Papers

Modal synthesis is a widely-used technique for simulation of musical instrument dynamics. In the linear case, a modal decomposition leads to an uncoupled system of damped and forced harmonic oscillators which can be efficiently solved by standard time-stepping methods. However, extensions to nonlinear problems are challenging due to the presence of products of modal expansions in the governing equations. In the case of the Föppl-von Kármán plate, the nonlinear coupling between the modes is described by a fourth-order tensor and is prohibitively expensive to evaluate in the modal domain. In this work, we propose a pseudospectral method in which the products are evaluated on a grid in the spatial domain while spatial derivatives are computed exactly in the modal domain. Discrete sine and cosine transforms between the modal and spatial domains are used to impose simply supported boundary conditions for the plate. Finally, we prove non-negativity of the nonlinear potential energy of the system and employ a scalar auxiliary variable technique for explicit and stable time integration in the modal domain. As a result, we reduce the computational cost of modal synthesis while preserving its advantages like a precise control over the simulated frequency range. Sound examples are presented.

Cold heavy molecules are promising systems for exploring nuclear $\mathcal{P}$- and $\mathcal{CP}$-violating phenomena in search of new physics beyond the Standard Model. However, most proposed experimental strategies and their early realizations to date have been limited to proof-of-principle molecular species with effectively spin-zero nuclei that are not sensitive to nuclear symmetry-violating phenomena. Here, we introduce a comprehensive experimental toolbox that integrates cooling, trapping, coherent state manipulation, and a complete precision-measurement protocol that is applicable to molecules carrying relevant nuclear spins. Using ${}^{137}$Ba${}^{19}$F and nuclear-spin-dependent parity violation (NSD-PV) as representative species and benchmark application, respectively, our approach achieves a projected statistical sensitivity roughly two orders of magnitude beyond comparable molecular beams by combining techniques already demonstrated individually in current experiments. This level of precision could provide realistic experimental access not only to the enhanced NSD-PV signals arising from the heavy ${}^{137}$Ba nucleus within this molecule but also to the contributions from the lighter ${}^{19}$F nucleus, bringing direct benchmarks of nuclear ab initio theory within reach. We further identify a candidate magic wavelength as a route to second-scale rotational coherence in future experiments. The techniques developed here can be transferred to measurements of nuclear Schiff and magnetic quadrupole moments in molecules containing deformed nuclei, establishing a general platform for laboratory searches for nuclear symmetry violations.

We demonstrate pathway-selective control of extreme-ultraviolet high-harmonic generation by jointly tuning laser pulse duration ($5$ - $29$ fs) and intensity ($0.8$ - $74$ TW/cm$^2$). Many-cycle pulses at moderate intensities, $\sim 6$ TW/cm$^2$, promote cumulative carrier transfer over successive optical cycles, progressively accessing higher conduction bands. In contrast, few-cycle, high-intensity, $\sim 22$ TW/cm$^2$, pulses drive subcycle multiband dynamics that reach $25$ - $50$ eV photon energies before decoherence can suppress coherent emission. These results reveal pulse duration and intensity as decisive control knobs for high-harmonic emission, opening a route to band-structure-guided pulse design for higher energy extreme-ultraviolet light sources.

Portable smart telescopes can make introductory astronomy more observational, quantitative, and locally grounded by allowing students to acquire, share, and analyze astronomical images within a single class period. This article presents an eight-laboratory sequence for introductory Solar System astronomy using the Seestar S50 smart telescope and archived or student-collected images. The sequence begins with a galaxy-size investigation that introduces pixel scale, angular size, physical size, proportional reasoning, and measurement uncertainty before students apply the same image-to-evidence approach to Solar System objects. Subsequent activities examine the positions and apparent motion of Jupiter's Galilean moons, comparative planetology and telescope limitations, the apparent sizes of Mars, Jupiter, and Saturn, lunar phase and angular diameter, relative lunar surface history through crater-density comparisons, single-session solar activity, and multi-day sunspot tracking to estimate solar rotation. Each investigation follows a 5E-informed structure and produces a focused student product, such as a measurement table, graph, comparison chart, or claim-evidence-reasoning statement. Throughout the sequence, students must define transparent measurement rules, distinguish direct observations from interpretations, and evaluate how image scale, illumination, exposure, seeing, target visibility, and boundary selection constrain their conclusions. The activities are designed for high-school, dual-enrollment, community-college, and introductory university astronomy courses and may be implemented with live observations or prepared image sets when weather, scheduling, or local observing conditions prevent data collection.

An analytical solution for a wave velocity field scattered by a submerged permeable vertical plate-type breakwater under the linear monochromatic wave is obtained and the applications of the solution are presented. The water has an infinite depth, and the flow is assumed to be incompressible, inviscid, and irrotational, which leads to the two-dimensional potential wave theory. The permeable breakwater vertically occupies a finite interval beneath the water surface and the water flows through the breakwater. The porous boundary condition is linear, but it couples the normal velocity on the plate to the discontinuity in the velocity potential across it, so that the scattering problem does not reduce directly to a Riemann-Hilbert problem of standard form. This is resolved by a perturbation expansion in a small dimensionless parameter representing the permeability. The solution is expanded up to the first order: the leading order gives the wave scattered by the impermeable breakwater through a homogeneous Riemann-Hilbert problem, and the first-order term gives the correction for the permeability through a nonhomogeneous Riemann-Hilbert problem. The far-field amplitudes follow in closed form up to a single Cauchy principal-value integral. The effects of wavelength, breakwater length, and breakwater permeability conditions on the reflection and transmission coefficients are discussed in detail as an illustrative example of the application of the solution. An exact energy identity is also derived; it verifies the first-order solution and yields a closed-form energy-consistency bound $\varepsilon_{\max}(kb)$ on the perturbation parameter, beyond which the truncated expansion ceases to conserve energy. The hydrodynamic load on the plate is obtained to the same order, and the leading-order results are verified against the closed-form solution of Evans for the impermeable plate.

We demonstrate, by studying precession-driven flows, that inertial wave hydrodynamic turbulence can drive a robust magnetic dynamo action. Motivated by the stronger damping of large-scale geostrophic vortices in rapidly rotating planetary and stellar interiors, we introduce a controlled damping of the vortices, which usually accompany inertial wave turbulence and feed on wave energy. It is shown that even a small vortex damping results in a significant increase of the growth rate of the dynamo due to inertial waves in the kinematic regime, allowing it to persist for magnetic Prandtl numbers as low as $Pm \sim 10^{-3}$ and Poincaré numbers $Po\sim 0.025$. These critical values of $Po$ and $Pm$ for the dynamo onset decrease with increasing Reynolds number. The onset and growth of the dynamo appear to correlate with the coherent fluctuations of kinetic helicity. Spectral analysis shows that magnetic energy growth is primarily due to inertial-wave-induced induction over a broad range of scales. These results establish inertial waves as an efficient mechanism for magnetic field amplification in rapidly rotating low-$Pm$ flows relevant to planetary and stellar interiors.

Spin-rotators in the the few-MeV range require large trajectory deflection angles in order to change the spin direction appreciably. We describe a magnet system that accumulates adequately large bending angles in a small footprint and, at the same time, supports continuous-wave operation.

We derive the Hamiltonian and the transfer matrix of a Wien-filter with vertical magnetic field from first principles.

Using official government data sets of USA and France we analyze the occurrence/frequency/popularity distributions of given names on a time scale of more than 100 years. These distributions are characterized through the Lorenz and Pareto curves broadly used in the analysis of wealth inequality in the world. These curves remain stable during the considered time period with the Gini coefficient remaining in the narrow range 0.85-0.95. As for the case of wealth inequality, we show that the distributions of names are well described by the Rayleigh-Jeans (RJ) thermalization and condensation phenomenon well studied in various physical systems. The RJ thermalization results from two integrals of motion being analogous to energy and probability norm conservation in physical systems with energy states corresponding to popularity levels of names. Time correlations between names are also determined showing their stability until the middle of the twentieth century and a significant change after that.

We investigate pseudovorticity generation in Gaussian beams undergoing self-focusing under amplitude and phase noise, using the cubic-quintic nonlinear Schrödinger equation. Pseudovorticity, defined as the curl of the optical momentum flux, characterizes local rotational flow in the absence of phase singularities. Our numerical simulations show that thermal amplitude and phase noise induce a multipolar pseudovorticity pattern. Unlike the pure cubic case, where noise asymmetries are radiated away during collapse, the quintic saturation arrests collapse and traps the noise in the resulting soliton. Hence, pseudovorticity multipoles persist, oscillating at the focusing-refocusing period. These results suggest a potential pathway for controlling local optical torque through noise engineering.

Nanoscale devices that integrate materials of different dimensionalities (0D, 1D, and 2D) hold great potential for advanced applications in photonics and optoelectronics. A fundamental requirement for the development of such devices is the engineering and control of light-matter interactions beyond the simple enhancement or quenching of linear and nonlinear optical emission. In this study, we demonstrate control over nanoscale light-matter interactions by achieving twist-angle tunability of the nonlinear optical response in a hybrid system composed of a ZnO nanowire and a monolayer of WSe$_2$. By varying the relative orientation between the ZnO polar axis and the WSe$_2$ crystal axes, we realize both constructive and destructive interference in second-harmonic generation, as well as full material selectivity in second harmonic polarization-dependent measurements. These outcomes arise from the distinct dimensionalities and symmetries of the hybrid constituents, underscoring the generality of our approach. Thus, our work presents an advanced framework for the design and control of nonlinear light-matter interactions in nanoscale hybrid devices, thereby paving the way for their future use in photonic and optoelectronic technologies.

We study the simultaneous vanishing-viscosity and vanishing-resistivity limit of steady incompressible MHD flows in a disk. The boundary velocity is a small nonaxisymmetric perturbation of a rigid rotation with mean angular speed \(\alpha\), while the prescribed tangential magnetic trace has mean \(\beta\). Assuming \(\alpha\neq0\) and the non-Alfvénic condition \(|\alpha|\neq|\beta|\), we construct solutions converging on compact interior subdisks to a rigidly rotating ideal MHD core with constant vorticity and out-of-plane current density. A new MHD–Wood law determines the two core rotations from the boundary data: the velocity core is selected by a coupled kinetic–magnetic balance, whereas the magnetic core is fixed by the imposed mean circulation. Consequently, zero circulation gives complete interior magnetic expulsion, while nonzero circulation leaves a uniform magnetic rotation after the nonaxisymmetric modes are confined to a thin boundary layer. This provides a fully coupled realization of Prandtl–Batchelor selection and flux expulsion; unlike classical kinematic models, the magnetic field actively changes the flow and need not be weak. The proof combines a non-Alfvénic coercive theory for a periodic MHD boundary layer, global matching of the two fields, and a coupled stability estimate adapted to the magnetic boundary condition. A separate conditional rigidity argument, using exact viscous identities and local convergence but no interior asymptotic expansion, explains the same core structure for a broader single-eddy family.

Autonomous agents choose actions using scores that may not reflect experimental success. We developed OPERA, an operator-residual framework for optical experiments. It represents experimental actions as optical operators and evaluates their outcomes using physically interpretable residuals. Operators specify executable changes to measurement, control or reconstruction, while residuals report departures from specified physical conditions. The agent uses both to select, combine or generate operators, and physical performance is evaluated independently against a withheld reference. Across three optical tasks, score-only feedback produced score increases without physical improvement in 23.6–39.0% of decisions, compared with 0.9–1.9% for operator-residual feedback. Operator-residual feedback increased the probability of reaching and maintaining task targets and reduced experimental budgets. Protocols selected in digital twins were transferred to three optical instruments, and repeated experiments showed a lower projection budget in structured-light reconstruction. Together, operators and residuals guide autonomous decisions using measurable physical evidence.

We investigate Hamiltonian curl-force systems with indefinite kinetic energy. We first reconsider Berry's polynomial Hamiltonian curl-force model, whose numerically observed closed trajectories motivated an integrability conjecture. A Painlevé analysis yields a non-principal resonance spectrum, so that the corresponding Laurent series cannot accommodate the required number of arbitrary constants of the general solution. The model therefore fails the standard Painlevé test. We then introduce a four-parameter curl-force family and identify the parameter locus on which this system is integrable. We construct a second Hamiltonian, compatible Poisson tensors, separated complex characteristic variables, and a Lax representation. More generally, the separated form yields polynomial integrable curl-force Hamiltonians of arbitrary degree. We also show that the same construction admits a higher time-derivative potentialisation whose free limit is the degenerate Pais-Uhlenbeck oscillator. Finally, we analyse zero-curl invariant reductions and elliptic periodic solutions, and exhibit an isolated periodic orbit outside the integrable regime. This illustrates that closed trajectories alone do not imply Liouville or Painlevé integrability.

Electric-field-induced second-harmonic generation (EFISH) is an established laser diagnostic for quantifying electric fields in plasmas, yet ensuring field accuracy remains challenging given the coherent, path-integrated nature of the signal. We address this via machine learning, developing a Polarization-Conditioned Fourier-enhanced Deep Operator Network (PC-FDON) – a unified operator-learning model that reconstructs field profiles from EFISH measurements across both polarizations and various optical parameters. Its architecture incorporates three advances: (i) a Fourier-enhanced branch providing inductive bias for the Gouy phase shift and wave-vector mismatch; (ii) a polarization-conditioning branch encoding signal polarization via Feature-wise Linear Modulation (FiLM) and gated units, enabling one model to handle both polarizations; and (iii) a physics-informed loss enforcing self-consistency with the governing EFISH equation. Trained on data spanning multiple function families, polarization states, and phase-mismatch values, PC-FDON achieves promising reconstruction under noise-free, incomplete, and noisy inputs, with generalizability comparable to our previous polarization-specific model. Pointwise epistemic uncertainty estimates via Monte Carlo dropout reflect model confidence and enable out-of-distribution (OOD) detection through a location-dependent exceedance fraction metric. Validation is performed on realistic electrode configurations under both polarizations and varying Rayleigh ranges, including a simulated surface dielectric barrier discharge where the framework correctly flags OOD inputs, and experimental data showing good agreement with simulations. The architecture – spectral inductive bias, conditional modulation, and dataset-specific uncertainty – shows strong potential for broader application beyond plasma diagnostics.

Dissipative Kerr soliton microcombs enable compact and scalable frequency comb sources for precision metrology, spectroscopy, communications and coherent LiDAR, where broad and reliable frequency tuning is essential. Thermo-optic response can support thermal locking during soliton operation, enabling resonance tracking and thereby extending the tuning range, albeit modestly. However, it also induces pronounced thermal instability during soliton initiation, hindering reliable access to this extended operating regime and limiting practical deployment in applications requiring frequency agility. Here we show that strong mode coupling reshapes the effective detuning trajectory governing soliton formation, establishing a distinct operating regime in which thermo-optic response is significantly reinforced and constructively harnessed. In this regime, soliton formation proceeds without the thermal instability inherent to conventional operation, enabling robust soliton generation in material platforms previously limited by strong thermal effects. Importantly, the enhanced thermo-optic response strengthens thermal locking during soliton operation, enabling more effective resonance tracking and substantially extending the tuning range. Leveraging this regime in AlGaAs-on-insulator multimode microresonators, we demonstrate soliton generation with a tuning range approaching 100 GHz at a pump power of 32 mW. The same mechanism further enables frequency-agile operation through direct pump-frequency tuning without auxiliary stabilization, allowing massively parallel chirped comb generation with more than 90 channels exhibiting frequency excursions exceeding 10 GHz. These results establish a general operating principle for transforming thermo-optic effects from a limiting factor into an active resource, enabling robust and frequency-agile integrated soliton microcombs.

Modern physics has achieved extraordinary empirical success while retaining much of the absolute, unobservable structure introduced by Newton, largely without questioning its necessity. We investigate how far this structure can be eliminated by adopting a relational ontology guided by Leibniz's principle of sufficient reason. Removing absolute position, orientation, time and, finally, scale leads naturally to a formulation of the gravitational $N$-body problem where only dimensionless ratios are physically meaningful. Within this framework, the scale-invariant variety $V$ becomes a central quantity, providing a measure of structure, a natural ordering of shapes, and an emergent gravitational arrow of time. We argue that the resulting formulation unifies classes of Newtonian solutions previously regarded as distinct, uncovering a possible new symmetry, suggests a notion of explanation based on timeless spatial correlations rather than temporal evolution, and points towards a more economical ontology. Although developed in the context of Newtonian gravity, the principles proposed here may also offer a new perspective on general relativity and quantum mechanics.

Symmetries of a crystal often restrict its physical properties. In particular, they determine possible forms of the tensors that describe interatomic exchange interaction, which governs a wide range of magnetic phenomena. Computationally demanding first-principles calculations of the exchange tensors can be greatly simplified by taking the symmetry constraints into account. Here, we present Jsymm, a Python package that derives the most general symmetry-compatible form of the exchange tensors directly from the crystallographic data. For any bond formed by magnetic ions, Jsymm produces the tensors of the Dzyaloshinskii-Moriya and anisotropic Heisenberg exchange interaction in symbolic form, as well as the tensors for all other bonds related to it by symmetry. This reduces the number of independent model parameters, dramatically lowering the computational cost of the ab initio calculations and preventing unphysical results arising from symmetry violations. The package accepts standard CIF files and provides a web interface in addition to an interactive text mode and a Python library. We demonstrate its utility on La$_2$CuO$_4$ and $\alpha$-Fe$_2$O$_3$, reproducing known symmetry constraints and revealing additional relations between components of the exchange tensors of different bonds.

A combination difference analysis of Fourier transform microwave spectroscopy (FTMW) measurements of $^{174}$YbO combined with earlier near-infrared chemiluminescence data have resulted in much improved YbO rotational and centrifugal distortion constants. These have been confirmed in a multi-isotopologue analysis of further FTMW measurements of $^{172}$YbO and $^{176}$YbO and an analysis of nuclear-size-dependent Born-Oppenheimer breakdown effects in the molecule. Multiple excited electronic states overlap with low-lying excited vibrational levels of the electronic ground state leading to irregularities in its vibrational spacings and other previously observed electronic manifolds. This has been modeled with a matrix of the vibrational levels of the ground and multiple interacting states assuming Morse potentials and including electronic Hamiltonian matrix elements mixing the states. Vibrational level overlaps were calculated numerically assuming Morse vibrational wavefunctions. The resulting de-perturbed potentials for the states inform continuing experimental and theoretical work on this and other ytterbium-containing molecules.

Many of the smooth functions that matter most in physics are precisely the ones that standard neural network methods struggle to fit accurately. Here we present NestyNet, a coupled model-and-optimizer framework capable of fitting such targets to high accuracy while also delivering their gradients, Hessians, Laplacians, and antiderivatives analytically and at low cost. This makes it a natural substrate for scientific machine learning tasks. The model is a deterministic segmented analytic surrogate, and its optimizer is a second-order Levenberg–Marquardt scheme whose damping and linear solves are tailored to the stiff, strongly correlated parameter geometries induced by multiscale and sharply structured targets typical in physics and other scientific applications. On the AI Feynman benchmark of 120 physics equations, NestyNet achieves median improvement factors of $2\,100\times$ for function values, $1\,400\times$ for first derivatives, and $780\times$ for second derivatives relative to standard neural networks trained with first-order optimization (Adam). Even after refining those fits with quasi-Newton (L-BFGS) optimization, the corresponding improvements are $540\times$, $450\times$, and $250\times$. Owing to the analytic design it is up to $\approx 44\times$ faster than vectorized automatic-differentiation (autograd) baselines, with a margin growing with model size. The same analytic-derivative framework also supports vector- and complex-valued targets, measurement uncertainties in both inputs and outputs, and constraints, and its modules can be composed flexibly to build scientifically useful model architectures, all without reverting to autograd. Together, these components provide a practical modular framework for fitting difficult scientific surrogates while delivering accurate differential operators for subsequent analysis.

We calculated shear viscosities of 15 neat molecular liquids from equilibrium molecular dynamics (MD) simulations using the OrthoBoXY approach and compare them to viscosities calculated via the Green-Kubo method. Data from both methods agree very well. Here, we show how to avoid pitfalls while computing the OrthoBoXY-data to obtain optimal results. From simulations of multiple system sizes, we could verify that the viscosity of molecular liquids is not influenced by finite size effects down to systems as small as 250 molecules. Moreover, we demonstrate that also the standard error of the viscosity is nearly independent of the system size. This is shown to be a consequence of a compensation effect of an increasing accuracy of the self-diffusion coefficients with increasing systems-size and the system-size dependent weighting according to the OrthoBoXY-equation. As a consequence, we suggest that it is preferable to run simulations of smaller systems with longer simulation times rather than larger systems with shorter simulation runs. In addition, we discuss a refinement of the recently introduced "recipe" for OrthoBoXY simulations block-lengths $\tau_\mathrm{block}$. Based on data from simulations with varying run-lengths, we suggest the following modification: for highly viscous systems, the value of $\tau_\mathrm{block}$ might safely be scaled by a factor of $1/8$, significantly reducing the computational resources needed. For less viscous systems, the value of $\tau_\mathrm{block}$ might safely be scaled by a factor of $1/4$. For systems with high fluidity, the value of $\tau_\mathrm{block}$ should not be scaled down in order to achieve reliable results. When using a smaller system size of 250 molecules, these refinements are leading up to a 24-fold reduction in computational cost compared to the previous recommended set-up without sacrificing numerical accuracy.

Time-varying bivariate fields arise in many scientific applications, where the relationship between two scalar quantities evolves over time. While topological methods such as merge trees provide an effective framework for identifying and tracking features in univariate data, analogous approaches for bivariate fields remain comparatively underexplored. Reeb spaces extend topological analysis to multivariate data by representing fiber connectivity through a collection of interconnected sheets, making these sheets natural candidates for describing bivariate structures. However, establishing temporal correspondences between sheets is challenging due to the structural complexity of Reeb spaces, sensitivity to noise, and the difficulty of defining meaningful similarity measures across timesteps. We present a framework for tracking Reeb space sheets in time-varying bivariate fields. The method establishes correspondences between sheets in consecutive timesteps using complementary similarity measures defined in the spatial domain and the range space. We evaluate the method on a synthetic torus dataset and two time-varying molecular electronic structure datasets. The results show that Reeb space sheet tracking reveals persistent structures and highlights interesting intervals of temporal change. Overall, the results demonstrate that Reeb space sheets can serve as trackable topological structures and provide a foundation for the visual analysis of time-varying bivariate data.

Charge separation during the breakup of water drop has been recognized since the early studies of waterfall and spray electrification, yet the role of controlled drop fragmentation at structured liquid-repellent surfaces remains unclear. Here we show that water drops impacting superhydrophobic meshes generate charged secondary droplets as liquid penetrates and fragments through the mesh pores. By combining Faraday-cup charge measurements with high-speed imaging, we identify how the charge depends on the Weber number and on the pathway of spray formation. No measurable charge is detected below the penetration threshold. At low Weber numbers, recoil jet formation gives a high charge per unit spray mass, whereas at intermediate Weber numbers both recoil jets and impact-induced jets contribute to charging. At higher Weber numbers, pancake bouncing suppresses recoil jet formation, so charging is dominated by impact induced penetration and the total charge approaches a saturated value. We further show that smaller mesh pores enhance the charge-to-mass ratio and that conductive meshes provide stable charging under repeated impacts by dissipating residual surface charge. These findings provide design principles for superhydrophobic mesh platforms for spray charging and rain-driven energy harvesting.

Existing scintillation-detector models typically treat scintillation kinetics, optical transport, silicon photomultiplier (SiPM) response, and timing statistics separately, limiting end-to-end prediction of waveform formation and detector performance. We present a unified analytical framework for lutetium-yttrium oxyorthosilicate (LYSO)-SiPM scintillation detectors that links these processes within a single forward model. The framework incorporates finite thermalization, depth-dependent optical transit-time spread, and microcell occupancy dynamics to provide a physics-based description of macroscopic pulse formation. It yields closed-form exponentially modified Gaussian pulses in the linear regime, state-dependent integral solutions in saturation, and recovers the conventional bi-exponential pulse model—ubiquitously used yet hitherto only empirically justified in scintillation pulse fitting and sparse-sampling reconstruction—as a controlled reduction of the full optoelectronic cascade. Experimental validation on 10,000 directly digitized Na-22 pulses shows that the dynamic saturation model captures amplitude-dependent waveform distortion and is favored by the Akaike information criterion (AIC) over a matched bi-exponential baseline in 100/100 high-amplitude pulses and 98/100 medium-amplitude pulses. By coupling the dynamic triggering rate to compound Poisson statistics, the framework also predicts current-variance envelopes and Fisher-information-based timing limits, including an intrinsic coincidence timing resolution lower bound of about 100 ps full width at half maximum (FWHM) for a reference 511-keV LYSO-SiPM configuration. These results deepen the physical understanding of scintillation-detector waveform formation and timing limits by clarifying how scintillation kinetics, optical transport, and SiPM microcell dynamics jointly shape the observed response.

Responding productively, in real time, to the reasoning students actually produce is among the most difficult and slowest to acquire of the skills physics teachers develop, and prospective teachers get few opportunities to practise it before entering a classroom. In this pilot study, we describe a simulated class of five AI students, each consistently enacting a distinct reasoning pattern drawn from the dual-process theory (DPT) "hazards" framework of physics education research, and report on its first use in a university course for prospective physics teachers. Fifteen graduate students worked through an instructional sequence on DPT and questioning strategies. They then diagnosed two parallel sets of written vignettes, in a crossover arrangement, before and after interacting in pairs with the simulated class on a static-friction problem. The data set is completed by individual written hypotheses and reflections, the session logs and a short feedback questionnaire. Diagnostic scores improved significantly from PRE to POST (n = 11 paired, Wilcoxon p = 0.014, r = 0.79; on a 0-18 scale). During the simulation itself, however, participants asked predominantly uniform guiding questions, and the DPT vocabulary they had been taught appeared in only 2 of 71 substantive teacher turns, while seven of thirteen POST sheets used it readily. We read this knowing-doing gap not as a failure but as a snapshot of where each participant stands on the developmental trajectory of responsiveness to student ideas, a trajectory the simulation makes visible with transcript-level granularity. We discuss design, findings and implications for physics teacher preparation.

Whereas conventional Gaussian focusing gradually concentrates optical energy around the focal plane, abruptly autofocusing waves maintain a low peak intensity over most of their evolution before undergoing a sudden, high-contrast intensity surge at a prescribed focus. Since their introduction in 2010, their two-dimensional spatial realizations have enabled applications ranging from particle manipulation and material processing to terahertz generation and nonlinear optics. The recent work of Cao et al. marks the transition from (2+1)-dimensional spatial autofocusing to the full space-time domain through the experimental synthesis of spherical Airy wavepackets. This advance opens new opportunities for ultrafast structured light, tightly localized energy delivery, and nonlinear photonics.

We introduce a majority-rule model in which collective reversal can be activated in highly aligned groups even when a limited number of members dissent. The dissent tolerance $d$ extends the strict-unanimity dynamics by making near-unanimous group compositions eligible for reversal. Mean-field analysis and simulations reveal that this change qualitatively alters the phase structure. Under strict unanimity, a physically accessible transition exists only for $n=3$ and $n=4$. Allowing dissent restores transitions at larger interaction sizes, replacing the fixed interaction-size threshold with an accessibility boundary in the $(n,d)$ plane. When the activation window is sufficiently broad, directional asymmetry can eliminate one of the two ordered attractors through a saddle-node bifurcation, producing a single stable collective state. In the one-sided case, increasing the dissent tolerance can shorten the transient approach to consensus but leaves its leading logarithmic dependence on population size unchanged. Activation selectivity acts as an independent control parameter for collective ordering, bistability, and consensus dynamics.

Multiphase electrohydrodynamic (EHD) flows play a crucial role in various engineering applications. However, existing numerical studies on three-phase electrohydrodynamic systems predominantly rely on phenomenological models, often neglecting thermodynamic consistency and critical surface charge convection mechanisms. To address these fundamental gaps, this paper proposes a thermodynamically consistent three-phase EHD model derived strictly from the Onsager variational principle. This theoretical framework intrinsically guarantees thermodynamic consistency and accurately captures complex multiphysics interactions without requiring a priori assumptions. Furthermore, a mesoscopic lattice Boltzmann method is developed to solve the proposed model, enabling the natural capture of interfacial evolution and charge transport. The accuracy of the numerical framework are rigorously validated against several benchmark cases, including electroosmotic flow in microchannels, the spreading of a three-phase liquid lens, the equilibrium of static compound droplet, and the deformation of compound droplet under uniform electric field. Using this validated framework, we investigate EHD applications, specifically simulating the complex dynamics of double droplet coalescence and separation under electric field, as well as the behavior of droplets subjected to combined EHD and shear flow. Overall, this work provides a robust, thermodynamically reliable numerical tool for exploring the highly nonlinear behaviors of multiphase EHD systems.

In this work, we present two novel strategies to impose high-order boundary conditions on fixed and moving curved domains, approximated with piecewise affine triangulations. Achieving high-order accuracy on curved domains requires tackling both the PDE discretization error and the geometrical error simultaneously. While the former can be reduced by employing high-order numerical methods such as finite volume and discontinuous Galerkin, the latter demands either a high-order parametrization of the physical domain or a consistent approximation of the boundary conditions. Minimization-based approaches like the Reconstruction for Off-site Data (ROD) method allow one to skip the construction of high-order curvilinear meshes by defining high-order consistent boundary conditions on a computational boundary that does not match the physical one. The ROD approach mitigates the second-order geometrical error by retrieving a modified polynomial in each boundary cell, which enforces the boundary conditions exactly on the physical boundary. However, the standard ROD method requires the inversion of a local linear system, whose cost grows with the polynomial degree and mesh refinement. Inspired by a recent one-dimensional analysis, we show that ROD-type approaches can be recast as simple polynomial corrections, applicable without any linear system inversion. This greatly simplifies the development of minimization-based boundary treatments and reduces the associated computational cost. To prove the wide applicability of our strategy, we develop it within a Runge-Kutta discontinuous Galerkin framework and an ADER arbitrary-Lagrangian-Eulerian finite volume framework for compressible flows on fixed and moving domains. Several numerical experiments with Dirichlet and slip-wall boundary conditions are presented, with convergence analysis up to fifth order in both 2D and 3D.

Full waveform inversion (FWI) can recover high-resolution subsurface velocity models. Conventional waveform-difference objectives, however, are vulnerable to cycle skipping when the starting model is inaccurate. We introduce an FWI objective that compares features produced from modeled and observed seismic traces by SeisLM, a pretrained seismic foundation model. The SeisLM encoder remains frozen during inversion, and the feature discrepancy is differentiated with respect to the modeled traces to construct an adjoint source compatible with the standard adjoint-state framework. We also test a scheduled hybrid loss that combines the SeisLM feature loss with the conventional $L_2$ objective. Time-shift diagnostics show that the loss computed from features produced by the pretrained encoder has a broader and smoother basin around the correct alignment than either the waveform $L_2$ objective or the feature loss obtained from an encoder with the same architecture and randomly initialized parameters. In the Marmousi experiment, the SeisLM and hybrid objectives produce similar improvements during early-stage inversion and provide useful models for subsequent reflection-based $L_2$ refinement. In the 2D Overthrust experiment, which begins from a laterally invariant linear-gradient model, the SeisLM feature-loss workflow outperforms the conventional and hybrid workflows, indicating that introducing the $L_2$ contribution too early can reintroduce cycle-skipping sensitivity. In the 3D Overthrust experiment, conventional $L_2$ inversion stalls near the initial linear gradient, whereas the SeisLM feature loss guides the inversion toward a background model from which $L_2$ refinement recovers the principal structures. These results support using features produced by pretrained seismic networks to define early-stage FWI objectives rather than complete replacements for waveform-domain misfits.