Papers

We propose a deep learning framework based on an encoder-decoder architecture for the design and evaluation of cloaking devices, demonstrated in this work for two-dimensional wave propagation governed by the Helmholtz equation. The cloaks under consideration are concentric layered media surrounding the object, whose geometry and material parameters determine the scattering response. We consider circular and object-fitted layer configurations and parameterize all designs by the layer thicknesses, enabling a unified representation for direct comparison of different cloaks for the same object. Training data are generated using a boundary element formulation suitable for geometries where analytic solutions are not available, and neural networks are trained with standard hyperparameters on geometry-specific datasets. The proposed approach is applied to circular, star-shaped, and kite-shaped objects. Results show that object-fitted configurations consistently outperform simpler circular-layer designs in scattering reduction, highlighting the importance of geometry in cloaking performance. Overall, we present a flexible, data-driven approach for systematic comparison of cloaking strategies, with potential extension to more complex geometries and broadband settings.

We develop a long-wavelength theory for the linear stability of a flat interface between an active nematic and an isotropic fluid. Starting from a diffuse-interface Cahn–Hilliard–Landau–de Gennes description coupled to Brinkman-screened Stokes hydrodynamics, we project the linearized dynamics onto a small set of interfacial degrees of freedom: the conserved translation, or height, mode; a scalar profile distortion or amplitude mode; and a transverse orientational mode associated with director rotations. Eliminating the gapped scalar profile mode gives a reduced interfacial operator coupling the conserved height mode to the transverse orientational mode. The main result is that activity generates, in the screened diffuse-interface regime, a direct local contribution proportional to $q^2$ in the height sector. This term competes with the passive local diffusive capillary relaxation, which enters at order $q^4$, and defines a local active interfacial channel controlled by the internal structure of the diffuse interface. This mechanism is distinct from the non-analytic $|q|$ and $|q|q^2$ terms characteristic of weakly screened Hele–Shaw/Saffman–Taylor-type transport, which are controlled by long-ranged momentum transport in the surrounding fluid. This framework identifies a diffuse-interface route to active interfacial instability that can operate while the homogeneous active nematic remains linearly stable because of hydrodynamic screening. It also provides a basis for distinguishing local diffuse-interface instabilities, bulk-flow-driven hydrodynamic instabilities, and mixed regimes in active nematic–isotropic interfaces.

A common feature of most numerically optimized stellarator geometries is the presence of sharp ridges on outer flux surfaces, irrespective of the rotational transform. Despite their importance, an analytical theory for their existence has been lacking. In this work, we demonstrate that ridges are not artifacts but mathematical necessities. We develop such a theory for devices with quasisymmetry (QS). We demonstrate that QS exhibits close connections with the theory of geometrical optics, following Parker's “optical analogy" (E.N. Parker, Geophys. Astrophys. Fluid Dyn, 1989). By mapping vacuum QS to the eikonal equation of geometrical optics, we derive the conditions for ridge formation, identified as field line caustics where magnetic field lines focus. Furthermore, we prove a geometric theorem for stellarator coil design: both ridges and filamentary coils must lie on the zero-determinant manifold of the magnetic gradient tensor. This topological constraint unifies the description of plasma ridges and external coils, providing a precise criterion for identifying valid coil locations and explaining the efficacy of the magnetic gradient lengthscale (J. Kappel et al., Plasma Phys. Control. Fusion, 2024) as a coil optimization parameter. We demonstrate that as the device becomes more compact, sharp ridges naturally form on the inboard side in quasiaxisymmetry. We support our analytical theory with extensive numerical evidence.

We investigate the emergence of synchronization in a network of coupled chaotic macroeconomic systems. Each node represents an economy characterized by three key variables savings, gross domestic product (GDP), and foreign capital inflows. These economies interact or are connected through a fitness-based probability that depends on the potential GDP of each node. This formulation allows both structural heterogeneity, arising from uneven network connectivity, and dynamical heterogeneity, due to differences in local parameters, to be explored within a unified framework. Using both numerical simulations and a mean-field approximation, by varying the coupling strength and the degree of heterogeneity of both network topology and dynamical behavior of the nodes, we analyze synchronization transitions. Our results show that the mean-field approach accurately captures the collective dynamics in homogeneous and fully connected networks even with heterogeneity within the intrinsic dynamic of the nodes but fails when strong heterogeneity in the structure of the network is introduced. In heterogeneous networks, the system exhibits partial synchronization and on–off intermittency, where coherent phases of global synchronization alternate with abrupt desynchronization bursts. The distribution of laminar phase durations follows a power-law scaling, consistent with theoretical predictions for intermittent synchronization. From an economic perspective, these results suggest that global business cycle synchronization is inherently fragile: strong integration can promote temporary coordination among economies, but structural and dynamical disparities inevitably lead to intermittent breakdowns of collective behavior.

We revisit the Scovel-Weinstein framework (Scovel & Weinstein, CPAM 1994) for reducing the Vlasov-Poisson system while preserving its Hamiltonian structure. Standard particle-in-cell (PIC) algorithms approximate the distribution function by macro-particles with position and velocity. In contrast, Scovel-Weinstein decorated particles involve additional shape degrees of freedom, while maintaining a finite-dimensional reduction with Hamiltonian structure inherited from the continuum model. Although the original work established this structure three decades ago, its computational potential has remained largely unexplored. We present a practical implementation of the Scovel-Weinstein model and compare it with a standard PIC algorithm. Numerical experiments demonstrate that macro-particles in standard PIC can be replaced by far fewer decorated particles while retaining comparable accuracy. This decorated particle approach offers a new structure-preserving paradigm for kinetic plasma simulation.

Serpentinization of ultramafic rocks is a naturally occurring mineralogical process that can generate molecular hydrogen through the oxidation of ferrous iron during water-rock reaction. Although the resource potential is large, the natural reaction is kinetically limited, and practical hydrogen recovery requires methods that can accelerate conversion without imposing an energy penalty that exceeds the value of the hydrogen produced. This short communication reports a preliminary atmospheric-pressure microwave serpentinization experiment using a water-saturated 2 g crushed olivine sample. Microwave irradiation produced a rapid increase in measured hydrogen concentration compared with conventional hot-plate heating under otherwise similar conditions. The preliminary experiment showed approximately a 12-fold increase in hydrogen concentration and an apparent rate increase from about 2 ppb s$^{-1}$ for conventional heating to about 10 ppb s$^{-1}$ during microwave exposure. These results suggest that electromagnetic stimulation can enhance serpentinization kinetics, likely through rapid volumetric heating, selective coupling to iron-bearing phases, and localized thermal gradients. The result provides an initial experimental basis for evaluating microwave stimulation as a route to accelerated geologic hydrogen production and motivates follow-on measurements using calibrated gas analysis, absorbed-power measurements, dielectric characterization, and elevated-pressure testing.

We introduce force-kernel extended-system adaptive biasing force (FK-eABF), a force-based kernel reformulation of eABF that replaces the histogram-based mean-force accumulator of conventional eABF with a sparse population of Gaussian kernels storing local running-mean forces. Biasing forces are recovered by Nadaraya-Watson regression, yielding smooth estimates from the earliest stages of a simulation without a minimum-count threshold, while the same kernel population also defines an auxiliary, self-attenuating exploration force that requires no prior knowledge of barrier heights. On N-acetyl-N'-methylalanylamide in explicit water, FK-eABF achieves full free-energy landscape coverage faster than well-tempered metadynamics (WT-MetaD), on-the-fly probability enhanced sampling (OPES), and WTM-eABF, while all four methods converge to comparable accuracy given sufficient time. FK-eABF also retains long-time accuracy: on the DFG-in/out transition of Abl1 kinase, multi-microsecond simulations recover the established near-isoenergetic balance between states. At the opposite extreme, applied to the electrocyclic ring closure of 1,3-butadiene at the ab initio molecular dynamics level, FK-eABF recovers the free-energy landscape within 30 ps. Together, these benchmarks, spanning more than four orders of magnitude in simulation time, establish FK-eABF as more than a kernelized implementation of eABF: A force-based kernel reformulation that delivers faster early-time convergence without sacrificing long-time quantitative accuracy.

A method for measuring the altitude and particle size of noctilucent clouds, based on positioning and photometry from wide-angle three-color cameras, has been developed to determine the three velocity components, particle radius, and its derivative with respect to time for different cloud fragments. The updated method is applied to observational data of bright clouds during the summers of 2023-2025. Meridional motion of the cloud is found to be the principal factor driving the change in particle size. The effect of particle size evolution in the presence of a strong latitudinal temperature gradient is also studied.

This translational article documents the European Centre for Medium-Range Weather Forecasts (ECMWF) transition from a restricted data licensing model to open access under CC BY 4.0, completed in October 2025. The policy context included EU open data requirements and alignment with international data exchange frameworks. The transition was implemented through a tiered service model that kept core forecast data open while offering operationally supported delivery as a cost-recovered service. Between 2020 and 2025, ECMWF executed an iterative planning cycle: setting an annual target for revenue reduction, specifying additions to the open tier under that target, provisioning infrastructure, and assessing outcomes to update assumptions. Drawing on internal administrative records (2014 - 2025), we describe design choices, operational constraints, and early outcomes. In the six months following the end of the transition, more than 93% of previously paying organisations retained a Service Agreement, while open endpoint download volumes increased substantially. We discuss trade-offs in defining the open tier (resolution, parameters, schedule), the reduction of compliance overheads formerly associated with redistribution restrictions, and the scalability implications of global distribution. We note an emerging sustainability question as AI-based forecast products become freely available. The early evidence is consistent with the view that a tiered service model can be designed to reconcile open-access obligations with operational sustainability, subject to monitoring over longer contract renewal cycles (typically annual).

Shock-driven turbulence is central to astrophysical plasmas in which explosions and compressive driving inject energy through shocks rather than steady stirring. We present three-dimensional, three-temperature (ion, electron, and radiation; 3T) radiation-hydrodynamic simulations of a laboratory platform in which two offset CH mesh targets are irradiated by a $30\,\rm ns$ X-ray pulse. Mesh ablation launches counter-streaming supersonic flows whose vorticity is seeded baroclinically at mesh-cell corners, advected into collimated channels over $\sim15\,\rm ns$, and injected into the outgoing streams before collision. The flows first collide at $t\simeq75\,\rm ns$, forming a shocked turbulent mixing layer that persists for at least $300\,\rm ns$, reaches $\ell_0\simeq4.5\,\rm mm$, and evolves toward an effectively isothermal equation of state with $\gamma_{\rm eff}\simeq1.1$. After stagnation, $u_0(t)\propto t^{-1.1}$ while $t_0/t_{c_s}\simeq0.2$ remains nearly fixed. Compression and stretching dominate the vorticity budget, and the velocity field relaxes toward a kinetic-energy partition of approximately $70\%$ solenoidal and $30\%$ compressive. The Reynolds stress is strongly anisotropic at the outer scale and remains measurably anisotropic over much of the resolved inertial interval, indicating directional memory of the collision axis and mesh geometry across many scales. The solenoidal strain spectrum implies $\ell_{\nu,\rm s}\simeq92\,\mu\rm m$, $\ell_0/\ell_{\nu,\rm s}\simeq49$, and an effective Reynolds number $\mathrm{Re}\sim2\times10^2$. The density-gradient spectrum is directly tied to the compressive mode spectrum, which evolves independently from the incompressible cascade. Abridged.

Spin squeezing in atomic ensembles enables atom interferometry with sensitivities below the shot-noise limit, but the associated entanglement is highly susceptible to loss, making imperfections in atom optics a central limitation. Bragg diffraction is an established technique for driving transitions between atomic momentum states and enables large-momentum transfer through higher-order diffraction while preserving the internal state. However, it is intrinsically limited by two competing mechanisms: Short light pulses induce parasitic diffraction into off-resonant orders beyond an effective two-level description, while long pulses face velocity selectivity. We derive analytical expressions in a second-quantized framework for the atom optics and phase uncertainty of a Mach-Zehnder interferometer including these effects. We demonstrate that sub-shot-noise scaling is achieved only in a regime of intermediate pulse duration. Furthermore, we show that deleterious effects of higher-order diffraction are partially mitigated by optimizing the input quantum state.

The Pfirsch-Schlüter current is a current that flows along the magnetic field lines in a toroidal plasma equilibrium that is required to make the plasma current density divergence free in the presence of a plasma-pressure gradient. A distortion in the plasma shape is caused by the Pfirsch-Schlüter current, and it is desirable to minimize both the strength and the distance this current flows along the magnetic field lines. The Pfirsch-Schlüter current is localized within a half period of a stellarator when $d\ell/B$ integrated over the half period is the same for all lines in the magnetic surface. It is shown that within parts in a thousand this is the same condition as the distance $\ell_{s}$ required for a field line to cross the half period being the same for all lines in the surface. To make the $\ell_{s}$'s the same, the lines started on the small major radius side of the plasma must undergo wiggles to make their $\ell_{s}$ as long as those started on the outboard side. This is generally achieved using modular coils with a large helical component on the small major radius side but could be achieved with a central column carrying a helical current.

We develop a direct diagrammatic Monte Carlo method for the second Rényi entropy of inter- acting lattice fermions. Fermionic replica sewing yields a connected-determinant (CDet) expansion, which we sample with many-configuration Markov-chain Monte Carlo. On a 3 \times 3 Hubbard clus- ter, deterministic coefficients through third order agree with exact-diagonalization derivatives for three reference shifts, while sampling extends the series to tenth order. For a reference shift with a continuous stability region, conformal-Borel resummation also gives good agreement with the exact entropy. We further compute coefficients through ninth order on 40 \times 40 and 50 \times 50 periodic lat- tices, with subsystems of up to 676 sites. The resummed results from different reference shifts show good agreement at a common truncation order. Their shift and order dependence provide checks on the stability of the continuation. These calculations extend connected-diagram sampling to spatial Rényi observables on large finite fermionic systems.

Feshbach resonances, first studied in the context of nuclear reactions, have since become a cornerstone of modern atomic physics. They offer a remarkable degree of control over interatomic (and even intermolecular) interactions by tuning external magnetic fields. This tunability arises from the interplay between quantum scattering and the internal structure of atoms or nuclei. In this work, we explore the essential physics of Feshbach resonances using only basic quantum mechanics, aiming to make this powerful concept accessible to educators and students alike.

Managing the emission and absorption of thermal radiation is crucial for a wide range of technologies, from radiative cooling of buildings and vehicles to thermal regulation of satellites and future lunar and Mars habitats. Despite this universal and critical need, thermal emitters capable of adaptively modulating emissivity in a broadband, high-contrast, and fully solid-state manner remain elusive. Here, we leverage neural-network-guided photonic design to enable adaptive, solid-state thermal emitters based on chalcogenide phase-change materials capable of emissivity switching with extreme spectral contrast and bandwidth. These engineered nanophotonic emitters operate over a broad spectrum$-$from solar through thermal infrared$-$providing very low solar absorptivity while enabling switchable thermal infrared emissivity with high contrast. We experimentally demonstrate the core functionality of our approach in the space-like radiative environment in the stratosphere, observing a 31.5 {\deg}C temperature differential between the two solid-state phases of a simplified chalcogenide GeSbTe-225 thermal emitter. Our results point to even more significant capabilities, such as the potential to modulate >600 W/m$^2$ of radiative heat (at 100 {\deg}C) with minimal solar heating in the vacuum of space. The proposed nanophotonic solid-state adaptive emitter could provide high-power and high-speed heat modulation while requiring no power to maintain state, offering transformative capabilities for thermal control in dynamic radiative environments on Earth and in space.

The suitability of the actuator line method (ALM) to predict flutter instability is theoretically studied by employing a two-dimensional linear model of the ALM undergoing harmonic motion. Three different analytical models of the ALM, including or not the non-circulatory and pitch-rate terms, are compared to Theodorsen's theory. First, classical methods using Theodorsen's function are employed to calculate reference values of flutter velocity and frequency. Then, the theoretical response of the ALM is predicted by replacing Theodorsen's function in the lift and aerodynamic pitching moment models with the corresponding complex function that relates the lift calculated by an unsteady ALM and the quasi-steady lift in harmonic motion. This method is applied to an airfoil typical section and to an energy harvesting device based on aeroelastic vibrations of an airfoil. From the results, it is possible to conclude that the classical ALM does not accurately predict flutter. However, we show that an ALM that considers the pitch-rate and non-circulatory terms has the capability to reproduce the results of classical methods if the ratio between ALM smearing parameter and chord is carefully chosen. These results can guide aeroelastic simulations of energy harvesting devices, large horizontal-axis wind turbines and fixed-wing aircraft.

We show that Maxwell theory with a codimension-$1$ Chern-Simons interface supports chiral electromagnetic surface waves on the interface, even when the bulk theory on both sides is conventional vacuum electrodynamics in infinite space. Solving the exact boundary value problem we find that the Chern-Simons interaction acts with opposite sign on the two helicities oriented along the interface, giving rise to one normalizable mode localized on the interface. This mode is a gapless chiral surface photon with linear dispersion and a frequency-independent index of refraction set by the Chern-Simons coefficient. This mode exists despite the absence of ambient material response or geometric confinement.

Ciliated organs transport viscous fluids through confined ducts, yet how duct morphology and ciliary activity jointly set the limits of flow rate and sustainable pressure remains unclear. Here, we model dense arrays of beating cilia lining duct walls as an active porous medium driven by prescribed metachronal waves, and identify two key morphological parameters that govern transport: the ciliary confinement ratio and the mean ciliary fraction. The resulting flows are described by the incompressible Navier-Stokes-Brinkman equations, which we solve numerically using a spectral method in the low-Reynolds-number regime. We also develop a complementary mean-field analytical model. The active porous medium framework provides an intermediate description between classical envelope theories and filament-resolved simulations and enables a systematic investigation of how fluid transport is shaped by confinement and packing of ciliary material. We find that transport is characterized by a decreasing linear relationship between flow rate and pressure generation, marking a fundamental trade-off between throughput and sustainable adverse pressure. These results provide a unified physical interpretation of the morphological diversity of ciliated ducts, from high-throughput ciliary carpets to pressure-generating ciliary flames, and offer guiding principles for the design of bio-inspired microfluidic pumps.

We develop an optimization framework for high-efficiency quantum cycles implemented with a trapped Bose-Einstein condensate, whose control parameters are the trap stiffness and the interaction strength tuned via a Feshbach resonance. Optimal driving protocols for each stroke of the cycle are obtained from a variational description of the condensate dynamics combined with Nelson's stochastic quantization, which maps the quantum evolution onto an effective Ornstein-Uhlenbeck process. The optimal protocol is obtained by minimizing a user-defined cost functional that selects the best trade-off between protocol duration and arbitrary physical constraints (such as the expended work or the proximity to an adiabatic evolution), and exhibits remarkable stability over repeated cycles. The method also provides a systematic route to optimal control for generic nonlinear Schrödinger equations, paving the way to optimal control strategies in fields as diverse as nonlinear optics, quantum fluids, and quantum plasmas.

We introduce the Compression-Directional Entropic Stress (CoDeS) method inspired by information geometric regularization. CoDeS replaces scalar multidimensional entropic pressure with a tensor stress aligned with the principal directions of compression. The stress has the form $\boldsymbol{\Pi}_{\Sigma}=\sigma\boldsymbol{M}$, where $\sigma$ is obtained from a modified-Helmholtz equation and $\boldsymbol{M}$ is constructed from the compressive eigenspace of the symmetric velocity-gradient tensor. The source is gated by volumetric and principal-strain compression, so the regularization vanishes in smooth expansion, rigid-body rotation, and ideal contacts, while recovering the compressive one-dimensional IGR mechanism at planar shocks. The same tensor stress is used in the conservative momentum flux and the stress-work energy flux. CoDeS is tested on one-, two-, and three-dimensional problems including smooth expansion, double rarefaction, the Sod shock tube, multidimensional Riemann flow, a viscous shock tube, a two-fluid triple point, a Mach-3 slot jet, and a supersonic Taylor–Green vortex. The results show that CoDeS remains inactive in expansive and contact regions, supplies localized stress at shocks, and concentrates regularization along compressive wave structures while remaining weak in shear- and vorticity-dominated regions. At matched resolutions, the three-dimensional Taylor–Green results are comparable to or more energetic than seventh-order WENO/TENO references. These results indicate that CoDeS provides a compression-selective shock regularization compatible with high-order finite-volume resolution of contacts, interfaces, shear layers, and vortical structures. All the code, case settings, and code for plotting figures of this paper are available at https://github.com/xubonan/code\_for\_CoDeS.

We revisit a neural negative binomial model for weekly earthquake counts on a 3 x 3 degree grid over the Tian Shan and Pamir, and ask which of its conclusions survive a careful evaluation. At the completeness magnitude of 4.5, the 144-week test period holds 2448 cell-weeks; six cell-weeks, in five distinct weeks, have three or more events. Two conclusions survive. First, Poisson forecasts, temporal ETAS included, understate the probability of such a busy week: ETAS expects 0.72 where six occurred, a shortfall by a factor of 8.3 (p = 0.00009, exact test). One dispersion parameter removes it (ETAS with dispersion expects 4.45, p = 0.58); simulating aftershock chains within the week also reproduces the tail but overshoots the total count by about a quarter. Second, the network's advantage over a linear model disappears once that model has an intercept per cell: the remaining gain is 3.4% of deviance, not significant (p = 0.57 over five test years), and it comes from one cell-week out of the 4420 scored; without it the network is 0.7% worse. A blind test on 2024 to September 2026, with every model fitted on data through 2023, confirms the tail result: Poisson forecasts are rejected (p from 3 x 10^-8 to 0.001), dispersion models are not (p between 0.25 and 0.84), except the NB GLM, whose level blew up out of sample and which is rejected at p = 0.003. Out of sample, model families differ in how they extrapolate beyond the training range, not in the per-cell term. We also measure the evaluation traps met on the way: a biased reference level, a single seed (five of six effects in v1's results table change sign), too few bootstrap resamples, and a threshold below completeness, which shrinks the ETAS shortfall from 8.3 to 2.8 times. This version replaces preprint v1; Section 7 lists the corrections.

Transparent conducting oxides near their epsilon-near-zero frequency exhibit near-unity ultrafast modulations of the refractive index which have enabled the field of time-varying metamaterials, yet the underlying carrier dynamics at high driving fluences remain poorly understood. Here, we report ultrafast modulations in the reflectivity and transmissivity of indium tin oxide, and a non-monotonic oscillatory behavior. This is especially evident in the time evolution of the complex Fresnel coefficients retrieved directly from pump-probe spectrograms using an optical gating technique, GRUMPY FROG. The dynamics of the retrieved plasma frequency and damping coefficient are well captured by an extended two-temperature model incorporating a competing nonlinear interband process: at high fluences, Auger-type scattering of hot conduction electrons promotes valence band carriers, increasing the plasma frequency while accelerating hot-electron cooling and raising the damping coefficient. These results clarify the origin of anomalous high-fluence dynamics in indium tin oxide and identify a fluence-tuneable modulation dynamic with direct implications for ultrafast refractive index engineering in time-varying photonic devices and optical switching.

Extreme ultraviolet (EUV) lithography is the cornerstone of the fabrication of advanced integrated circuits at the 7-nm node and beyond, but its reliance on multi-element reflective projection optics makes it inaccessible for small-scale research and prototyping. EUV interference lithography (EUV-IL) provides a lensless alternative but is intrinsically restricted to periodic structures. Here we demonstrate EUV holographic lithography (EUV-HL) as a lensless route to arbitrary, non-periodic, curvilinear patterning at the EUV wavelength of 13.5 nm. We introduce an inverse-design framework for computer-generated holograms that captures the dominant physical effects of EUV mask diffraction within a shift-invariant convolution model that is tractable for full mask layouts. Using this framework, we design and fabricate transmissive holographic masks by direct-write electron-beam lithography in hydrogen silsesquioxane, expose them with synchrotron-generated EUV radiation, and print target layouts with critical dimensions down to 40 nm, nearly an order of magnitude finer than the previous state of the art in EUV-HL. The demonstrated combination of sub-50 nm resolution, curvilinear design freedom, and a lensless optical setup establishes EUV-HL as a uniquely flexible tool for nanostructure prototyping at EUV wavelengths, and provides a natural pathway to non-periodic pattern prototyping at beyond-EUV (BEUV) wavelengths, which is currently inaccessible to interference-based methods.

Compared with traditional fuels, emulsified fuels can improve fuel atomization and combustion, and nanoparticles as additives have the potential to enhance combustion and reduce emissions. Previous studies on micro-explosion mainly considered emulsion droplets, but the role of nanoparticles in emulsion droplets is still unclear. In this study, we experimentally investigate the micro-explosion of emulsion droplets with nanoparticles via high-speed photography, digital image processing, optical microscopy, and scanning electron microscopy. The results show that the presence of nanoparticles can greatly improve the strength and probability of micro-explosion, particularly for carbon nanoparticles. This is mainly because nanoparticles can agglomerate during the evaporation of emulsion droplets, facilitate the absorption of radiation energy, inhibit the diffusion of superheated vapor, and ultimately promote micro-explosion. The effects of nanoparticle mass fraction and water content are also investigated, and the results show that the increase of nanoparticles and water can facilitate micro-explosion.

This study investigates radar technology for non-invasive brain imaging and tumour detection, offering an alternative to MRI and CT scans. Using Ansys HFSS to simulate electromagnetic interactions in brain tissues, we evaluate the penetration, signal strength, and safety of Patch and Vivaldi antennas. Results show Patch antennas are optimal for tumour localization, while Vivaldi antennas suit broader scanning applications. Although promising for safer, more accessible imaging, especially in resource-limited environments, further research with diverse models and actual patient data is essential to advance this technology in non-invasive medical diagnostics.

Solving partial differential equations with neural operators significantly reduces computational costs but remains bottlenecked by high training data requirements. Active learning offers a natural framework to mitigate this by selectively acquiring the most informative samples in an iterative manner. We introduce physics-based acquisition - a novel physics-informed active learning algorithm that leverages the partial differential equation residual to guide data selection. We validate the method by presenting numerical experiments for the 1D Burgers equation and the 2D compressible Navier-Stokes equations. We show that, in our experiments, physics-based acquisition consistently outperforms random acquisition and matches the state of the art in data efficiency. At the same time, it has the unique advantage of injecting a physics inductive bias into the training process, ensuring that simulation cost is spent where the model's physical understanding is weakest.

Light scattering by two-dimensional (2D) van der Waals heterostructures (vdWHs) is immense, especially given their infinitesimal volume, thus enabling strong light-matter interactions. Surface 2D polariton waves manifest through large concentration of electromagnetic field in vertical direction, normal to their propagation. By confining vdWH materials into 2D photonic shapes, one can manipulate and compress light in lateral directions. Scattering-type scanning near-field optical microscopy is a perfect tool for direct imaging of the propagating polaritons and studying the properties of confined polaritons in nanostructures. Though, thus far the quantitative analysis, such the wavelength extraction, has been challenged for confined polaritons by incapability of mapping of the wave period on sub-wavelength scale and difficulty of identifying an adequate substrate's "background" to subtract. Here, an analytical approach is developed to reveal the local propagation constant of confined polaritons under abovementioned constraints and map it with the sub-wavelength resolution. Applied to analysis of the SiC/2D-Ag/EG (epitaxial graphene) photonic nanostructures, the technique uncovered that the polaritons are highly confined in both vertical ($\sim\lambda$/50) and lateral directions ($\sim\lambda$/40) by 2D metal.

The dynamics of a Lamb-Oseen vortex dipole in a viscoelastic fluid are investigated, with emphasis on asymmetry, coupling strength, and transverse shear waves relevant to strongly coupled dusty plasmas. Dusty plasmas provide a natural realization of strongly coupled VE behavior, where transverse shear modes dominate in the incompressible limit. Numerical simulations are carried out using the incompressible generalized hydrodynamic model for both symmetric and asymmetric dipoles, with variations in vortex core size, circulation strength, and separation distance. In the symmetric case, dipoles exhibit sustained translational motion, with propagation speed decreasing as the initial separation distance increases, consistent with inviscid predictions. In contrast, asymmetric configurations-arising from unequal core radii or circulation strengths-lead to rotational motion due to imbalance in induced velocities, with the weaker vortex orbiting the stronger one. Viscoelasticity introduces transverse shear waves whose strength and propagation speed increase with coupling. In weakly coupled regimes, their influence is minor, while in moderately coupled regimes they modify propagation and induce deformation. In strongly coupled regimes, transverse shear waves significantly enhance vortex-vortex interaction, accelerating strain-induced deformation and leading to rapid dissipation of the weaker vortex. The evolution also satisfies the conservation theorem, where the contributions from convective, radiative, and dissipative processes dynamically compensate each other, maintaining global balance throughout the dynamics. These results provide insight into wave-vortex coupling in complex fluids, with implications for transport processes and structure formation in strongly coupled plasmas and other viscoelastic media.

This paper presents our research software engineering (RSE) experiences over two years with libNEGF, a quantum transport code. We describe practical approaches to code quality assurance–including continuous integration, automated testing, and compiler warning correction–and performance engineering through continuous benchmarking. Our systematic application of these practices revealed critical defects: uninitialized memory reads, out-of-bounds writes, and notably, a misunderstood mathematical model in our boundary condition handling. We also document how continuous benchmarking exposed performance regressions caused by HPC system configuration changes. Our findings provide data points suggesting that a dangerous class of defects–equivalent to undefined behavior in C/C++ and processor-dependent behavior in Fortran–is as prevalent in Fortran scientific codes as elsewhere. While libNEGF is implemented in Fortran, most recommendations are applicable to scientific software regardless of implementation language, and they can be implemented selectively or in their entirety for both new and existing projects.

Olfactory search in turbulent environments is a sensorimotor problem that many animals solve with remarkable efficiency, yet replicating this ability in artificial systems is an enduring challenge because detections are intermittent and wind direction fluctuates strongly, rendering standard search strategies unreliable. We introduce a wind-relative reinforcement-learning framework in which an agent navigates a turbulent plume with a single internal variable — the elapsed time since the last odor detection — and selects actions relative to a locally estimated wind direction filtered through an exponential memory kernel. Policies are trained and evaluated in direct numerical simulations of turbulence, capturing the multi-scale characteristics of velocity and odor fields in natural environments, both in the presence and absence of a mean wind. In a mild mean wind, the learned policy outperforms well-known biomimetic policies such as cast-and-surge regardless of the wind memory time, yet adapts its movement pattern to wind-estimation quality. In isotropic turbulence, performance peaks at an intermediate wind memory time, identifying temporal wind integration as a regime-dependent resource. Our results highlight the importance of developing and validating olfactory-navigation strategies under realistic turbulent conditions, and offer a compact design principle for minimal robotic olfactory navigation and testable predictions for biological search behavior.