Papers

We develop structure-preserving methods for the compressible Euler equations with gravity in vector-invariant form and potential temperature as a prognostic variable within the flux-differencing discontinuous Galerkin spectral element method (DGSEM) framework. By discretizing the nonconservative terms as symmetric and antisymmetric products, we derive two-point numerical fluxes that conserve both the thermodynamic entropy and the total energy. Moreover, we design an entropy-stable numerical flux that is well-balanced for both isothermal and isentropic background states. All properties are shown to carry over to the high-order DGSEM on general curvilinear meshes. Several numerical examples confirm the theoretical findings and show the robustness and accuracy of the scheme for use in modern dynamical cores for atmospheric flows.

We show that the expressions for the matter Lagrangian \(L_m\) and the metric variation \(\delta T_{\mu\nu}\) of a perfect fluid obtained in previous studies appear to be inconsistent with the standard energy-momentum tensor under general conditions. Consequently, a large number of studies in astrophysics and cosmology relying on these expressions may need to be re-examined. By performing a series of straightforward calculations directly on the standard energy-momentum tensor \(T_{\mu\nu}\) together with the particle number conservation condition, we derive an expression for \(\delta T_{\mu\nu}\) that is independent of the choice of \(L_m\). Applying this result to \(f(R,T)\) gravity, we obtain the exact form of the tensor \(\Theta_{\mu\nu} = g^{\sigma\rho} \frac{\delta T_{\sigma\rho}}{\delta g^{\mu\nu}}\), which remains an important yet long-standing controversial quantity. This expression is shown to hold also for radiation, regardless of whether particle number is conserved. A major result is that if the energy-momentum tensor \(T_{\mu\nu}\) of the Universe consists solely of standard components (baryonic/cold dark matter, radiation, and the cosmological constant), then \(f(R,T)\) gravity satisfies the conservation law \(\nabla_\mu T^{\mu\nu} = 0\) for any function \(f(R,T)\). This contrasts with previous studies, which found that the conservation law holds only for a restricted class of \(f(R,T)\) functions. Applying the same formalism to stellar interiors, we derive a class of functions that preserve the conservation law. We construct a specific \(f(R,T)\) model that is consistent at both cosmological scales and in high-density objects such as neutron stars. Remarkably, the same parameter set in this model simultaneously alleviates the Hubble tension and reproduces the observed mass-radius (M–R) relation of neutron stars.

Body-body interactions have long been investigated to leverage the performance of various fluid-based machines. This study analyzes the flow interaction between a cylinder and a NACA0012 airfoil using direct numerical simulation and machine learning. We consider a two-dimensional incompressible flow at Reynolds number 100, where the airfoil is positioned in the wake of a cylinder. By sweeping the parameter space, composed of the distance between the cylinder and the airfoil $\Delta x$, the relative height $\Delta y$, and the angle of attack of the airfoil $\alpha$, four characteristic vortex-shedding regimes are observed. This study particularly focuses on suppressed vortex shedding at a certain arrangement as oscillation death in coupled oscillators, with the theoretical prediction of flow stability on a machine-learned low-order coordinate. Independent flows around each body are regarded as a system that exhibits isolated periodic vortex shedding at infinite distance, and interactions appear at smaller distances. We employ a synchronization-theoretic autoencoder to derive models for two coupled oscillators from an aerodynamic coefficient. The proposed approach, which enables the assessment of system stability and the prediction of vortical interaction behavior, may pave the way for the analysis of unsteady body-body interactions from the data-driven and synchronization perspectives.

Groups of individuals can solve collective problems more accurately than any single member, by aggregating their opinions. Recent theoretical work has identified individual-level reward schemes that allow uninformed individuals to evolve collective intelligence from the bottom up, through social learning. Yet these results are restricted to linear prediction problems and simple averaging, while the decision tasks that real groups confront are often non-linear, and the institutions that aggregate opinions are seldom single-layer averages: districts elect representatives who in turn vote on policy, referees advise editors who decide on publication. Here we develop a framework for the evolution of collective intelligence in multi-layer voting populations, where individuals observe limited information and groups recursively aggregate their opinions by majority rule. We prove that single-layer voting cannot solve non-linear classification problems under any individual reward scheme. We then identify a "marginal feedback" payoff structure, which rewards individuals only when their opinion is pivotal in their group, and at every layer above them. This reward scheme induces a layered population to evolve accurate collective solutions to complex, non-linear decision tasks through individual-level peer imitation alone. The collective behavior that emerges is equivalent to a multi-layer perceptron in machine learning. Our results provide a naturalistic account of hierarchical institutions, in which the outsize importance of swing voters is the incentive that sustains collective accuracy; and they identify the credit-assignment rule in machine learning as not just an engineered solution but a natural evolutionary outcome.

A series of 11.6-d-duration photon-counting experiments, employing a broad variety of light sources with different statistical properties and optical spectra, were carried out over a 1.5-yr period. All of the photon-count spectra at baseband followed a common $1/f^2$ form over the frequency range $1 \times 10^{-6} \leqslant f \leqslant 5 \times 10^{-4}$ Hz, corresponding to a timescale range $33$ min $ \leqslant T_f \leqslant 11.6$ d, where $T_f \equiv 1/f$. The lower and upper timescale limits were established by the photodetector noise floor and the duration of the individual experiments, respectively. Unlike ordinary Brownian motion, all of the measured photon-count sample paths exhibited irregular long-timescale fluctuations, with durations ranging from hours to days. It has been established that the photon-count spectra cannot plausibly be ascribed to fluctuations of the current, voltage, or temperature of the source or the detector, nor to technical sources of noise associated with the optical system or local environment. Although the physical origin of the photon-count fluctuations remains unresolved, several heterodox hypotheses are set forth. From a statistical point-of-view, the photon counts appear to follow a doubly stochastic Poisson process with a slowly varying random intensity. Analogous experiments that rely on ionizing radiation and direct-conversion solid-state radiation detectors are proposed.

Global magnetohydrodynamic (MHD) simulations provide the complete plasma state of the heliosphere, but their computational cost limits applications requiring repeated model evaluations. We introduce SNOW (Solar Neural Operator for Wind), a fast and differentiable surrogate for global MHD solar wind. SNOW combines a rotational ballistic approximation, a spherical harmonic neural operator, and causal radial context to autoregressively propagate all eight MHD variables from 20 to 240 Rs through consecutive shell to shell transitions. Trained and evaluated using AWSoM simulations spanning a solar cycle, SNOW remains stable across the complete rollout. The model successfully reproduces the large scale plasma and magnetic field structures, including fast and slow wind streams, magnetic polarity sectors, vector orientations, fieldline connectivity, and bulk-flow structures. Additionally, the magnetic divergence and induction diagnostics remain comparable to the reference MHD solutions. The complete three-dimensional solution is generated in less than one second on a single GPU. These results demonstrate the feasibility of fast neural emulation of global MHD solar wind solutions while retaining physically meaningful plasma and magnetic field structure.

Long-term multi-turn tracking is required to study nonlinear phenomena in circular accelerators, such as resonances, chaotic motion, and the dynamic aperture. General-purpose neural networks do not preserve the symplectic structure of Hamiltonian dynamics, so their errors can grow over many turns. Symplectic neural networks (SympNets) guarantee symplecticity through their architecture rather than through a loss penalty. In this work, we use a SympNet to learn the normal-form transformation of a nonlinear map from tracking data. In the learned coordinates, the dynamics become a rotation of each mode, whose amplitude-dependent phase advance is given by a second network. We demonstrate the method on a four-dimensional McMillan-type map. The model reproduces the one-turn dynamics, the learned phase advances stay constant along each trajectory to within $\sim 10^{-5}$~rad, and orbits become close to circles in the learned coordinates at small and moderate amplitude. At large amplitude the learned orbits spread noticeably, and the cause of this degradation is not yet established. The approach is a step toward fast, structure-preserving surrogate models for lattice analysis and online beam-dynamics applications in storage rings.

Accurate skull-to-array registration is essential for transcranial focused ultrasound (tFUS) because CT-derived skull models must be aligned with the physical-array coordinate system to support patient-specific aberration correction. Current workflows typically use MRI and/or external tracking to establish this spatial relationship, adding imaging infrastructure and coordinate transformations to the treatment workflow. Here, we describe an MRI-free CT-to-ultrasound registration framework using a hybrid hemispherical CMUT tFUS array that combines a sparse therapeutic array with an integrated CMUT US-Cross imaging array. The therapeutic array provides pulse-echo measurements of skull location, while the US-Cross array provides local high-resolution images of the skull surface. The approach was evaluated using a CT-derived outer cortical skull surface across a 25-pose matrix with 10-mm lateral offsets between the skull and array centers and +/-5 degree angular perturbations. Five randomized radial-noise seeds were applied to therapeutic pulse-echo measurements to model measurement or element-placement errors, yielding 125 pose-seed realizations per noise and active-element setting. US-Cross imaging features were generated using Field II and delay-multiply-and-sum plane-wave compounding. Four registration modes were evaluated: Therapeutic only, US-imaging only, Sequential, and Fused registration. Fused registration yielded the best overall performance, with a median total displacement error of 0.271 mm [0.169-0.420] and a median rotation error of 0.904 degrees [0.432-1.639]. These results support an all-ultrasound-based approach using a hybrid CMUT tFUS array for MRI-free CT-US skull registration.

Reconstructive spectrometers (RSs) shift spectral analysis from hardware-heavy dispersion to encoding-decoding schemes. In the speckle-based RSs, spectra are encoded into disordered intensity patterns and then recovered algorithmically. However, characterizing such spectral-encoding transmission matrices (TMs) typically demands empirically complex calibrations, which rely on expensive tunable light sources to generate known wavelengths. In this work, we demonstrate a fully calibration-free RS that leverages conical phase modulation from an axicon. The target spectra are encoded into a Bessel-form intensity profile, enabling computational construction of a deterministic TM and thus completely removing the need for optical calibration. With this computer-generated TM, broadband spectral reconstruction is experimentally achieved across a 650 nm range (1050-1700 nm)–nearly three times the bandwidth of existing calibration-simplified RSs–while a spectral resolution of 2.9 nm remains comparable to that of these counterparts. Compared with an RS requiring optical calibration for equivalent performance, our solution achieves an approximate 36-fold cost reduction.Unlike most speckle RSs, the axicon RS requires no fixed input polarizer, further enhancing energy efficiency and simplicity through polarization-insensitive operation. To the best of our knowledge, this is the first reported experimentally calibration-free RS, featuring superior simplicity, practicality, and cost-effectiveness for practical applications.

The identification of plastic inorganic semiconductors becomes challenging when their mechanical responses depend on crystallographic orientation, sample size, and loading conditions. Using layered GeSe as a model system, we examine its deformation behavior through macroscopic compression, bending, conventional micropillar compression, and eccentric micropillar compression. Under macroscopic compression perpendicular to the layers, GeSe sustains approximately 23% strain without fracture, whereas bending along the c-axis armchair direction produces brittle cleavage fracture. Conventional micropillar compression results in brittle fragmentation, while eccentric loading introduces a shear component that activates pronounced interlayer sliding and accommodates deformation. These contrasting responses reflect the coupled effects of bonding topology, interlayer van der Waals interactions, defect density, stress constraints, and strain path on the competition between sliding and fracture. The results highlight the limitations of identifying plasticity from a single direction, scale, or test and support a systematic evaluation framework combining multiple directions, length scales, loading modes, and characterization techniques. More rigorous and unified criteria are needed to guide reliable materials selection for flexible electronics and devices integrated on curved surfaces.

Design-dependent wall velocities are difficult to treat in density-based fluid topology optimization. This difficulty arises because the fluid-solid interface is represented implicitly and evolves with the design. This paper proposes a diffuse-interface formulation for topology optimization of steady incompressible Navier-Stokes flows with design-dependent wall actuation. A continuous topological description field parameterized by compactly supported radial basis functions (CS-RBFs) provides the local interface orientation, and its regularized projection defines the pseudo-density for Brinkman flow analysis. The wall velocity is imposed on a fixed mesh through an equivalent volumetric momentum source, which is localized by a diffuse-interface measure constructed from the pseudo-density and the gradient of the description field. Assuming a locally planar interface and uniformly distributed Wendland radial basis functions, the source coefficient is determined analytically by balancing the equivalent momentum input with the Brinkman resistance at the interface center. These assumptions also yield a characteristic transition-width estimate in terms of the projection steepness and support radius. Continuous adjoint analysis is performed to derive the design sensitivities. Two- and three-dimensional examples formulated using the analogy equation demonstrate the effectiveness of the proposed topology optimization method for flow-rate maximization. Body-fitted re-simulations verify the flow fields and transport performance of the optimized designs. The formulation is further extended to electroosmotic transport under the thin electric double layer (EDL) assumption using the Helmholtz-Smoluchowski relation.

Atomistic foundation models screen hypothetical crystals by thresholding predicted energies, an output that states neither how likely a candidate is to be stable nor whether more computation would change the decision. CrystalJev reads one forward pass of a frozen potential on the unrelaxed structure and returns calibrated probabilities, conformal guarantees and a rule for escalating candidates to relaxation or density-functional theory (DFT). Across 65 Matbench Discovery models, threshold calls hide cost assumptions, and ordering slower computation by its value for the decision, rather than by probability, recovers most of its benefit at a tenth of its cost. In a registered prospective test with 2,100 DFT calculations on ionic substitutions, forecasts calibrated on existing data over-stated the stable fraction of new candidates by 0.9–2.2 percentage points, because the population had shifted, not the labelling protocol; a few hundred labels from the new pool removed this bias more reliably than label-free corrections.

We theoretically investigate the microscopic mechanism of melting in finite two-dimensional ion crystals confined in anisotropic traps. Building on our previous studies of melting probability as a function of temperature and anisotropy, we extend the analysis to crystal sizes ranging from $N=4$ to $N=101$ ions and examine how structural isomerization modifies the melting pathways. Using molecular dynamics simulations together with Metropolis-Hastings equilibrium sampling, we analyze radial fluctuations, angular disorder, Lindemann parameters, and isomer-dependent energy landscapes in these Coulomb crystals. We find that crystals with identical particle number and trap anisotropy can exhibit substantially different melting behavior depending on the metastable structural isomer they occupy. Contrary to a simple soft-mode instability picture, the observed melting process is characterized by a gradual thermally-driven accumulation of radial and angular disorder. Structural isomerization reshapes the fluctuation channels through which delocalization develops, leading to nonuniform melting probabilities across temperature and anisotropy space. These results provide a unified microscopic picture of melting in finite ion crystals and clarify the role of structural rearrangements in finite-size phase transitions.

Repeated impacts of a droplet on a vertically forced bath can produce a growing Faraday-wave response under forcing conditions for which the corresponding initially undisturbed bath remains linearly stable. We investigate this mechanism using axisymmetric two-phase direct numerical simulations over a wide range of Reynolds and Weber numbers. The resulting phenomenological regime map identifies quasi-periodic, decaying, faint, and unstable-bath responses. Along the parameter path considered here, the transition to the unstable-bath regime occurs over a narrow range of Weber numbers and varies only weakly with Reynolds number. In the unstable regime, the bath develops a coherent subharmonic response at half the forcing frequency, while disturbances in the decaying regime remain broadband and weaken between successive rebounds. Bath-only simulations show that a finite-amplitude perturbation representative of droplet impact can seed the confined radial mode susceptible to parametric forcing, initiating a growing subharmonic response below the linear instability threshold of the initially flat bath. A reduced capillary-dominated model provides a scaling estimate for the impact-equivalent perturbation amplitude, and bath-only simulations initialized with these perturbations reproduce the bounded-to-growing transition observed in the coupled simulations. Floquet analysis of the finite cylindrical bath identifies the first axisymmetric Neumann mode as having the lowest subharmonic instability threshold. A time-resolved Bessel decomposition independently shows that the growing bath response is dominated by the same radial mode, while the droplet-induced subharmonic response projects predominantly onto this structure. These results identify a finite-amplitude route by which localized droplet impacts can access Faraday-wave dynamics below the linear onset threshold of an initially undisturbed bath.

The variational calculation of rovibrational spectra without model Hamiltonians remains challenging, with the size and composition of the vibrational basis constituting a major bottleneck. Preceding vibrational configuration interaction (VCI) calculations reduce this basis, but leave the question of which vibrational state functions to include. In close analogy to configuration-selective VCI theory, we propose a basis-pruning algorithm in which candidate vibrational states are represented by inexpensive approximate wavefunctions and selected according to their impact on rovibrational energies in a spectral window of interest. For formaldehyde, comparisons with widely used polyad schemes controlling the vibrational basis are provided. Calculations on thioketene benchmark the accuracy and efficiency of the pruning approach for different threshold values.

Through intermolecular collisions, a gas-surface scattering law can reshape the incident molecular population on which it acts. We examine this feedback using direct simulation Monte Carlo for hypersonic flow past a $40^\circ$ inclined flat plate at four benchmark conditions spanning $0.023\leq Kn_\infty\leq8.439$. Maxwell and Cercignani-Lampis-Lord (CLL) scattering are assessed through fixed-incidence moment references and evaluation of alternative kernels on the same recorded non-reactive incident populations. At $Kn_\infty=0.023$, Maxwell shear and heat transfer depart from diffuse-specular endpoint interpolation by up to $40\%$ of their diffuse-reference values. In the trailing patch, the population change induced by reduced tangential CLL accommodation overturns the fixed-incidence reductions in both shear and translational heat transfer. At the two highest conditions, the CLL momentum responses become nearly componentwise, producing nearly orthogonal displacements in the drag-lift plane. Nevertheless, a total-energy constraint required by common incidence across wall laws retains a defect of $3.1\%$ of the diffuse heat-transfer coefficient at $Kn_\infty=8.439$. Recovery of selected response relations therefore does not establish common incidence or a free-molecular flow. A cold-beam symmetry makes lift invariant under exchange of the normal and tangential CLL accommodation coefficients, but not drag. This provides a limiting explanation for the simulated asymmetric cases: at $Kn_\infty=8.439$, they yield nearly equal lift while one produces $66\%$ more drag. Population feedback and force projection thus determine whether the conditional scattering response is reinforced, obscured or reversed in the macroscopic observables.

We develop and analyze several families of fully discrete, high-order methods in the finite difference time domain (FDTD) framework for a nonlinear dispersive electromagnetic model for ultrashort pulse propagation in a nonlinear optical medium. The model consists of the time domain Maxwell's equations coupled to two ordinary differential equations; the nonlinear Kerr-Debye equation and the linear dispersive Lorentz equation, in one space dimension. The proposed methods combine staggered spatial discretizations of $2M$th-order, for integer $M>0$, with second-order explicit leapfrog or implicit trapezoidal time integrators. To handle the stiff relaxation in the nonlinear Kerr-Debye equation, we adopt a modified exponential integrator, introduced in \cite{PengJCP2020}, which ensures asymptotic-preserving (AP) behavior in the limit of vanishing relaxation time. We prove that the resulting schemes satisfy a discrete analogue of the continuous energy identity and preserve the positivity (PP) of the nonlinear susceptibility. For the schemes based on the leapfrog time integrator, we establish energy stability under a CFL condition, while the schemes based on the trapezoidal time integrator are unconditionally energy stable. High-order temporal accuracy in the trapezoidal time integrator based schemes is further achieved via Richardson extrapolation yielding $2M$th-order accurate methods in both space and time. Numerical experiments demonstrate the theoretical convergence rates and the ability of the proposed schemes to capture nonlinear wave phenomena such as soliton propagation, self-steepening, and odd harmonic generation. This work extends previous AP-PP and energy stable approaches in a discontinuous Galerkin framework to the FDTD setting, offering a computationally efficient, flexible and robust tool for simulating electromagnetic wave propagation in nonlinear dispersive optical media.

We show that quasi-paraxial fluids of light propagating in nonlinear Kerr media naturally experience an effective gauge field arising from the intrinsic spin-orbit interaction of light encoded in Maxwell equations. By deriving the leading nonparaxial corrections to the nonlinear Schrödinger equation governing the fluid evolution, we find that, for circularly polarized beams, these corrections generate an effective Lorentz force that modifies the fluid dynamics. Remarkably, the corresponding gauge field is not externally imposed but self-consistently generated by the fluid itself, with its sign controlled by the light helicity and its magnitude governed by the spatial variations of the nonlinear refractive index. We illustrate the physical consequences of this gauge field in two configurations: the chiral deformation of normal and superfluid flows past an obstacle, accompanied by a transverse spin Hall force, and the cumulative precession of an optical wave packet trapped in a focusing fluid.

Across biological and social complex systems, models of epidemics or contagions incorporate complexity through network correlations, adaptive behavior, higher-order interactions, or co-circulating strains. Tracking these mechanisms lead to high-dimensional mathematical systems that resist analytical treatment. We show that a broad class of models admits a systematic reduction via fast-variable elimination. The central insight is that complexity can be captured by fast variables equilibrating much faster than the epidemic, leading to “emergent complex contagion” where the force of infection depends on prevalence. The epidemic transition follows a universal equation and is continuous or discontinuous whether the force of infection decays or intensifies with prevalence. Our results reveal diverse epidemic models share a common skeleton such that mechanisms that share a characteristic form can be macroscopically indistinguishable.

We discuss surface-pinned, topologically charged, nonsingular defects (SD) in light scattering by a plasmonic object. They follow from exact Maxwell boundary conditions and are purely topological—unaffected by surface forces. At optical frequencies, in (quasi) 2D, they appear in the electric and Poynting vector fields for $H^{(z)}$ polarization, not for $E^{(z)}$. Exact solutions for a circular cylinder reveal topological charge-conserving bifurcations involving SDs with bulk singularities or SDs alone, and contraction of defect regions under loss.

We present a qualitative case study of a human-supervised team of specialized AI agents supporting an astronomy research project. The Bot Spectroscopist team, described in the project record as operating through Grok Bot powered by xAI Grok, divided work among orchestration, numerical implementation, data curation, spectroscopy critique, literature search, figure preparation, manuscript editing, and review. Human decisions determined scientific scope, model changes, and manuscript inclusion. The scientific application is CondGen, a deterministic label-to-spectrum network extending our previous work to five individual elemental abundances. The reported baseline assessment achieved a mean absolute error (MAE) of 0.003681 in continuum-normalized flux on 21,657 synthetic test spectra. Existing binned diagnostics show that reconstruction error varies with effective temperature and abundance. The bots also flagged a non-monotonic cool-star magnesium response for further investigation; a matched SYNSPEC abundance sweep is needed to assess its physical fidelity. Building on a pre-existing spectral database, notebooks, and research program, the authors estimate that the reported analysis, diagnostics, figure preparation, and initial manuscript drafting were assembled in less than a week through human prompting and exchanges among agents. No comparison with a human team starting from the same resources was performed, so this elapsed-time account does not establish a productivity or labor saving. The study illustrates task delegation, artifact exchange, critique, and correction under human supervision.

Motivated by recent experimental observations by Matsuzawa et al. (2026) of colliding several vortex rings within a water tank, this paper extends a compact trefoil vortex simulation to later times and generates a persistent ==energy spectrum that obeys Kolmogorov scaling, together with other statistics characteristic of fully developed turbulence, including structure function scaling. This temporal extension uses a larger (4pi)3 periodic domain, with the improved compactness being achieved by the use of an algebraic Rosenhead vorticity profile, from which viscosity(nu)-independent finite energy dissipation is generated and pre-reconnection convergence of nu1/4-dependent higher-order vorticity moments. These properties suggest, perhaps for the first time, how decaying Navier-Stokes simulations can generate fully-developed turbulent flow from an unforced initial state that is far from boundaries, thereby suggesting how further simulations at higher values of Re could be harnessed for experimental comparisons. Moreover, the exponents for the energy decay and the integral scale growth, E(t)~(t+t0)-10/7 and and ell(t)~(t+t0)2/7, follow those based upon preservation of the Loitsyanskii integral. On a related question, an integral scale growth rate ell that is close to the experiment rate of ellX~(t+t0)(0.16or1/7)is only obtained if the Fourier modes at the scale of the periodic domain are not considered.

The steepening of fast magnetosonic waves in the inner magnetospheres of magnetars can produce monster shocks, whose precursor emission may account for fast radio bursts (FRBs). For sufficiently bright bursts, particles crossing the shock radiate their energy within a single gyration period, raising the question of how radiation reaction affects the shock structure and its coherent emission. We investigate strongly cooled, relativistically magnetized shocks using a stationary multifluid model generalized to include the Landau-Lifshitz radiation-reaction force, together with particle-in-cell simulations of monster-shock dynamics. We show that the kinetic-scale shock transition is governed by only two dimensionless parameters: the Alfvénic Mach number and a cooling parameter $\tau$ that measures radiative losses over a gyration period. Coherent precursor emission is triggered above a critical Mach number that increases with $\tau$, at which the beam dynamics becomes chaotic. Above this threshold, radiative cooling shifts the peak frequency of the precursor to higher values, scaling as $\tau^{2/7}$. Remarkably, monster shocks remain far above the emission threshold even under strong radiative cooling. Radiation reaction therefore does not quench the precursor emission; instead, it primarily shifts the spectral peak into the kinetic regime. The luminosity of the precursor wave is determined solely by the luminosity of the driving kHz wave and the conversion efficiency, $\epsilon_X\sim 10^{-3} - 10^{-2}$.

The Van Allen Probes were launched into nearly identical orbits and experienced the same solar and geomagnetic environment, yet their post-mission lifetimes diverged dramatically. Probe A underwent rapidly accelerating orbital decay and reentered the atmosphere in March 2026, while Probe B remains in orbit. We investigate the cause of this divergence using reconstructed orbital trajectories, modeled thermospheric densities, and measures of low-altitude residence and atmospheric drag. We find that small differences in orbital evolution progressively increased Probe A residence time in the lower thermosphere, where the steep density gradient made additional low-altitude exposure increasingly important. Enhanced thermospheric density during periods of geomagnetic activity further amplified this difference, leading to greater drag and accelerating orbital decay of Probe A. Our results show how small differences in orbital evolution can be amplified through the coupled effects of thermospheric drag and space weather, producing substantially different orbital lifetimes even for twin spacecraft sharing nearly identical initial orbits.

Motivated by Kepler's long battle with the orbit of Mars, we present a family of orbits that satisfy his second law, conserving angular momentum around a central mass, and also fulfill Ptolemy's belief in an equant — a point around which the angular speed is constant. For specific values of the angular momentum, these orbits can be written in terms of Legendre polynomials and functions of the second kind. They are analytic except at perihelion where they are twice differentiable. They resemble the "ovoid" (egg-shaped) or "metopoid" (face-shaped) orbits that Kepler considered on his way to the ellipse.

Molecular chirality gives rise to left- and right-handed enantiomers whose balance underpins biochemical function. Deviations from this enantiomeric excess are promising biomarkers of disease. Despite its importance, rapid and sensitive detection of enantiomeric excess in trace amounts of small chiral molecules remains an outstanding challenge. Synthetic chiral light introduces new opportunities for chiroptical spectroscopy, with the potential to enhance light-matter interactions by several orders of magnitude. Here we propose a new class of photonic architectures for synthetic chiral light, in which photonic structures generate, guide and optimize chiral light-matter interactions. As a first realization, we show that hollow dielectric waveguides support phase-matched propagation of multicolor fields enabling coherent accumulation of the enantio-sensitive nonlinear response over centimeter-scale distances. By combining microscopic quantum-response simulations with Maxwell's equations, we predict that incident pulse energies of around 1 uJ produce hundreds of picojoules of third-harmonic emission from only picomole quantities of carvone gas at 50 mbar over just 2 cm of propagation, with enantio-sensitive contrast approaching 5%. Phase-resolved Fourier analysis isolates a background-free chiral signal exhibiting the maximum possible dichroism of 200%. Beyond efficient chiral sensing, photonic architectures for synthetic chiral light establish a scalable platform for integrated nonlinear chiral spectroscopy, molecular fingerprinting based on ultrafast electron dynamics, and topologically robust chiroptical observables.

A geometrically-exact planar beam finite-element framework is developed for the analysis of beams with hyperelastic constitutive models. A conventional three-field beam model is first formulated with full geometrical nonlinearity and a linear elastic material law. The kinematics are then enriched by an additional global field that permits deformation through the in-plane thickness. The out-of-plane direction is incorporated separately through plane-strain and plane-stress constitutive reductions, allowing the cross-sectional deformation assumptions and constitutive behaviour to be formulated independently. Numerical results for the present benchmarks show that the plane-stress condition gives essentially coincident centreline deformations for the Poisson's ratio values considered. In contrast, the plane-strain condition, which is widely employed in the literature, makes the formulation sensitive to Poisson's ratio coupling, with the beam becoming significantly stiffer at higher Poisson's ratios. Comparisons between Saint Venant-Kirchhoff and Neo-Hookean hyperelastic models further demonstrate close agreement in the global deformation and in-plane thickness response, with small constitutive differences becoming more apparent in the local out-of-plane stretch. The proposed approach offers a simple and consistent framework to integrate hyperelastic material models into planar geometrically-exact beam models.

The integrated universal linear optical processor realized via multi-plane light conversion (MPLC) features low hardware complexity and high fabrication robustness, suitable for diverse photonic processing tasks. However, the lack of validated calibration protocols limits its universality and potential. Here, we propose a machine-learning-based calibration method and verify it using an eight-mode silicon photonic processor composed of interleaved multiport directional couplers and phase-shifter arrays. We characterize coupler transfer matrices and current-phase responses of individual phase shifters. To validate the robustness, we demonstrate its universality with Haar-random unitary matrices at wavelengths of 1500, 1550, and 1580 nm, and under partial phase-shifter deactivation. With this white-boxed device, we also demonstrate high-dimensional quantum gates and quantum reservoir computing for handwritten digit classification. Our work advances integrated MPLC-based universal linear optics and paves the way for large-scale, fabrication-robust, broadband hardware for classical and quantum photonic information processing.

Analytical greenhouse models traditionally rely on the gray approximation, simplifying radiative transfer but treating optical depth as an unconstrained parameter that yields unrealistic surface temperatures. We derive an exact, closed-form solution directly from Schwarzschild's equations for a non-gray atmosphere. While the gray approach is physically inadequate because it over-weights saturated bands that carry negligible net energy transport, we show that the non-gray formulation constrains column optical depth via the surface net radiative flux, naturally accounting for the atmospheric window without ad hoc corrections. The resulting effective optical depth penalizes saturated cores due to the negative spectral covariance between opacity and transmission. This shifts the computed surface equilibrium to an observationally consistent 288 K, yielding a purely radiative Transient Climate Response of +2.18 K under doubled \ce{CO2}, fully consistent with Intergovernmental Panel on Climate Change estimates. The framework eliminates any theoretical basis for greenhouse-effect saturation. While not intended to replace three-dimensional general circulation models, this work reconciles classical radiative transfer with modern climate estimates, demonstrating that proper flux-weighting aligns analytical theory with anthropogenic warming.

We present a new experimental apparatus for matrix isolation spectroscopy capable of growing cryogenic crystal matrices doped with barium monofluoride (BaF), a candidate for measurements of the electron electric dipole moment (eEDM). \\ In this work, BaF molecules are produced in a cryogenic buffer-gas source and used to dope a neon matrix grown on a substrate, cooled by a cryocooler, reaching temperatures as low as 3.2 K. A rotatable flange allows for multiple substrate orientations, optimizing spectroscopic investigations and matrix crystal growth. \\ Fluorescence emission analysis of BaF in neon crystal show emission when exciting the $A\,^2\Pi_{1/2}$, $A\,^2\Pi_{3/2}$ and $B\,^2\Sigma^+$ states, along with the presence of fluorescence from barium atoms in the crystal. A first estimation of the column density of BaF in the crystal is given on the order of $5 \times 10^{-13} \, \text{cm}^{-2}$. \\ We also demonstrated the production of BaF using parahydrogen as the buffer gas of the cryogenic source, a first step toward BaF molecules embedded in a para-hydrogen matrix. \\ Finally, we also observed fast fluorescence decay, attributed to optical bleaching effects, whose amplitude arise at lower temperatures or higher laser intensities, introducing a systematic effect to be studied in future experiments.