (CP) model. Results show that finer grain sizes reduce pitting severity but promote faster defect propagation under mechanical loading. At the structural scale, coupling with the CP model enables predictions of defect growth under varying electrochemical conditions and over engineering-relevant length scales, as exemplified with the analysis of an offshore wind turbine monopile. CP delays pitting and suppresses crack propagation, although its effectiveness diminishes as sacrificial anodes degrade. The framework provides a predictive and computationally efficient tool for assessing MIC-induced damage over extended times, with potential applications in the integrity and life assessment of metallic structures operating in aggressive microbial environments.

A methodology for passive mitigation of vortex-induced vibrations (VIVs) in subsea dynamic power cables is developed using optimized, strongly nonlinear bi-stable mass-spring-damper attachments, termed bi-stable nonlinear energy sinks (BNESs), within the open-source MoorDyn library. A fully three-dimensional time-domain framework captures cable dynamics, Morison-type hydrodynamic forcing, nonlinear vibration-mitigation mechanisms, and spatially and temporally varying currents. The BNESs are consistently integrated into the cable model, allowing treatment of highly non-stationary VIVs. A data-driven optimization study samples the BNES design space across multiple current profiles and shows that properly tuned configurations substantially reduce peak-to-peak cable vibration amplitudes. The BNESs also produce significant and robust reductions in cumulative VIV-induced energy intake from the surrounding flow and in drag energy. To the authors' knowledge, passive nonlinear attachments are shown for the first time to reduce both energy intake and drag amplification in a subsea cable, with potential benefits for short- and long-term fatigue. Time-frequency wavelet analysis reveals targeted nonlinear energy transfers and scattering from dominant high-amplitude, low-frequency cable modes to lower-amplitude, higher-frequency modes. This modal redistribution promotes rapid dissipation through hydrodynamic damping and internal structural losses, explaining the simultaneous reductions in vibration amplitude and cumulative energy intake. The results demonstrate that BNESs can provide effective and robust VIV mitigation for subsea power cables under realistic unsteady operating conditions and motivate future studies involving combined current-wave loading, platform-induced motion, and fatigue-life assessment.

We report the fabrication and characterization of an integrated quantum photonic device consisting of an electrically driven whispering-gallery-mode micropillar laser evanescently coupled to a ridge waveguide, both incorporating InGaAs quantum dots (QDs). The lasing characteristics of microlasers are systematically investigated as a function of the pillar-waveguide gap distance. Coherent emission from the whispering-gallery-mode microlaser coupled into the waveguide enables on-chip optical excitation of QDs embedded in an electrically contacted micropillar at the end of the waveguide. Under continuous-wave on-chip excitation, we observe single-photon emission with $g^{(2)}(0) = (3.49 \pm 0.01) \%$ for a QD integrated in the outcoupling micropillar which can be spectrally tuned-by the quantum confined Stark effect. These results constitute an important step toward low-footprint, deterministic, and scalable single-photon sources for QD-based integrated quantum photonic circuits.

Building on resistive communication, this paper presents a physics-based design of an on-chip neural network with multi-level memristive synapses supporting a dense spectrum of conductance states. Derived from ionic transport physics, we develop a state-variable model and quantify storable sub-levels under thermal noise, drift, and quantized conductance. We assemble these devices into a 1T1R crossbar fabric, derive the linear algebra of analog vector-matrix multiplication (VMM) under wire resistance, and design a differential synapse for signed weights. A multilayer pipeline executes inference, backpropagation, and weight updates physically in the analog domain. We derive the in-situ outer-product learning rule, its discretization onto the conductance lattice, and the resulting quantization noise. We provide energy, area, capacity, and inter-tile models, showing this substrate is ideally suited for large language models (LLMs). Our design eliminates weight movement, surpassing binary ReRAM and traditional CMOS. We detail the material stack (HfO_2-based), the FEOL/BEOL CMOS foundry-integration flow, a self-contained SPICE model, the complete memristive-FPGA neuromorphic system, and an in-memory self-attention engine with current-mode translinear softmax. Finally, a ternary BitNet datapath shows projected per-token efficiency orders of magnitude better than advanced CPUs or GPUs. The result is a self-contained hardware-native blueprint for a high-density, analog, in-memory neural processor.

The HYDRA (HYpernuclei Decay at R$^3$B Apparatus) TPC is a 5,376-channel pion tracker developed for hypernuclear studies at the R$^3$B experiment at GSI/FAIR. Its installation inside the GLAD dipole magnet imposes strict space constraints above the pad plane. To fit the front-end electronics within this volume, the VMM3a/SRS readout was adapted through a vertical hybrid arrangement and custom boards for signal routing and power distribution. At the same time, the readout had to be integrated with the R$^3$B timing system, which is not natively supported by the SRS. This was achieved by recording the R$^3$B heimtime and trigger signals through spare VMM3a channels, allowing the global timestamps to be reconstructed from the same data stream. Simulations of the PCB coupling indicated low crosstalk between adjacent traces, while S-curve measurements gave a baseline noise level consistent with that reported for the standard VMM3a/SRS readout. Cosmic-muon measurements with the plastic wall provided reconstructed tracks and confirmed event-by-event timing correlation between the two detector systems.

Why would anyone help a stranger, knowing they may never meet again? Indirect reciprocity offers one of the most compelling evolutionary answers, yet its two canonical forms – upstream reciprocity (experience-based), and downstream reciprocity (reputation-based) – have been studied mostly in isolation. Their joint dynamics in finite and structured populations remain largely unexplored. Here, we fill this gap using agent-based simulations in which an agent is behaviourally either defector, upstream reciprocator, or downstream reciprocator, and the agents' population state is temporally updated using different evolutionary update mechanisms. We show that update mechanism plays a surprisingly decisive role in shaping the fate of downstream and especially upstream reciprocators. Whether agents' experiences and reputations are updated globally or locally can shift outcomes from rich behavioural coexistence to the dominance of downstream reciprocators alone. Intriguingly, we uncover a robust structural feature that persists across all the explored update rules and population sizes: an optimal network degree at which upstream reciprocity is maximized, reflecting a fundamental tug-of-war between cooperative clustering and exposure to defectors. Our results highlight that while downstream reciprocity can either foster or inhibit upstream reciprocity depending on the update mechanism, its net effect on cooperation remains largely positive.

The transition-matrix ($T$-matrix) method has established itself as a prominent technique for computing the scattering response from spatially localized objects. The suitability becomes apparent particularly when considering not just isolated objects but also large ensembles of aperiodically or even periodically arranged objects. A versatile implementation of the method is provided by the treams program, which efficiently computes the electromagnetic response of scatterers in various arrangements [Comput. Phys. Commun. 297, p. 109076 (2024)]. Here, we rely on this framework and present a new program, acoustotreams, dedicated to simulating the acoustic scattering of pressure waves by clusters of particles, both with and without periodic boundary conditions. The computations are performed using the $T$-matrix method with scalar spherical and cylindrical waves as basis sets, and the scattering matrix ($S$-matrix) method in the basis of scalar plane waves for stratified media. The underlying theory is presented alongside the program structure and illustrative examples. The code is open-source and available on the Python Package Index for Linux, Windows, and macOS. Version control is maintained through GitHub, where we also provide automated tests, documentation, and detailed examples. We expect this work to contribute to the field of numerical methods for multiple-scattering problems by offering a computational framework capable of a comprehensive description of pressure-acoustic scattering in artificial media, including well-established metamaterials and metasurfaces.

We introduce OASIS, a simulation-based inference framework for scientific settings where observations are distorted by measurement error, selection effects, and other survey-specific transformations. In many real applications, simulators generate latent, noiseless quantities, while the data are observed only after passing through a complex observational pipeline. Standard simulation-based inference methods often ignore this distinction, comparing observations to idealized simulator outputs or relying on low-dimensional summaries that can miss important structure. OASIS addresses this mismatch by explicitly embedding the observation model into the simulator and performing inference directly at the level of observed-data distributions. The method constructs a pseudo-posterior by reweighting prior samples according to a maximum mean discrepancy (MMD) loss between the empirical distributions of the observed data and forward-simulated observations, thereby avoiding both handcrafted summaries and learned neural surrogates. We provide theoretical guarantees for Monte Carlo consistency, convergence of the empirical pseudo-posterior to its population counterpart, and posterior concentration on the MMD-identified parameter set, with consistency for the true parameter under correct specification and identifiability. In controlled errors-in-variables regression experiments, OASIS delivers robust parameter recovery and well-calibrated uncertainty under heterogeneous and non-Gaussian measurement noise. We then demonstrate the method on a realistic cosmological application involving galaxy cluster observations across multiple wavelengths, in which latent physical properties are linked to observables through nonlinear scaling relations, heteroscedastic errors, selection functions, and incomplete coverage.

Integrated structured-light sources usually obtain high-dimensional orbital angular momentum (OAM) states by encoding each channel into separate gratings, waveguides or metasurfaces, which ties modal capacity to structural complexity. Here we show that intrinsic material anisotropy can instead act as a built-in angular-momentum coupler. In an X-cut thin-film lithium niobate (TFLN) microring vortex emitter, the in-plane optical axis causes a circulating whispering-gallery mode to sample a periodically varying effective index, producing continuous azimuthal phase modulation. This modulation converts each resonance from a nominal single-charge emitter into a coherent topological sideband lattice with charges l=l_p+2n and Bessel-weighted amplitudes. Broadband measurements resolve a representative principal-charge series from l_p=-13 to +13, while additional devices with 100 and 200 GHz free spectral ranges (FSRs) show scalable resonance addressability. The emitted lattices are reproduced by a forward-calculated Fourier–Bessel model, supported by OAM projection measurements, and exhibit focusing into annular perfect-vortex fields and self-healing after obstruction. Waveguide-induced circular polarization further adds a vectorial spin–orbit channel. These results turn TFLN anisotropy from a material constraint into a compact mechanism for resonance-addressed high-dimensional structured-light generation.

Nonlocal optical nonlinearities arising from the thermorefractive effect provide a long-range material response determined by heat diffusion and absorption. In graded-index media, this nonlocality fundamentally alters modal interactions, yet its accurate modeling remains computationally demanding when starting from the full spatial nonlinear Schrödinger equation. In this work, inspired by the nonpolynomial Schrödinger equation (NPSE) framework, we extend the dimensional reduction techniques to incorporate thermally mediated nonlocal nonlinearities. By coupling the optical field to an equation for the temperature-induced refractive index change, and employing a variational ansatz based on Laguerre–Gauss modes of the annular kind, of arbitrary azimuthal order, we derive explicit analytic expressions for the variational equations. The resulting effective model captures the dependence of the nonlinear interaction on mode order and degree of nonlocality, providing a tractable reduced description of the dynamics in thermal nonlocal media.

An improved formulation of the recently developed cell-centered nodal integral method (MCCNIM) is proposed for the numerical solution of the nonlinear Burgers' equation. The improved scheme, referred to as RCCNIM, reformulates the nonlinear convection term prior to discretization by evaluating the convective velocity using cell-averaged values from the previous time level, rather than the present-time approximation used in the original MCCNIM formulation. This reformulation leads to a fully algebraic system whose coefficients depend only on known quantities and are therefore evaluated once per time step. As a result, the proposed method significantly reduces computational cost while retaining the accuracy of the original MCCNIM. The performance of RCCNIM is assessed through systematic numerical comparisons with MCCNIM for the nonlinear Burgers' equation. The results demonstrate that RCCNIM achieves comparable accuracy with improved computational efficiency, indicating its potential for extension to more complex nonlinear fluid flow problems.

Convection in icy moon oceans is strongly influenced by rotation, organizing into slantwise columnar structures aligned with the planetary rotation axis. They generate significant meridional heat transport, which can affect the ice shell topography, a primary observable of these moons. However, global ocean simulations cannot resolve convection under realistic icy moon conditions, and traditional convection schemes cannot represent slantwise convection. Here, we develop a slantwise convection scheme and implement it in a global ocean model. We perform benchmark tests in a global spherical shell by comparing parameterized fluxes with convection-resolving simulations. The scheme reproduces the meridional heat transport inside the tangent cylinder, where slantwise convection dominates. The resulting meridional heat transport significantly modifies the surface heat flux, producing variations comparable to the imposed bottom heating magnitude. Although the simulations with parameterized convection cannot fully reproduce the temperature structure, likely due to an inability to reproduce the temperature gradients near the boundaries, they capture the bulk interior vertical temperature gradient. The new scheme allows unresolved slantwise convection to be represented in global ocean simulations for icy moons. It is also applicable to other rapidly rotating oceans with small natural Rossby number ($\mathrm{Ro}^* \ll 1$), including deep ocean worlds on exoplanets.

Weakly collisional plasmas are widespread in astrophysics and can sustain pressure anisotropy, yet most analytical tearing-mode scalings assume an isotropic equilibrium. We develop a linear theory of resistive tearing in nonideal gyrotropic MHD for a force-free Harris current sheet characterized by perpendicular plasma beta $\beta_0$ and parallel-minus-perpendicular beta difference $\Delta\beta_0$. In the ideal outer region, anisotropy changes the far-field decay rate, the matching parameter $\Delta'$, and the upper wavenumber cutoff for localized tearing, $\alpha\equiv ka<\alpha_c=\sqrt{\mathcal{A}/\mathcal{R}_0}$, with $\mathcal{A}=1-\Delta\beta_0/2$ and $\mathcal{R}_0=1+\frac{1}{2}[(\gamma_\parallel+\gamma_\perp-2)\beta_0+\gamma_\parallel\Delta\beta_0]$. In the resistive inner layer, anisotropy enters the leading momentum balance through $\mathcal{A}$. We derive modified FKR and Coppi branches and, by matching them at their crossover wavenumber, obtain $\gamma_{\max}\tau_A\sim\mathcal{A}^{1/2}\mathcal{R}_0^{-1/4}S^{-1/2}$. Thus the classical Lundquist-number exponent is retained, while the prefactor depends on the equilibrium anisotropy, plasma beta, and gyrotropic closure. PSECAS eigenvalue calculations support the Coppi branch and are consistent with the FKR branch when a fitted finite-wavelength approximation for $\Delta'$ is used. Within the localized-mode and pressure-positive domain, positive $\Delta\beta_0$ generally suppresses tearing and broadens the inner layer, whereas negative $\Delta\beta_0$ enhances growth and shifts the fastest mode to larger wavenumber. This work identifies how prescribed equilibrium pressure anisotropy modifies both ideal outer matching and resistive inner-layer dynamics in the gyrotropic-MHD regime.

Hybrid bright-dark soliton complexes offer profound insights into multi-component nonlinear wave dynamics, yet their systematic generation via artificial saturable absorbers remains unexplored. Here, we experimentally demonstrate a comprehensive hierarchy of higher-order hybrid soliton architectures within a single nonlinear polarization rotation (NPR)-based erbium-doped fiber laser. Continuous tuning of intracavity polarization states and pump power enables reproducible access to soliton structures, with stable mode-locking confirmed at 8 MHz and a signal-to-noise ratio exceeding 72 dB. Cross-phase modulation (XPM)-mediated inter-component coupling and birefringence-induced polarization evolution collectively govern the observed soliton multiplicity, with NPR's inherent tunability proving decisive in accessing higher-order hybrid soliton regimes unexplored in prior studies. These findings expand the fundamental taxonomy of dissipative solitons and establish NPR-based fiber lasers as a reconfigurable platform for complex nonlinear wave engineering.

The 1990-2024 North Atlantic trend in the proportion of major-cyclone Category 3-5 fixes among all Category 1-5 fixes (the Kossin ratio, KR) was about five times the combined Pacific trend. This contrast motivates examining their basin-specific links: aerosol loading to cyclone potential intensity, and potential intensity to observed cyclone activity. Annual increases in aerosol loading were generally associated with decreasing potential intensity both in the North Atlantic and in all three Pacific basins. Potential intensity changes were consistently positively associated with cyclone-fix count changes in the North Atlantic, in some specifications also in the eastern North Pacific and South Pacific. However, changes in potential intensity in the western North Pacific were significantly negatively correlated with fix-count changes. The negative association disappeared after controlling for El Niño-Southern Oscillation changes. Furthermore, annual potential intensity changes were never significantly positively associated with KR changes.

Quantitative imaging of heat transport with high spatial and temporal resolution is essential for understanding thermal processes in heterogeneous systems, yet direct measurements of transient temperature fields at material interfaces remain challenging. Here, we employ time resolved thermal optical diffraction tomography (thermal ODT), a label free nanoscale optical thermometry technique that reconstructs spatio-temporal evolution of three dimensional temperature fields from thermally induced refractive index changes. We show that thermal diffusion along an interface is controlled by their thermal effusivity contrast. We also derive an effective interfacial diffusivity that accurately describes the lateral propagation of thermal fields and validate the model through finite-element simulations across a broad range of liquid-glass interfaces. Surprisingly, liquids with lower bulk thermal diffusivities exhibit faster interfacial thermal spreading due to their lower effusivities. The measured diffusivities agree quantitatively with theoretical predictions over diverse material combinations. By combining volumetric thermal imaging with a general framework for interfacial heat transport, our work establishes thermal ODT as a powerful platform for investigating nanoscale thermodynamics and engineering heat flow in heterogeneous environments.

Comprehensive characterization of numerical dissipation is essential for high-fidelity simulations of magnetohydrodynamic (MHD) turbulence. In this work, we present an a posteriori framework for directly estimating numerical dissipation in MHD turbulence from simulation data without invoking a priori assumptions. Implemented in the open-source Python package PyMHD, the framework is applied to simulations of Alfvénic turbulence, turbulent small-scale dynamos, and MRI-driven turbulence, yielding a systematic characterization of the anisotropy and spectral properties of numerical dissipation across these regimes. The results indicate that numerical dissipation primarily dissipates energy transferred by the turbulent cascade at small scales, consistent with the conventional interpretation. However, its spectral properties are distinct from those of physical viscosity and resistivity, such that it cannot simply be represented by effective dissipation coefficients. In addition, numerical dissipation inherits the anisotropy of the underlying turbulence, and can even exhibit anomalous anti-dissipative behavior under certain circumstances. Moreover, this framework enables identification of the conditions under which physical dissipation dominates numerical dissipation across all scales, thereby providing practical guidance for achieving high-fidelity simulations of astrophysical MHD turbulence.

We present a design agent which is a Large Language Model (LLM) that orchestrates, but does not perform, the numerical simulations to design a silicon-on-insulator (SOI) $2\times2$ directional coupler. We choose a symmetric phase-matched coupler where a lot of analytical results are available that help the design strategy. The LLM proposes candidate gap values (a geometrical dimension size) and judges convergence, while all physics is owned by deterministic solvers: a frequency-domain eigenmode solver estimates the coupling coefficient~$\kappa$ for the current design, and an independent Finite-Difference Time-Domain (FDTD) stage validates it. Both solvers operate on a common slab-projected two-dimensional (2D) effective-index reduction of the silicon film, so the design~$\kappa$ and the FDTD response are consistent by problem design; the residual between them is shown to be a single constant phase offset~$\phi$, attributable to a fixed excess coupling length $L_{\mathrm{extra}}=\SI{2.837(11)}{\micro\meter}$ that we find invariant across a factor-of-two range in~$\kappa$. Folding this offset into a closed-loop length correction, the agent delivers a $50/50$ splitter whose FDTD-measured cross fraction is $0.498$ (target $0.500$), a residual of $0.0017$. Results are made self-consistent within the 2D effective-index model; and the LLM succeeds in delivering a suitable design over a number of attempts.

We consider localized oscillation of an Euler–Bernoulli beam on a visco-elastic foundation coupled to a damped discrete oscillator. All parameters of the system independently vary in time in a slow manner. For the conservative case, we use three various analytic approaches. Namely, these are asymptotics, the method based on the adiabatic invariance of the action of a trapped wave, and the consideration of the equivalent Hamiltonian system. All approaches result in the same formula for the amplitude of oscillation. In the dissipative case, we obtain the amplitude of oscillation only utilizing the asymptotic approach.

Geometric phase quantifies net locomotion in dissipative media via gauge theory, but linking this theoretical quantity to noisy, sparse, and weakly periodic biological shape data is challenging. We develop a theory-guided, data-driven Koopman autoencoder to recover the limit cycle embedded in imperfect cyclic data and extract shape gaits and geometric phase from sperm and nematode data. We introduce a geometric phase sensitivity function that quantifies responses to shape perturbations and reveals mechanical information using only gauge-theoretic structure, without assuming mechanical laws.

We derive compact analytical formulae for the spectrum of nonlinear Compton scattering in a finite plane-wave pulse with a smooth temporal envelope. The strong-field QED probability is reduced to finite-pulse phase integrals, which are evaluated asymptotically for multicycle pulses with a broad class of smooth envelopes. We use the uniform approximation to remove the caustic divergences that appear at the nonlinear edges of broadened harmonics. Away from the caustics, it reduces to the standard saddle-point result. The behavior near the linear edge is further improved by an envelope-corrected saddle-point approximation. The approach retains the harmonic substructure in the spectral-angular region carrying the dominant part of the emitted radiation. The locally monochromatic approximation is recovered by averaging the finite-pulse interference. Within their asymptotic domain of applicability, the resulting formulae agree with direct numerical calculations and can be used to evaluate spectra from an electron beam.

Optical image differentiation is a key operation for edge extraction in imaging and machine vision, yet most existing implementations rely on momentum-domain filtering elements and are typically developed within a scalar-wave framework. Here we demonstrate a nonlinear vectorial mechanism for optical image differentiation based on parametric wave mixing. By solving the full vector wave equation with a nonlinear polarization source term, we show analytically that frequency conversion intrinsically generates cross-polarized field components that correspond to spatial derivatives of the incident field. Exploiting the polarization-selective phase-matching conditions of second-order nonlinear crystals, particularly uniaxial crystals, we propose filter-free imaging schemes that simultaneously perform spatial differentiation and wavelength conversion. This nonlinear vector differentiation platform enables compact, wavelength-agile, and edge-enhanced imaging, offering new opportunities for mid-infrared imaging and all-optical signal processing.

Time-stretch spectroscopy is powerful for capturing transient spectral phenomena but remains fundamentally limited by detector bandwidth or timing jitter, especially under photon-starved conditions. Here, we devise and implement single-photon time-stretch computational ghost spectroscopy, which integrates dispersive wavelength-to-time mapping with programmable temporal encoding and correlation-based reconstruction to overcome these detection limitations. Specifically, temporally stretched ultrashort pulses are modulated by predefined encoding patterns and detected by a low-bandwidth detector, allowing reconstruction of near-infrared spectra with 450 resolvable channels across 1530-1590 nm without direct high-speed waveform acquisition. By further incorporating compressive sensing, accurate spectral recovery is achieved at sub-Nyquist sampling rates, substantially reducing acquisition requirements to facilitate high-speed operation at 210 kHz. In the single-photon regime, computational ghost reconstruction effectively suppresses the intrinsic detector timing jitter, yielding high-fidelity spectra at illumination fluxes down to 0.01 photons/pulse. By jointly enabling broadband coverage, high spectral resolution, high acquisition speed, and single-photon sensitivity, this approach establishes a computation-enhanced paradigm for time-stretch spectroscopy and provides a versatile platform for ultrafast and photon-efficient spectroscopic applications.

Advances in the semiconductor industry are driven by the development of increasingly compact devices featuring intricate etched geometries, the characterization of which essentially requires ultraprecise, label-free, and real-time metrology. However, non-destructive and alignment-free optical metrology of sub-wavelength structures with nanometric resolution remains a major challenge. Here, we demonstrate a novel single-shot, label-free, and alignment-free optical metrology approach for determining the 1D position of sub-wavelength nanostructures, achieving lambda/110 (7.2 nm) precision. The high precision benefits from utilizing structured illuminations of Laguerre-Gaussian (LG) or Hermite-Gaussian (HG) beams, and the AI analyzing method can retrieve the information when such structured light interacts with sub-wavelength objects. Instead of relying on phase singularities in superoscillatory microscopy, our approach leverages spatially distributed phase jumps in HG and LG beams interacting with the nanostructures, providing an alignment-robust solution to the challenges in optical metrology. Such an alignment-free, non-destructive, and high-precision metrology technique enables real-time machine vision, semiconductor inspection, and advanced manufacturing.

The atmospheric tropical belt is believed to be more predictable than the extratropics. This question is revisited here by exploring the emergence of chaos in reduced-order model versions of the vorticity equation under the weak temperature gradient hypothesis, which provides a good description of the large-scale tropical atmosphere. The analysis reveals that under fairly realistic divergence forcing amplitudes, chaos may emerge, sometimes with Lyapunov time scales of less than a day. This result contrasts with the idea of a predictable tropical atmosphere, and opens important questions on the effective origin of predictability in the Tropics.