Papers

Folding changes the linearized aeroelastic spectrum and can switch which mode becomes unstable first, with consequences for local postflutter interactions. This study formulates a three-component Z-fold wing by assigning every aerodynamic station to a structural component and a material coordinate. The same attachment map generates surface motion and returns pressure loads through virtual work. Geometrically exact component dynamics, an explicit-wake unsteady vortex-lattice model, and block-structured descriptor assembly preserve the physical paths of configuration actions. A two-parameter flutter analysis shows that a smooth flutter-speed envelope conceals a high-low-high sequence of controlling neutral branches, expressed as a critical-frequency valley and a redistribution of component deformation. Numerical continuation locates a near-1:2 double-Hopf point. Within a local model retaining quadratic and cubic structural restoring forces with aerodynamic and inertial operators fixed at the scheduling point, the cubic normal form captures selected 26-state observations and admits high-frequency-dominant and mixed phase-locked periodic solutions. The formulation links configuration-dependent flutter-mode identity to local resonant dynamics and supports blockwise sensitivity and design reasoning.

We present a lower bound on the total physical thickness of a lossless, non-dispersive dielectric mirror for a given minimum reflectance across a wavelength band. The bound is based on a causality-based sum rule translated from a known result in acoustics, that expresses the wavelength integral of the logarithmic transmission of any lossless one-dimensional refractive-index profile as a function of the total thickness of each material comprising the profile, independent of how the layers are arranged. Calculating the thickness bound for a dielectric mirror, given some incident medium and substrate, requires only the lowest and highest refractive indices used in the thin-film stack and the minimum desired reflectance for a given wavelength span. We find that (1) the bound is set by the wavelength span so, for example, a 400-700 nm and an 800-1100 nm mirror have the same bound; (2) the figure of merit for materials minimizing the necessary thickness is $(n_H-n_L)^2/(n_H+n_L)$, where $n_H$ and $n_L$ are the indices of the high- and low-index materials; and (3) each additional "nine" of reflectance (e.g., from 99% to 99.9%) requirement adds a fixed amount of additional thickness to the bound. Non-exhaustive numerical calculations show that the readily achievable thickness is about twice our bound.

Viscoelastic compliant coatings offer a passive route to modify wall-bounded turbulence; however, their effectiveness for drag reduction remains unresolved. We perform resolvent analysis of turbulent boundary layers over linear viscoelastic continuum, and apply it to incompressible hydrodynamic and compressible aerodynamic zero-pressure-gradient turbulent boundary layers, using both standard and eddy viscosity resolvent formulations. Across a wide range of storage modulus E and coating thickness H, viscoelastic surfaces amplify near-wall-cycle-type modes while also attenuating the resolvent gain of very large scale motions (VLSMs) by up to 50%, which together result in a reduction of Reynolds stress. For density-matched coatings representative of aqueous incompressible flows, however, these favorable bands lie entirely within the regime where the effective coatings are linearly unstable to traveling wave flutter, rendering them practically unrealizable. Optimizing material damping does not eliminate this but provides a pathway to use weaker sub-optimal interactions. In supersonic flow, the large solid-to-fluid density ratio (O(1000)) shifts the favorable interaction to substantially higher moduli, weakening the achievable reduction in turbulence production to a few percent. However, the strongest interaction band occurs in the linearly stable regime. These results suggest that compliant wall drag reduction via coupling with high gain modes is fundamentally constrained by flow-induced structural instabilities in incompressible applications, whereas the high density ratios of supersonic flow offer a much narrower but stable window for practical coatings.

The design and control of wave scattering, that is, of the reflection and transmission parameters of a device, is of ubiquitous importance. These parameters generally change with varying frequency, though certain frequency-independent linear relations may exist between them. Reciprocity and geometric symmetry (reflections, rotations, etc.) are classic and well-known examples that are present in many devices and significantly ease their design. In this work, we go beyond these and introduce a new class of relations that cannot be induced by reciprocity or geometric symmetry. Choosing networks of waveguides as our workhorse, we discuss the conditions and consequences of such novel behaviour and showcase suitable example setups. We further experimentally test our predictions using coaxial cables and find excellent agreement in the broad frequency range between 0 and 1 GHz. Our work not only deepens the theoretical understanding of waveguide network dynamics, but also opens new avenues for applications in broadband signal processing, quantum information, and integrated photonics.

We investigate random recursive simplicial complexes growing by adding, at each step, a vertex together with a simplex formed by joining the new vertex with a randomly chosen existing simplex. We also add all faces of the new simplex to ensure that the resulting object remains a simplicial complex. If the choice of an existing simplex is uniform among simplices of dimension $<m$, the number $S_d$ of simplices of any admissible dimension $d\leq m$ is an asymptotically self-averaging random variable. This feature allows us to determine the asymptotic growth law of the average of $S_d$ when the number of vertices diverges. We also probe the degree distribution, examine the probabilities of various extreme outcomes, and analyze the characteristics of the first vertex.

Detector lag, also referred to as afterglow, is a source of image degradation in flat-panel x-ray detectors, producing temporal artefacts that reduce image quality and quantitative accuracy. In this work, we present a robust and repeatable experimental framework for characterising long-term detector lag (from minutes to hours) under controlled step-up and step-down exposure transitions of particular relevance to tomography. The measured transition curves from an amorphous silicon detector with a CsI:Ti scintillator exhibit unexpected behaviour, with the detector response temporarily overshooting its final equilibrium intensity following step-up transitions, rather than exhibiting the gradual monotonic rise and decay typically expected. These curves were well fitted by multi-exponential functions, providing initial estimates for the depth of the charge traps in the scintillator. These parameters were incorporated into a proposed multi-trap rate equation model that reproduces the overall observed behaviour of both step-up and step-down transitions, including the overshoot that is not captured by previous models. Although discrepancies remain between the model and observation, this work establishes a reproducible methodology for detector lag characterisation and presents an improved physical model that offers greater insight into the mechanisms governing detector lag.

We present a general approach for calculating new electron-electron interactions with atomic structure theory, include dominant many-body effects, and extract bounds for parity-odd cases. The procedure is valid for any mediator mass and improves previous calculations by including many-body corrections to the new interaction through the time-dependent Hartree-Fock method. Bounds on coupling strengths are then extracted for scalar-pseudoscalar and vector-axial vector interactions by comparison with experimental atomic electric dipole moments and parity non-conserving (PNC) transitions respectively. In the latter case, our calculations rule out any coupling-mass ratio |g^e_V g^e_A|/m_X^2 greater than 10^-11 MeV^-2 above m_X ~ 10 MeV, covering a previously unconstrained mass region. We also report an updated calculation of the regular (Standard Model) electron-electron Z^0 exchange contribution to the 6s-7s PNC transition amplitude E_PNC in cesium.

In swollen elastomers, elasticity can arrest macroscopic demixing between the polymer network and the solvent, producing stable domains of finite size. While previous theories have focused on isotropically swollen elastomers, anisotropy strongly influences the phase behavior of many related systems, such as gels and crosslinked polymer blends. Building on the approach developed in Part I of this two-part paper, we investigate the effects of two experimentally induced sources of anisotropy: uniaxial swelling and stiffness gradients. We show that uniaxial swelling can lead to the formation of stable lamellar microphases and modify phase behavior, while stiffness gradients can cause spatial variations in the characteristic microphase size.

Spontaneous parametric down-conversion (SPDC) is one of the most widely used sources of polarization-entangled photon pairs, and understanding the generated biphoton state is essential for realizing high-brightness and high-purity entangled-photon sources. In particular, Type-II SPDC produces a biphoton wavefunction with a complex coupling between the spatial and polarization degrees of freedom owing to birefringence. In this study, we calculate the real-space distribution of the two-photon polarization state from the biphoton wavefunction of Type-II SPDC generated in a e̱ta}-barium borate (BBO) crystal. By identifying the spatial correlation direction between polarization and real-space coordinates, we designed aperture shapes that restrict the collection along this correlation direction. Through both numerical simulations and experiments, we demonstrate that such correlation-aligned apertures simultaneously achieve higher entanglement purity and improved photon collection efficiency. These results establish a practical design principle for optimizing aperture geometries based on the real-space biphoton wavefunction, providing a new approach to realizing high-purity and high-brightness SPDC entangled-photon sources.

The temperature-dependent band gap of solids is usually computed from the perturbative Allen-Heine-Cardona (AHC) electron-phonon self-energy evaluated on-shell. Extending AHC to arbitrary frequency $\omega$ to determine the full spectral function via the Dyson equation is known to fail, misplacing satellites and yielding no broadening at band extrema, while non-perturbative supercell (SC) methods have focused on eigenvalue averages rather than lineshapes, and approaches based on special displacements cannot describe the full lineshape, or the lineshift at degenerate bands. Here we use a non-perturbative Green's function method (NPG), stochastically sampling distorted SC configurations, from which the spectral function, including lineshift, linewidth, and asymmetry, follows directly, and we recover finite spectral weight at the renormalized band extrema. We prove that the perturbative self-energy, computed to any order with the bare propagator and introduced into the Dyson equation, has an imaginary part that vanishes within the bare gap, giving incorrect spectral functions: self-consistency of the propagator is essential to broaden the band edges. NPG satisfies this property by construction, and contains all non-bubble diagrams. We also give a simple explanation of why SC methods converge with much smaller SCs than the corresponding $\mathbf{q}$-grids required by perturbation theory. For the band gap shift itself, the NPG and on-shell AHC results are found to be comparable, demonstrating that higher-order terms do not significantly alter the resulting renormalization in diamond. When it comes to the spectral function though, our results show that going beyond bare perturbation theory is not merely more accurate, but necessary, and NPG provides a robust framework to capture spectral broadening and higher-order effects from first principles.

Forecast-error growth has been studied through complementary approaches: scalar models describe the evolution of bulk error, whereas spectral theories follow decorrelation and error transfer across scales. Their connection matters when a fitted growth curve is used to infer a physical mechanism or a limit of predictability. We establish a conditional link between these approaches. Within a bilinear spectral exchange model, assume a stationary reference spectrum and a remainder that vanishes on the proposed common-shape evolution. For a common initial decorrelation fraction strictly between zero and one, the spectral shape is preserved and its amplitude grows logistically exactly when every participating scale shares one positive growth coefficient. The converse inference fails: a logistic aggregate need not imply proportional decorrelation or a common coefficient. An exact two-shell construction demonstrates this failure with identical aggregate curves and different spectral dynamics. For heterogeneous amplitudes, an exact averaging identity separates the contributions of growth-rate mismatch, shape variance, rate–shape covariance, evolving spectral weights, and residual tendencies. A finite-time bound relates their combined effect to departure from a reference logistic curve. Forced surface-quasigeostrophic simulations illustrate how similar retrospective agreement with a logistic reference can coexist with heterogeneous effective shell rates and substantial instantaneous tendency discrepancies. Thus a scalar growth curve alone cannot identify how uncertainty is distributed across scales or justify interpreting a fitted rate as a common spectral growth coefficient. The framework specifies the additional spectral and budget evidence needed to give scalar predictability models that interpretation.

The asymptotic properties, with vanishing viscosity, of inertial turbulence in Newtonian fluids have been of intense scrutiny over the years. Much less is known about elastic turbulence - a distinct spatio-temporally chaotic state exhibited by viscoelastic fluids. In this work, using direct numerical simulations of turbulence in a triperiodic box, we show that elastic turbulence achieves an ultimate state with increasing polymer relaxation time, i.e., the Deborah number, for two different constitutive models (Oldroyd-B and FENE-P). In the limiting state, various bulk quantities - the fluid dissipation, the polymeric energy transfer, as well as the elastic stresses - are shown to become independent of the polymer relaxation time scale, notwithstanding the microstructure deformation scales distinctly depending on the model.

Non-relativistic objective collapse theories have been remarkably successful in addressing the conceptual problems of standard quantum mechanics. Despite substantial efforts, the project of extending them to the relativistic domain remains burdened by significant conceptual objections and technical challenges, often taken to cast doubt on the viability of the program as a whole. On the conceptual side, relativistic collapse theories have been claimed to face challenges involving tension between instantaneous collapse and relativity, frame-dependence of property values and probabilities, the possibility of superluminal signaling and the failure of narratability. On the technical side, persistent infinities, difficulties in constructing fully covariant frameworks and the apparent need for non-standard fields have hindered the development of workable models. In this paper, we offer a systematic rebuttal of the conceptual objections and provide a structured account of the remaining technical challenges. We conclude that relativistic collapse theories do provide a promising route toward a fully relativistic quantum framework that overcomes the conceptual limitations of standard quantum theory.

We study graded arrays of highly dispersive subwavelength resonators through their volume-potential matrix reduction. The reduction gives a finite-dimensional nonlinear resonance problem whose diagonal entries encode the local dispersive response and whose off-diagonal entries encode volume-mediated coupling between distinct resonators. We show that monotone material grading turns this matrix into an analytically controllable frequency sorter. When graded detuning dominates coupling in the reduced characteristic matrix, the characteristic vectors localize near individual resonators; under an explicit half-lattice-site localization condition, this localization becomes a monotone frequency-position map. We also prove a constructive inverse-design statement: prescribed monotone target frequencies can be realized by choosing the local dispersive parameters, with robustness under sufficiently small grading errors. Numerical experiments, whose parameters and algorithms are recorded in an appendix, illustrate localized resonances, designed frequency-position maps, disorder stability, spacing dependence, and a resolved physical Lippmann-Schwinger validation beyond the leading logarithmic quadrature model.

Complex hypergraphs (chygraphs) contain graphs, hypergraphs, multiplex and interacting networks as special cases, and the percolation threshold of all of them follows from one symbolic calculation: the spectrum of a tensor $A$ built from four matrices of first moments. That calculation stops at the threshold. Here I show that $A$ is the Jacobian, at its trivial fixed point, of a non-linear self-consistency map whose non-trivial fixed point is the giant component fraction, so threshold and order parameter are two orders of one object on one index set. Carrying the expansion one order further gives the critical amplitude $B$ in $S=B\Lambda+O(\Lambda^2)$ in closed form, and exposes a hierarchy: first moments fix the threshold, second moments the amplitude, and only the generating functions themselves the order parameter away from it. Dropping the assumption that a complex's participation in different layers is independent generalises the tensor again, replacing unconditional first moments by inclusion-biased second moments: distributions with identical marginals have different thresholds and different order parameters. Six constructions from the literature are then solved by substitution, among them AND- against OR-logic hypergraph percolation, which share a chygraph and differ in one generating function, and SIR epidemics with two levels of mixing, whose household reproduction number falls out of the tensor. A reported failure of mean-field theory on strongly clustered graphs is shown to be a failure of applying it to the wrong object: mapped onto the treelike backbone rather than the clustered graph, the same calculation reproduces the exact threshold, order parameter and critical exponents. Everything is implemented in one class, in which a chygraph is specified once by its generating functions and then returns all three, and validated against Monte Carlo simulation.

QBists insist that theirs is a realist position while denying that the quantum formalism represents a mind-independent world. The insistence is hard to place. The realism debate is throughout a dispute about represented content, so a theory that denies standing in the representation relation appears not to take up a position within that debate at all. This paper examines the most developed attempt to make good on the QBist claim–David Glick's perspectival normative realism–and argues that it fails instructively. Glick seeks the ground of the Born rule's objectivity among states of affairs and construes an agent's perspective as a location within an already-constituted world; finding no state of affairs fit to bind every agent at once, he must book the ground as brute. Phenomenology supplies the third thing his picture lacks. A horizon is not a position within the world but the condition under which a world is given. Read as an agent's weighting–her curvature–of such a horizon, the quantum state is neither a defective description nor a brute posit, and the Born rule articulates the invariant lawfulness by which any sense confers a curvature at all.

As the population ages, the number of patients with cardiovascular diseases continues to increase, highlighting the need for early detection before progression to severe and irreversible functional decline. Consequently, estimating cardiovascular biomarkers from non-invasive biosignals, such as photoplethysmography (PPG) and arterial pressure wave (APW) signals, has attracted increasing attention. These signals can be measured using wearable and cuff-type devices. Previous studies have used PPG and APW signals to estimate cardiovascular biomarkers. However, these signals exhibit strong similarities in both the temporal and frequency domains and primarily reflect peripheral and arterial pulse waveforms. Therefore, they may provide limited information about cardiac mechanical function. In contrast, the quantitative impact of additional biosignals, such as ballistocardiography (BCG), which reflect the body's minute mechanical responses to cardiac ejection, remains unclear. In this study, we generated synthetic PPG, APW, and BCG signals from a unified whole-body cardiovascular circulation model and evaluated the complementary contribution of BCG to probabilistic cardiovascular biomarker estimation. We estimated posterior distributions of cardiovascular biomarkers using neural posterior estimation and simulation-based inference. The results showed that adding BCG signals significantly improved estimation performance. Furthermore, even in ill-posed cases where PPG and APW alone produced multimodal posterior distributions, adding BCG yielded unimodal posterior distributions. These findings provide fundamental insights into signal selection for estimating cardiovascular dynamics.

Exceptional deficiency is a newly discovered broadband non-Hermitian condition, at which the system's spectrum is entirely composed of exceptional points and all eigenvectors pairwise coalesce. Here, we analyze the steady-state and time-domain responses of non-Hermitian lattices at exceptional deficiency by considering their frequency and time-domain Green's functions. We show that the frequency-domain Green's functions are characterized by the emergence of second-order poles across the entire spectrum, producing broadband second-order super-Lorentzian line shapes, enhanced magnitude, and sequential 2pi phase shifts across each resonance. These second-order poles also underpin unconventional responses to global dissipation, by which we uncover a loss-revival of defective skin effect: the skin modes that are "missing" due to the system's defectiveness at exceptional deficiency can re-emerge in the responses. In the time-domain responses, a linear-in-time amplification factor is identified in the evolution kernel, which can enhance skin-effect dynamics that would otherwise be suppressed by global loss. The amplification strength scales with the degree of defectiveness of the system and diminishes upon spectral detuning between subsystems. Our work establishes a theoretical framework for analyzing steady-state and dynamic signatures of exceptional deficiency, and opens new routes for dissipation-controlled broadband exceptional responses.

Hydrodynamic ram (HRAM) loading remains a persistent challenge in impact mechanics, less due to exotic physics than to the difficulty of achieving convincing quantitative agreement in reduced-order representations. Prevailing studies typically employ a single mesh and boundary treatment validated against one experimental dataset, leaving unresolved whether agreement reflects genuine fidelity or compensating discretization errors. This work presents a planar 2D, GPU-accelerated WCSPH solver employing an Adami-type ghost-particle boundary condition, extended for the first time to a moving, decelerating disk penetrating a confined liquid channel at ballistic velocity. The boundary condition is examined against a purpose-derived potential-flow added-mass solution and the analytical acoustic reflection coefficient at the steel-water interface; this exploration reveals that the stiff equation of state and cavitation cutoff impose identifiable delineation of the solver's operating regime on quantitative agreement. A three-point resolution convergence study reveals a non-monotone near-probe pressure peak, attributed to a bounded ghost-fluid density inconsistency. A comprehensive coefficient sweep, conservation diagnostics, and O(N) GPU throughput scaling enable exhaustive characterization impractical in 3D. Qualitative comparison against literature evidence at 900 and 600m/s clarifies load bearing versus approximate elements. Notably, energy diagnostics reveal a modest total energy growth over the simulated window, with the fluid absorbing disproportionately more energy than the projectile relinquishes - an instructive signature of prescribed, non-back-reacting projectile kinematics that helps map the formulation's operating envelope. The resulting solver, while confined to planar geometry, delivers verified, convergence-checked performance well suited for rapid parametric design exploration.

This paper presents a procedure to optimize the way trains are driven, which pursues, in addition to fulfilling operational constraints such as admissible speeds or journey durations, the minimization of the cost related to supplying electrical energy to the trains, including the cost of the energy consumption and the cost of the power capacity utilization. This procedure combines: (i) a traffic model that merges the energy and power footprint of each rail service part of the traffic mesh, and (ii) an evolutionary computation framework that enables searching for the optimal way to drive the trains to achieve an optimal traffic mesh. This procedure is applied to a 450 km long section of the high-speed line from Madrid to Barcelona (Spain).

Origami-inspired tubular structures provide a versatile platform for shape morphing, with multistability achieved predominantly through crease-network geometry. Expanding the range of morphing behaviors can therefore require increasingly intricate crease patterns that become more difficult to model and fabricate, ultimately constraining the realizable morphing landscape. Here, we expand the design space of origami-inspired structures beyond geometry by introducing localized instabilities within the crease network, thereby creating compliant multistable structures whose local fold architectures govern global deformation and stability through both constitutive mechanics and geometric constraints. To relate local fold architectures to global multistability, we develop and experimentally validate a modeling framework in which compliant folds are represented as continuous fields that capture spatially varying bistable mechanics. Force- and displacement-controlled design maps demonstrate that global deformation and stability can be programmed through the fold architecture's local parameters. Redistributing bistability within a fixed crease-network topology shifts the global response between compliant, spatially distributed deformation in semi-bistable architectures and discrete transitions within a hierarchically organized space of stable configurations in fully bistable architectures. These results establish a local-to-global design principle for programming both the stable configurations of a structure and the transition pathways connecting them, expanding the design space for multistable metamaterials, adaptive morphing structures, and soft robotic systems.

The astronomical programme sponsored by the Saljuq Sultan Malikshah I in the late eleventh century occupies an important place in the history of Islamic astronomy. Umar Khayyam was a principal participant in this programme, which produced the Jalali or Maliki calendar and appears also to have resulted in a broader set of astronomical tables known as the Zij-i Malikshahi. A 100-star catalogue traditionally associated with these tables survives in the anonymous Arabic compendium Dustur al-munajjimin, preserved in the unique manuscript BnF Arabe 5968. This study distinguishes the catalogue from the Jalali calendar and from the lost or unidentified complete Zij-i Malikshahi, reconstructs its historical and manuscript context, and examines the provenance of BnF Arabe 5968. It presents a complete transcription of the catalogue from fols. 224r-225r and a new English translation made directly from the Arabic text, with B. A. Rosenfeld's 1961 Russian translation used as a control. The collation identifies several divergences, including a substantive correction to the longitude of entry 8, and clarifies the planetary temperament abbreviations. Rosenfeld and A. P. Yushkevich observed that 96 of the 100 stellar longitudes correspond to Ptolemaic values increased by about 14 degrees 26 minutes, while 87 latitudes agree with Ptolemy. These correspondences suggest systematic updating of inherited Ptolemaic data rather than 100 wholly independent observations, illustrating the combined roles of observation, computation, transmission, and adaptation in medieval Islamic astronomy.

We propose a formal account of how structured, shared knowledge about social relationships shapes action interpretation. The model represents relationships as constraints in a social environment, analogous to boundaries or obstacles in a physical environment and operating within the same generative model, but exerting distinct constraints on action. As an initial test of this framework, we draw on research across the social sciences to capture in the models how one dimension of relationships – formality versus intimacy – shapes how people interpret interpersonally vulnerable behavior. We test this account in stories of naturalistic everyday situations, extending structured models of action understanding to open-ended contexts. Across six preregistered experiments (N = 1,554), the model captures people's inferences about desires, physical environments, and social relationships. This work formalizes how relationships can constrain – and be revealed through – everyday action.

Direct simulation Monte Carlo (DSMC) resolves rarefied-gas dynamics without a constitutive closure, but finite-sample estimates of macroscopic moments converge at markedly different rates. We develop a non-intrusive, geometry-native machine learning reconstruction of the retained two-dimensional moment hierarchy: number density, two velocity components, translational temperature, three pressure-tensor components, and two heat-flux components. From three sampling blocks, the estimator corrects a structured prior learned from development data with a bounded term computed from the current observation, while preserving additive-moment consistency and the measured zero-frequency content. In cavity development tests, the final observation-conditioned estimator, whose prior is a trained MambaIR restoration network, reduces transverse-heat-flux error to 0.658 and 0.672 times that of a ten-block direct average at two rarefied conditions. For a hypersonic cylinder, a cylinder-centred estimator is fixed before evaluation on six new observation/reference pairs. It improves both global transverse heat flux and near-wall normal heat flux in every pair; the ratios of arithmetic-mean normalised root-mean-square errors (NRMSEs) are 0.846 and 0.793, and the Holm-adjusted one-sided exact probabilities are 0.03125.

We compare two thermodynamic prescriptions associated with the same static, spherically symmetric four-dimensional Einstein-Gauss-Bonnet anti-de Sitter black hole. Model A uses the usual Hawking temperature obtained from the surface gravity and consequently yields an entropy with a logarithmic correction. Model B preserves the shift symmetry of the scalar field at the level of the thermodynamic charges, recovers the Bekenstein-Hawking area law, and requires a modified temperature for consistency with the first law. We derive the equations of state, Gibbs free energies, heat capacities, and critical quantities of both prescriptions in the extended phase space. The two models display the same qualitative Van der Waals phase structure, but their critical scales and local stability regions differ quantitatively. In the uncharged case, Model A has a larger critical horizon radius and lower critical temperature and pressure than Model B.

This paper introduces a framework that integrates the dynamic stiffness matrix (DSM) with physics-informed neural networks (PINN). The DSM-PINN embeds physical constraints within the model and demonstrates robustness, particularly when addressing limited datasets across diverse investigations. In this approach, deep neural network outputs approximate the displacement fields of element nodes. Unlike the finite element method (FEM), the element shape functions are homogeneous solutions to the governing partial differential equation, forming the basis of the exact dynamic stiffness matrix, thereby avoiding high-order derivative terms. This matrix also serves as a frequency-domain spectral element, resulting in a strong-form PINN. The loss function is produced by connecting neural networks with dynamic stiffness matrices. We focus on utilising PINNs to resolve eigenvalue problems by employing the Wittrick-Williams algorithm, which overcomes the challenge of neural networks failing to converge to higher-order eigenvalues. Additionally, the frequency domain-PINN method is used to analyse structural dynamic responses under moving and impulsive loads, addressing the limitation of neural networks in handling complex numbers. Theoretical convergence stability of the suggested approach is also analysed even DSM is an indefinite matrix after implementing the boundary condition. The numerical results validate the practicality and efficacy of the recommended approach.

Double-diffusive convection in the diffusive regime is often observed to be in a long-lived layered state, well-known in the Arctic ocean and in volcanic lakes, and thought to exist in the interiors of giant planets. The density profile resembles a `staircase', with stacks of convective layers of uniform density separated by strongly stratified interfaces. The governing parameters are the Prandtl number $\mathrm{Pr}$, diffusivity ratio $\tau$, density ratio $R_\rho$, and Rayleigh number $\mathrm{Ra}$. In this work, we perform direct numerical simulations in triply periodic domains to systematically investigate the properties of statistically stationary double-diffusive staircases with $\tau \le \mathrm{Pr} \ll 1$. We demonstrate that they can exist for significantly larger density ratios than previously reported, and propose a new criterion for the existence of long-lived layered states. Notably, this criterion depends weakly on $\mathrm{Ra}$. In all simulations, we measure the total fluxes of density $F^{\mathrm{tot}}_\rho$, temperature $F^{\mathrm{tot}}_T$ and composition $F^{\mathrm{tot}}_C$, and the flux ratio $\gamma =F^{\mathrm{tot}}_C/F^{\mathrm{tot}}_T$. We confirm that $\gamma$ is approximately constant for moderate to large $R_\rho$ but also depends weakly on $\mathrm{Ra}$. We show that the Nusselt numbers for composition and temperature scale as $\mathrm{Ra}^{1/3}$ in this limit, which notably differs from the $(\mathrm{RaPr})^{1/3}$ scaling previously found at lower $R_\rho$. We propose a new model for these findings that is based on the rise and turbulent mixing of density anomalies that form at the edges of the interfaces. The model explains the existing low $\mathrm{Pr}$ data with reasonable accuracy.

Full-wave calculations of ion cyclotron resonance heating (ICRH) under different plasma dielectric conditions require repeated assembly and solution of large-scale discretised systems, limiting parameter sweeps and multi-case response analysis. We therefore propose an anisotropic Maxwell neural operator (AMNO) for rapid parametric modelling of ICRH full-wave responses for the Experimental Advanced Superconducting Tokamak (EAST), which learns, within the one-parameter dielectric-field family generated by varying the hydrogen minority fraction X_H over 0.01-0.05 under otherwise fixed settings, a shared solution operator from the spatially varying complex anisotropic dielectric-tensor field to the three-component complex electric field under frequency-domain Maxwell constraints. It represents global spatial coupling through spectral operator layers and local fine-scale responses, and combines sparse reference-field supervision with the frequency-domain Maxwell-equation residual. Comparisons with COMSOL reference solutions for the same EAST frequency-domain Maxwell-dielectric model show that AMNO reconstructs the principal spatial and spectral features and maintains stable accuracy for unseen interpolation test cases. With reference-field points reduced to 7.5% of the dense full-wave set, AMNO reduces the relative L_2 error by 66.1%-89.9% compared with a sparsely supervised Fourier neural operator (FNO-Sparse) under the same supervision and requires about 0.25 s for single-case inference. AMNO thus reduces dependence on dense reference-field supervision while enabling subsecond parametric complex-field inference, providing a physics-constrained and data-efficient surrogate for rapid in-range X_H sweeps and cross-case response analysis within the modelled EAST configuration.

Coarse-mode aerosols (CMAs), including pollen, spores, and dust, remain difficult to characterize in situ because conventional instruments rarely resolve particle geometry and number concentration together. We present HoloCMA, which combines digital inline holography, numerical reconstruction, and deep learning-assisted analysis for particle-resolved measurement. Its optical system targets particles from approximately 5.0 um to the millimeter scale. HoloCMA supports active sampling at up to 30.0 L/min and converts to open-path operation by removing the sampling module. With an NVIDIA GeForce RTX 5070 Laptop GPU and 8 GB VRAM, HoloCMA reports equivalent circular diameter (ECD) and number concentration in real time without sustained queue buildup up to 11.4 particles/cm3. Additional computing could extend real-time analysis to the workflow limit of 100.0 particles/cm3. We evaluated HoloCMA using polystyrene latex spheres, sodium chloride and ammonium sulfate crystals, and oleic acid droplets with nominal diameters of 4.9-11.8 um, with an Aerodynamic Particle Sizer (APS) for comparison. Across 12 comparisons, absolute differences between HoloCMA and corrected APS geometric-mean diameters ranged from less than 0.1 to 1.0 um, with a mean absolute difference of 0.5 um and a mean absolute relative difference of 8.4%. HoloCMA measures geometric size directly from reconstructed contours, whereas converting APS aerodynamic diameter requires material-specific assumptions. The APS-to-HoloCMA concentration ratio generally decreased with particle size, consistent with size-dependent transport and counting losses in the APS, although the cause could not be determined conclusively. HoloCMA thus enables continuous CMA measurements that combine geometric size, number concentration, and retained particle images, supporting classification and long-term atmospheric, environmental, and indoor-air monitoring.

Anti-similar earthquakes, those with nearly identical but flipped waveforms, remain an uncommon observation. We document three locations where these events occur at intermediate depth. The first of these is Colombia, including the well-established source of anti-similar events in the Bucaramanga Nest, and new reports in other intermediate depth seismicity clusters in the Wadati-Benioff zones of Colombia. The second is the Alaska subduction zone, and the third is the Vrancea seismic nest in Romania. These new observations, combined with reports from Japan and Chile, provide mounting evidence that anti-similar earthquake sequences might be a common or characteristic process of intermediate-depth seismicity. Either conjugate faulting promoted by eclogitization induced stresses or sub-parallel faulting can explain their occurrence at these depths. Careful examination of seismicity in other productive intermediate depth seismicity zones might reveal an even more widespread geography for anti-similar earthquakes and place tighter constraints on their underlying mechanism.