Papers

The linear stability of nanofluid boundary-layer flow over a flat plate is investigated using a two-phase model that incorporates Brownian motion and thermophoresis, building upon the earlier work of Buongiorno (2006). Solutions to the steady boundary-layer equations reveal a thin nanoparticle concentration layer near the plate surface, with a characteristic thickness of $O({\Rey}^{-1/2}{Sc}^{-1/3})$, for a Reynolds number $\Rey$ and Schmidt number $Sc$. When Brownian motion and thermophoresis are neglected, this nanoparticle concentration layer disappears, resulting in a uniform concentration across the boundary layer. Neutral stability curves and critical conditions for the onset of the Tollmien–Schlichting wave are computed for a range of nanoparticle materials and volume concentrations. Results indicate that while the effects of Brownian motion and thermophoresis are negligible, the impact of nanoparticle density is significant. Denser nanoparticles, such as silver (Ag) and copper (Cu), destabilise the Tollmien–Schlichting wave, whereas lighter nanoparticles, like aluminium (Al) and silicon (Si), establish a small stabilising effect. Additionally, stability characteristics are influenced by the viscosity model. Finally, a high-Reynolds number asymptotic analysis is undertaken for the lower branch of the neutral stability curve.

Spontaneous magnetic field generation plays important role in laser-plasma interactions. Strong quasi-static magnetic fields affect the thermal conductivity and the plasma dynamics, particularly in the case of ultra intense laser where the magnetic part of Lorentz force becomes as significant as the electric part. Kinetic simulations of giga-gauss magnetic field amplification via a laser irradiated microtube structure reveal the dynamics of charged particle implosions and the mechanism of magnetic field growth. A giga-gauss magnetic field is generated and amplified with the opposite polarity to the seed magnetic field. The spot size of the field is comparable to the laser wavelength, and the lifetime is hundreds of femtoseconds. An analytical model is presented to explain the underlying physics. This study should aid in designing future experiments.

The Fe-O system is fundamental to understanding the composition and properties of the Earth's core. Recent studies have suggested the possible existence of stable, iron-rich FenO compounds at around 215 GPa. Here, we performed crystal-structure searches and fully anharmonic free-energy calculations to investigate the Fe-FeO system under inner-core conditions. We identified Fe2O as a stable phase and constructed its high P-T phase diagram. Fe2O undergoes a hexagonal-to-tetragonal transition with increasing pressure and temperature. It remains thermodynamically stable against decomposition into Fe and FeO from 200 to 400 GPa and at high temperatures. Although oxygen has been considered nearly absent in the inner core due to its limited solubility, these results suggest that oxygen can, in fact, be incorporated into the solid inner core in the form of an Fe+Fe2O mixture, and can match PREM densities for 53 mol% Fe2O. Our work has the potential to lead to a significant revision of the current understanding of the core's structure and composition.

Electrostatic interactions fundamentally govern the structure and transport of electrolytes. In concentrated electrolytes, however, electrostatic and steric correlations, together with ion-solvent coupling, give rise to complex behavior, such as underscreening, that remains challenging to explain despite extensive theoretical effort. Using molecular dynamics simulations of primitive electrolytes with and without space-filling solvent particles, we elucidate the structural and dynamical crossovers and their connection that emerge with increasing salt concentration. Explicit-solvent electrolytes exhibit a screening transition from a charge-dominated dilute regime to a density-dominated concentrated regime, accompanied by dynamical crossovers in ion self-diffusion and ion-pair lifetimes. These dynamical crossovers display a marked discontinuity, unlike the smoother variation of the screening crossover, which originates from short-range ion-counterion structures. The pronounced growth of ionic clusters leads to a percolation transition only at higher concentrations, whereas the onset of the structural and dynamical crossovers is associated primarily with local ion pairing or small aggregates. Both structural and dynamical behaviors are found to depend sensitively on ion-solvent coupling: implicit-solvent electrolytes exhibit a screening transition between two charge-dominated regimes, accompanied by qualitatively distinct dynamical behavior. Finally, we demonstrate that the diffusion-corrected ion-pair lifetime provides a consistent descriptor linking ionic structure and dynamics across electrolyte systems.

Microbubble implosion (MBI) is a recently proposed novel mechanism with many interesting and exciting potential applications. MBI predicts that the inner layers of a spherical target with a hollow cavity can be compressed into a core with a density 105 times that of the solid density. Furthermore, this ultra-compressed core mostly consists of ions. This leads to the generation of ultra-high electric fields, which may be applicable to gamma-ray lensing or pair creation. However, MBI has yet to be studied for finite hollow spheres whose electrons are free to redistribute themselves after being given an initial temperature. This paper studies MBI under finite sphere conditions. Using an electron distribution model, the electron distribution after receiving an initial temperature is studied. Then, the optimal parameters required to fill a hollow cavity with electrons are calculated. The dynamics of MBI is simulated using a hybrid one-dimensional code. The simulation demonstrates that MBI occurs even for finite spheres, and high-density compression is still achievable with this setup. It also shows the optimal target structure, which maximizes ion flashing.

The use of differential phase contrast (DPC) in scanning transmission electron microscopy (STEM) has shown much promise for directly investigating the functional properties of a material system, leveraging the natural coupling between the electron probe and atomic-scale electric fields to map the electrostatic configuration within a sample. However, the high sensitivity of these measurements makes them particularly vulnerable to variations in both sample properties and the configuration of the instrument, stressing the need for robust methodologies to ensure more accurate analyses. In this work, the influence of key instrumental parameters - probe convergence angle, defocus and two-fold astigmatism - on atomic-resolution segmented-detector DPC-STEM measurements is evaluated through extensive image simulations. Results show that the limit of interpretability for a 21 mrad defocused probe is found at a magnitude of 4 nm, where electrostatic field magnitude can be underestimated by about 16 % in overfocus and just above 10 % in underfocus. Equivalent results for a 30 mrad probe demonstrate underestimated values around 30 % at overfocus and 20 % for underfocus, at a lower interpretability limit of 3 nm. Two-fold astigmatism introduces orientation dependent variations that surpass 40 % for magnitudes below 3 nm, but a reduction in sensitivity to the aberration is observed when oriented along detector-segment edges. Overall, the analysis confirms the sensitivity and usefulness of the scattergram-based method and underscores the importance of optimized instrumental alignment for accurate CoM based STEM imaging.

An electronic modulation can retain a substantial local amplitude while its translational coherence is limited by spatial disorder. Its coupling to superconductivity therefore cannot be characterized by a single modulation intensity. We develop a phenomenological formulation of a finite-wave-vector complex electronic envelope coupled to a charged superconducting field. Translation and gauge symmetries constrain the interaction terms, while amplitude, modulation-gradient and condensate-gradient couplings act on distinct responses. The resulting variational equations give uniform coexistence conditions, local stability criteria and phase-gradient coefficients. We define the helicity modulus by a boundary twist, distinguish phase-only from amplitude-weighted correlations, and give an explicit minimal spectral Hamiltonian illustrating how the electronic texture may enter momentum-resolved measurements. The proposed tests use distinct spatial, spectral and stiffness observables; none assumes that a tunnelling gap directly measures condensate amplitude. An explicit kernel expansion yields the leading displacement of the selected wave vector, while the thermodynamic twist response determines phase rigidity independently of charge intensity. The analytical relations and selected numerical responses distinguish amplitude, spatial organization and condensate rigidity within the specified coupled-field model.

Single-crystal X-ray diffraction (SC-XRD) is the gold standard technique to characterize crystal structures in solid state. Despite significant advances in automation for structure solution, the refinement stage still depends heavily on expert intervention and subjective judgment, limiting accessibility and scalability. Herein, we introduce RefrActor, an end-to-end deep learning framework that enables crystal structure determination directly from HKL data. By coupling a physics-informed reciprocal-space encoder (ReciEncoder) with a symmetry-aware diffusion-based generator (StruDiffuser), RefrActor produces fully refined atomic models without requiring initial structural guesses or manual input. Comprehensive evaluations on the GenRef-10k benchmark demonstrates that RefrActor achieves low R1-factors across diverse systems, including low-symmetry, light-atom, and heavy-atom crystals. Case studies further confirm that RefrActor can correctly resolve hydrogen positions, elemental assignments, and moderate disorder. This work establishes a new data-driven paradigm for autonomous crystallographic analysis, offering a foundation for fully automated, high-throughput crystal structure determination.

Stemming from antiferromagnetic coupling, exchange bias allows inverted hysteresis in a magnetic system. Such room temperature magnetic reversal has yet to be observed in an amorphous antiferromagnet. Furthermore, the impact of this exchange bias effect on its magnetoelectric transport behavior remains a mystery. Here we discovered a zero-field magnetization switching effect in an exchange-biased amorphous antiferromagnet with inverted magnetic hysteresis. This zero-field magnetic reversal was further evidenced by its inverted large anomalous Hall effect. Notably, this collective spin flipping at zero field can occur at room temperature or above room temperature, which may be associated with quantum interference effect due to thermal fluctuation enhanced disorder. Our experimental results offer a way to design room-temperature exchange-biased amorphous antiferromagnets with zero-field multi magnetic-states and large anomalous Hall effect, holding potential for low-power and high-density memory applications.

In this work, we systematically investigate the optical feedback dynamics of terahertz (THz) frequency combs generated from quantum cascade lasers (QCLs) using the effective semiconductor Maxwell-Bloch equations (ESMBEs). Starting from a free-running comb state at low bias (1.3Ith), we identify clear bifurcation routes as the external feedback is increased. In the weak feedback regime (C<1), the frequency comb operation remains stable; as feedback increases to the moderate feedback regime (1<C<2.4), the system transitions through frequency splitting into period-one (P1) oscillations around each comb, followed by higher-order bifurcations (P2, P4, P8). Within the range 2.4<C<13.86, only combs with P1 states are observed, with the split frequency increasing continuously with feedback strength. In the strong feedback regime (C>13.86), complex feedback dynamics re-emerged but with significantly reduced complexity compared with the weak feedback regime. More interestingly, we show that optical feedback can induce chaotic THz emission at higher bias current conditions (>1.6Ith), when the free-running laser output (C=0) is originally a stable frequency comb. The resulting chaotic dynamics, characterized by broadband spectra and large positive Lyapunov exponents, are shown to depend strongly on the linewidth enhancement factor. Although THz QCLs widely considered as ultrastable under external perturbations, this work provides the first detailed report of chaotic dynamics and routes to chaos in THz QCLs under optical feedback. These findings not only deepen the understanding of nonlinear dynamics in THz QCLs but also open new possibilities for exploiting applications of chaotic light in THz sensing, imaging and secure communications.

We introduce Sketch Tomography, an efficient procedure for quantum state tomography based on the classical shadow protocol used for quantum observable estimations. The procedure applies to the case where the ground truth quantum state is a matrix product state (MPS). The density matrix of the ground truth state admits a tensor train ansatz as a result of the MPS assumption, and we estimate the tensor components of the ansatz through a series of observable estimations, thus outputting an approximation of the density matrix. The procedure is provably convergent with a sample complexity that scales quadratically in the system size. We conduct extensive numerical experiments to show that the procedure outputs an accurate approximation to the quantum state. For observable estimation tasks involving moderately large subsystems, we show that our procedure gives rise to a more accurate estimation than the classical shadow protocol. We also show that sketch tomography is more accurate in observable estimation than quantum states trained from the maximum likelihood estimation formulation.

This contribution presents an integration method based on the Simpson quadrature. The integrator is designed for finite-dimensional nonlinear mechanical systems that derive from variational principles. The action is discretized using quadratic finite elements interpolation of the state and Simpson's quadrature, leading to discrete motion equations. The scheme is implicit, symplectic, and fourth-order accurate. The proposed integrator is compared with the implicit midpoint variational integrator on two examples of systems with inseparable Hamiltonians. First, the example of the nonlinear double pendulum illustrates how the method can be applied to multibody systems. The analytical solution of the Lagrange top is then used as a reference to analyze accuracy, convergence, and precision of the numerical method. A reduced Lagrange top system is also proposed and solved with a classical fourth-order method. Its solution is compared with the Simpson solution of the complete system, and the convergence order of the difference between both is consistent with the order of the classical method.

The bulk circulation associated with convective clouds includes not only a region of updraft and cloudy air but also a region of compensating descent and cloud-free air and horizontal motions coupling these regions. The Kinematic Representation of Non-rotating Updraft Tori (KRoNUT) model is a simple representation of this entire flow. First, the skill of the KRoNUT in representing flows from a high resolution full-physics simulation of marine tropical convection is compared to various plume representations of convection. Then the KRoNUT is used to construct bulk descriptions of the dry dynamics of isolated and interacting convective circulations under the influence of advection and diffusion (only). Cross sections of advective and diffusive tendencies show that while vertical advection of the vertical wind is the most important advective tendency in clouds, the horizontal component of the convective circulation and advection thereof plays a crucial role in the evolution of circulations in the absence of buoyancy. Strong curvature of the flow near the surface and near the updraft core results in locally strong diffusive tendencies that depend on scale. Cross sections of tendencies from the KRoNUT compare favourably to results from the simulation. Interacting circulations are shown to exhibit a wide range of dynamics with some cases of interactions leading to unique stability of geometric properties of otherwise evolving flows and some leading to geometric clustering of circulation centers.

Many coronal mass ejections (CMEs) initially propagate non-radially, and then transition to radial propagation in the corona. This directional transition is a significant process that determines a CME's space weather effects but remains poorly understood. Based on multi-wavelength observations, we investigate the transition from non-radial to radial propagation in the low corona for two large-scale CMEs from the same active region on the solar limb. In the beginning, both CMEs move in a non-radial direction, beneath a system of overlying loops that are roughly parallel to the flux-rope axis. The CMEs laterally deform by bulging their upper flanks in the non-radial stage toward the higher corona, which results in the transition to a radial propagation direction approximately 25$^\circ$ away from the eruption site. After the directional transition, the non-radial-stage upper flank becomes the leading edge in the radial stage. Although the overlying loops do not strap over the flux rope, their strong magnetic tension force constrains the radial expansion of part of the CME during the transition by acting on the flux-rope legs. A major portion of the filament is displaced to the southern part of a CME in the radial stage, which implies the complexity of observational CME features. This study presents the first investigation of the lateral deformation during the transition of CMEs from non-radial to radial in the low corona, and makes an essential contribution to the complete CME evolution picture.

Developing an understandable theory for the dynamic evolution of the morphology of clouds remains intractable. To break this deadlock, we introduce a new conceptual model for cloud-scale motions named the Kinematics Representation of Non-rotating Updraft Tori (KRoNUT) model, where non-rotating reflects the absence of motion in the azimuthal direction. Using this model, we conduct a series of relaxation experiments whereby we “turn off” the baroclinic term associated with a pre-existing cloud-scale circulation. We then implement a moment reduction technique to generate a system of differential equations named the Dynamics of Non-rotating Updraft Tori (DoNUT) equations, which describe the temporal evolution of a cloudy circulation under various combinations of forcings, namely turbulent diffusion, self-advection, and cross-advection from a neighboring cloud-scale flow. The solutions of the DoNUT equations show that all single KRoNUT configurations either start at or evolve toward a specific steady state circulation. The cloud-scale motions represented by the current KRoNUT model always grow vertically but may narrow, due to advection, or widen, due to diffusion. Meanwhile, invigoration or enervation of the vertical velocity may result from advection or diffusion processes, with short, wide KRoNUTs more likely to invigorate and tall, narrow KRoNUTs likely to enervate. Our study of the coupled KRoNUTs provides insight into clouds' tendencies to attract or repel one another. Important results of the coupled KRoNUT analysis include a scaled metric for interaction, ranges of specific height ratios that induce the most meaningful interaction, and circulation parameters that alter the location and stability of a steady KRoNUT.

Measures of access, defined as the ease with which people can reach opportunities or services, are often based on proximity. Proximity measures of access are often unrealistic or idealized, ignoring many of the real barriers to access including social and economic barriers. There is a need to develop GIS measures of access that incorporate all aspects of access, which we term realized access. Our goal is to develop a conceptual framework of realized accessibility in active transportation, and compare idealized and realized measures of access to bicycling. We apply the framework to measure realized accessibility in a case study focusing on bicycling access in Santa Barbara County, and compare idealized and realized measures of access for four cities in Santa Barbara County in California (Santa Maria, Lompoc, Santa Barbara, and Goleta). Differences in measures from idealized access to realized access are greatly increased in cities with lower median household income and a higher proportion of people identifying as Hispanic. Studies aiming to understand equity and access can benefit from more nuanced and realized access measures, as idealized access measures may overestimate accessibility in underserved communities. In GIScience, especially as new data on mobility become more widely available, nuanced measures of accessibility should be the standards in analysis.

While large language models (LLMs) have introduced novel paradigms in science and education, their adoption in higher education is constrained by inherent limitations. These include a tendency to produce inaccuracies and high computational requirements, which compromise the strict demands for accurate and reliable knowledge essential in higher education. Small language models (MiniLMs), by contrast, offer distinct advantages in professional education due to their lightweight nature and precise retrieval capabilities. This research takes "Atmospheric Physics" as an example. We established a specialized corpus and image repository by gathering over 550,000 full-text PDFs from over 130 international well-respected journals in Earth and environmental science. From this collection, we extracted over 100 million high-quality sentence-level corpus and more than 3 million high-resolution academic images. Using MiniLMs, these resources were organized into a high-dimensional vector library for precise retrieval and efficient utilization of extensive educational content. Consequently, we systematically redesigned the courses, textbooks, and teaching strategies for "Atmospheric Physics" based on MiniLMs. The course is designed as a "interdisciplinary-frontier" system, breaking down traditional boundaries between atmospheric science, space science, hydrology, and remote sensing. Teaching materials are transformed from static, lagging text formats into a dynamic digital resource library powered by MiniLM. For teaching methods, we have designed a question-based learning pathway. This paradigm promotes a shift from passive knowledge transfer to active cognitive development. Consequently, this MiniLM-driven "Atmospheric Physics" course demonstrates a specific avenue for "AI for education".

The three-dimensional (3D) Ising model is mapped into a 3D spinless fermionic model by the Jordan-Wigner transformation. The exact solution of the 3D model for spinless fermions is derived analytically by performing a diagonalization process consisting of the Clifford algebraic approach, the Fourier transformation and the Bogoliubov transformation. The Clifford algebraic approach is the same as that developed for the 3D Ising model, using a time average within the Jordan-von Neumann-Wigner framework, a linearization procedure and a local gauge transformation. The formulas for eigenvalues, partition function, subsequent thermodynamic properties and critical behaviors are presented. The dimensionality and the topological phases are investigated. The present results for many spinless fermions in a 3D lattice are applicable for studying the mechanisms of magnetism, superfluid, superconductors and topological materials.

A widely circulated infrared video from 2024 appears to show an air-to-surface missile engaging a small luminous "orb"-like object, producing debris and an apparent deflection of the missile's trajectory. This paper presents a comprehensive physics-based analysis of the event. Using classical mechanics, fluid dynamics, and imaging-system geometry, we examine momentum transfer, debris behavior, gimbal-induced optical distortions, and the physical plausibility of various interpretations. A balloon-like object remains the most conservative explanation compatible with known physics. However, modern physics is incomplete: the extreme weakness of gravity relative to the gauge forces, the existence of dark matter, dark energy, neutrino masses, and the possibility of extra spatial dimensions indicate that the Standard Model is not the final description of nature. For this reason, anomalous observations should not be dismissed outright as "impossible". Nevertheless, extraordinary claims require extraordinary evidence, and the present video lacks the multi-sensor, verified, and calibrated data required to support exotic interpretations. The aim is a balanced scientific evaluation based on current knowledge while maintaining appropriate theoretical humility.

This paper examines four case studies of life-detection claims in astrobiology, covering both biosignatures and technosignatures: the 1877 "canals" on Mars, the 1976 Mars Viking landers experiments, the 2020 phosphine detection on Venus, and the 2020 Breakthrough Listen Candidate 1 (BLC1) signal. We analyse the process of discovery for each case, including how they were detected, the media reception, the ensuing scientific debate, the correction processes, and the time it took until an expert consensus was reached. We identify lessons learned while providing scientists, the scientific community, and science communicators with recommendations for approaching future claims of astrobiological discoveries. To avoid potential cognitive biases and mitigate premature conclusions, we stress the need for clear communication of uncertainties, as well as thorough debate and verification processes among the scientific community. These responsible approaches can strengthen the credibility of scientists, cultivate a supportive scientific community, and help astrobiology flourish as a field.

This work improves upon our previously introduced explicit dynamic modal filter (DEMF) within the framework of the discontinuous Galerkin spectral element method (DGSEM) by introducing a mechanism for self-tuning of the model parameters. The new self-tuning dynamic explicit modal filter (STDEMF) also extends the methodology for obtaining modal values from nodal values beyond Chebyshev grids and polynomials to general collocation points and orthogonal polynomial bases by leveraging orthogonality. The generated modes are used to remove the built-up energy due to unresolved sub-grid scales (SGS) in large-eddy simulation (LES) of turbulent flows. The STDEMF improves the performance of DEMF in two ways. First, the filter kernel applied to the modes is adapted from a cut-off kernel to a hyperbolic tangent shape, which automatically adjusts the model for different polynomial orders. Second, the cut-off mode is computed dynamically for each element as a function of local flow characteristics, including the local Kolmogorov length scale and the second invariants of the strain and rotation rate tensors. The suggested formulation for the cut-off mode treats unresolved elements distinctly and improves performance by avoiding under- or over-dissipation. Moreover, the cut-off mode evolves over time within the same element as turbulent characteristics vary. The model is evaluated on three flows, homogeneous isotropic decaying, the Taylor-Green vortex, and periodic channel flow, each with distinct turbulent characteristics. Comparisons of the results show that the STDEMF model outperforms the DEMF model and the Smagorinsky eddy viscosity model.

Physics-Informed Neural Networks (PINNs) have emerged as a powerful, mesh-free paradigm for solving partial differential equations (PDEs). However, they notoriously struggle with stiff, multi-scale, and nonlinear systems due to the inherent spectral bias of standard multilayer perceptron (MLP) architectures, which prevents them from adequately representing high-frequency components. In this work, we introduce the Adaptive Spectral Physics-Enabled Network (ASPEN), a novel architecture designed to overcome this critical limitation. ASPEN integrates an adaptive spectral layer with learnable Fourier features directly into the network's input stage. This mechanism allows the model to dynamically tune its own spectral basis during training, enabling it to efficiently learn and represent the precise frequency content required by the solution. We demonstrate the efficacy of ASPEN by applying it to the complex Ginzburg-Landau equation (CGLE), a canonical and challenging benchmark for nonlinear, stiff spatio-temporal dynamics. Our results show that a standard PINN architecture catastrophically fails on this problem, diverging into non-physical oscillations. In contrast, ASPEN successfully solves the CGLE with exceptional accuracy. The predicted solution is visually indistinguishable from the high-resolution ground truth, achieving a low median physics residual of 5.10 x 10^-3. Furthermore, we validate that ASPEN's solution is not only pointwise accurate but also physically consistent, correctly capturing emergent physical properties, including the rapid free energy relaxation and the long-term stability of the domain wall front. This work demonstrates that by incorporating an adaptive spectral basis, our framework provides a robust and physically-consistent solver for complex dynamical systems where standard PINNs fail, opening new options for machine learning in challenging physical domains.

In this work, we combine the density functional tight-binding (DFTB) approach with a light-matter Hamiltonian beyond the long-wavelength approximation to propagate the dynamics of vibrational polaritons formed by coupling molecular vibrations to confined radiation inside a Fabry-Pérot optical cavity. Here, we develop a parallelized propagation scheme with lightweight inter-CPU communication by exploiting the sparse nature of the light-matter interactions in the real space representation. We find that the computationally expensive Born charges required for our propagation can be replaced with the computationally inexpensive Mulliken charges to obtain qualitatively accurate linear spectra especially when the nonlinearity (arising from molecular vibrations) of the light-matter interaction term is not substantial. However, the same approach may not be suitable to be used for studying cavity modification of energy transport or chemical dynamics as this approximation leads to spurious heating of the light-matter hybrid system. We demonstrate the utility of this on-the-fly approach to compute angle resolved polaritonic spectra of water. We implement our approach as an open-source computational package, CavOTF, which is available on GitHub.

This paper investigates the determination of the Qibla direction using both astronomical and geometrical approaches. The study reviews historical and classical methods employed by Muslim scholars and astronomers including the use of instruments such as the astrolabe and compass. It further explores spherical trigonometry techniques to precisely calculate the Qibla azimuth from any given location on Earth. The research clarifies geometric constructions and presents a computational model implemented in C++ to facilitate accurate Qibla determination. This interdisciplinary analysis underscores the rich tradition of Islamic astronomy and geometry in solving practical religious requirements, providing both theoretical frameworks and practical algorithms for modern application.

Earth's magnetosphere hosts a wide range of collisionless particle populations that interact through various wave-particle processes. Among these, cold electrons, with energies below 100eV, often dominate the plasma density but remain poorly characterized due to measurement challenges such as spacecraft charging and photoelectron contamination. Understanding the contribution of these cold populations to wave-particle interaction is of significant interest. Recent kinetic simulations identified a secondary drift-driven instability in which parallel-propagating whistler-mode chorus waves excite oblique electrostatic whistler waves near the resonance cone and Bernstein-mode turbulence. These secondary modes enable a new channel of energy transfer from the parallel-propagating whistler wave to the cold electrons. In this work, we develop a moment-based quasilinear theory of the secondary instabilities to quantify such energy exchange. Our results show that these secondary instabilities persist for a wide range of parameters and, in many cases, lead to nearly complete damping of the primary wave. Such secondary instability might limit the amplitude of parallel-propagating whistler waves in Earth's magnetosphere and might explain why high-amplitude oblique whistler or electron Bernstein waves are rarely observed simultaneously with high-amplitude field-aligned whistler waves in the inner magnetosphere.

The Surface Water and Ocean Topography (SWOT) mission provides two-dimensional sea surface height anomaly (SSHA) maps at unprecedented resolution, but its signal is a combination of balanced meso- and submesoscale turbulence, unbalanced motions such as internal waves, and small-scale noise. Interpreting the meso- and submesoscale flow features captured by SWOT requires careful isolation of the balanced signal. We present a statistical method to do so in regions where internal tides make a negligible contribution to the SSHA signal, such as western boundary current regions and the Southern Ocean. Our method assumes Gaussian statistics as a Bayesian prior for both the balanced flow and the remainder of the signal, and we infer their respective covariance functions by fitting parametric models to the observed SSHA wavenumber spectrum. Using these inferred covariance functions, we perform a Bayesian inversion to produce swath-aligned SSHA maps that isolate the balanced signal and fill the nadir gap. We evaluate the method using synthetic data from a high-resolution simulation with realistic SWOT-like small-scale noise added. Comparisons with the underlying model data show that our inversion successfully removes the unbalanced small-scale signal while preserving meso- and submesoscale eddies, fronts, and filaments down to a spatial feature scale (the inverse angular wavenumber) of about 6 km in the subtropical Northwest Atlantic region used for illustration. This comparison also demonstrates that the posterior uncertainty is a reliable estimate of the error. While our focus is on balanced dynamics, the balanced extraction can be extended to include tides, internal waves, and non-Gaussian priors.

Equations governing the flow of a polar fluid, with pressure-dependent Newtonian viscosity, through a variable-porosity medium are developed. Averaged equations are obtained using intrinsic volume averaging. A drag function is introduced to account for the interactions of the fluid with the porous matrix. Darcy and Forchheimer generalized terms are included in the model equations for both granular and consolidated media to account for the effects of the porous microstructure.

Adaptive control is applied to a supersonic dual-stream jet flow comprised of Mach 1.6 core and Mach 1.0 bypass streams that mix to form a supersonic shear layer. The vortices shed are the source of a high-frequency tone that persists throughout the flow. The intricate flow dynamics motivates the need for an elaborate and efficient actuation system to suppress the tone and weaken the propagating shock train. The present work utilizes online dynamic mode decomposition, which estimates the system dynamics as a locally linear evolution. Snapshot matrices are constructed using sensor measurements, facilitating economical and real-time computations, which are continuously updated and used in a feedback control model. Adaptive control is found to efficiently target the resonant tone with little disturbance to the mean features. The framework is not sensitive to sensor placements, enabling actuator design under physically realizable spatial locations in practical implementation. To reflect physical limitations, constraints are imposed on the controller model. It is found that the restricted controller yields greater vortex suppression due to repeated transitory stabilization of the shear layer instability. Statistical analysis reveals intermittent low-pressure events are responsible for the characteristic frequency, which are largely suppressed by adaptive feedback control.

Excitable tissue is fundamental to brain function, yet its study is complicated by extreme morphological complexity and the physiological processes governing its dynamics. Consequently, detailed computational modeling of this tissue represents a formidable task, requiring both efficient numerical methods and robust implementations. Meanwhile, efficient and robust methods for image segmentation and meshing are needed to provide realistic geometries for which numerical solutions are tractable. Here, we present a computational framework that models electrodiffusion in excitable cerebral tissue, together with realistic geometries generated from electron microscopy data. To demonstrate a possible application of the framework, we simulate electrodiffusive dynamics in cerebral tissue during neuronal activity. Our results and findings highlight the numerical and computational challenges associated with modeling and simulation of electrodiffusion and other multiphysics in dense reconstructions of cerebral tissue.

We present an experimental method to fabricate centimetric thin elastic capsules with highly uniform thickness and negligible bending stiffness using silicone elastomers. In our experiments, the capsules thickness is tunable at fabrication, while internal pressure and hoop (circumferential) stress are adjustable via hydrostatic inflation once the capsules are filled and immersed in water. Capsules mechanics are probed through hydro-elastic waves generated by weak mechanical perturbations at the capsule interface. By analyzing the surface wave dynamics in the Fourier domain, we extract the in-plane stress and demonstrate that the hydro-elastic waves are exclusively governed by hoop stress. This \reponse{provides a controllable macroscopic analogue of liquid drops} characterised by an effective surface tension, allowing the capsules to be modeled as large-scale “elasto-drops” with an inflation and thickness tunable effective surface tension. \reponse{In this limit, bending stiffness is negligible over the experimentally relevant wavelengths, so that the shell dynamics are governed primarily by in-plane tension.} Our work demonstrates that elasto-drops serve as a robust model system for parametric studies of large-scale \reponse{analogues of} liquid drops with experimentally adjustable surface tension.