Papers

The behaviour of internal waves propagating in a background shear flow is studied in the case where the direction of shear is orthogonal to gravity. Ray-tracing theory is used to predict properties of the wave state at locations where instability occurs. Local wave energy growth is found to result from two distinct mechanisms: an increase in wave steepness due to refraction by the shear, or an increase in streamwise velocity perturbations due to wave advection of the background flow. Based on the initial conditions, a dimensionless perturbation energy ratio $F$ is constructed to predict the relative importance of these two mechanisms in facilitating wave-breaking. When $F$ is small and waves become locally steep, perturbation kinetic and potential energy remain approximately equipartitioned and subsequent instabilities are expected to develop due to a combination of shear and convection. On the other hand, as $F$ increases, kinetic energy dominates and wave advection of momentum may instead cause breaking to become increasingly driven by enhanced vertical shear. To test these predictions, fully nonlinear direct numerical simulations are conducted, spanning a range of wave-breaking dynamics. Good qualitative agreement with the theory is found despite substantial departures from the underlying assumptions. Wave breaking leads to significant turbulent dissipation, which in some cases greatly exceeds the initial wave energy. Momentum and energy transfers between the wave, background flow and turbulence are found to be sensitive to the dynamics of breaking, as are the mixing properties.

Lattice spin models featuring kinetic constraints constitute a paradigmatic setting for the investigation of glassiness and localization phenomena. The intricate dynamical behavior of these systems is a result of the dramatically reduced connectivity between many-body configurations. This truncation of transition pathways often leads to a fragmentation of the Hilbert space, yielding highly collective and therefore often slow dynamics. Moreover, this mechanism supports the formation of characteristic elementary excitations, which we investigate here theoretically in a two-dimensional Rydberg lattice gas. We explore their properties as a function of interaction strength and range, and illustrate how they can be experimentally probed via sideband spectroscopy. Here, we show that the transition rate to certain delocalized superposition states of elementary excitations displays collective many-body enhancement.

We derive the stationary distribution in various regimes of the extended Chiarella model of financial markets. This model is a stochastic nonlinear dynamical system that encompasses dynamical competition between a (saturating) trending and a mean-reverting component. We find the so-called mispricing distribution and the trend distribution to be unimodal Gaussians in the small noise, small feedback limit. Slow trends yield Gaussian-cosh mispricing distributions that allow for a P-bifurcation: unimodality occurs when mean-reversion is fast, bimodality when it is slow. The critical point of this bifurcation is established and refutes previous ad-hoc reports and differs from the bifurcation condition of the dynamical system itself. For fast, weakly coupled trends, deploying the Furutsu-Novikov theorem reveals that the result is again unimodal Gaussian. For the same case with higher coupling we disprove another claim from the literature: bimodal trend distributions do not generally imply bimodal mispricing distributions. The latter becomes bimodal only for stronger trend feedback. The exact solution in this last regime remains unfortunately beyond our proficiency.

We show that the antisymmetric Mueller generator provides a universal algebraic kernel for geometric phase in classical polarization optics and in quantum two-level systems. For any ideal retarder, the antisymmetric 3x3 block of its Mueller matrix (the antisymmetric generator of the adjoint SU(2) action on the Stokes vector) encodes the angular-velocity vector that drives the tangential motion on the Poincaré sphere and fully determines the Pancharatnam-Berry phase, while the symmetric block is geometrically neutral. The same antisymmetric generator governs the evolution of pure qubit states on the Bloch sphere. This unified viewpoint yields operational criteria to identify and control geometric-phase contributions from measured Mueller matrices and from qubit process tomography.

This work presents a case study of a heterogeneous multiphysics solver from the nuclear fusion domain. At the macroscopic scale, an auto-differentiable ODE solver in JAX computes the evolution of the pulsed power circuit and bulk plasma parameters for a compressing Z Pinch. The ODE solver requires a closure for the impedance of the plasma load obtained via root-finding at every timestep, which we solve efficiently using gradient-based Newton iteration. However, incorporating non-differentiable production-grade plasma solvers like Gkeyll (a C/CUDA plasma simulation suite) into a gradient-based workflow is non-trivial. The ”Tesseract” software addresses this challenge by providing a multi-physics differentiable abstraction layer made fully compatible with JAX (through the `tesseract_jax` adapter). This architecture ensures end-to-end differentiability while allowing seamless interchange between high-fidelity solvers (Gkeyll), neural surrogates, and analytical approximations for rapid, progressive prototyping.

Pushing nanoscale optical confinement to its ultimate limits defines the regime of nano-cavity quantum electrodynamics (nano-cQED), where light–matter interactions approach the fundamental quantum limits of individual atoms, e.g., picocavities. However, realizing such extreme confinement in a stable and controllable manner remains a key challenge. Here, we introduce a van der Waals material-based nano-cQED platform by coupling monolayer MoS2 excitons to plasmonic sub-nanocavities formed via assembly of ultrasmall gold clusters (3-5 nm) in the nanogap of a nanoparticle-on-mirror nanocavity. These clusters emulate the field-confining role of atomic protrusions of the picocavities through a resonance-insensitive lightning-rod effect, achieving deep-subwavelength mode volumes. In this nano-cQED testbed, we observe pronounced multi-branch Rabi splittings and ultrastrong lower-branch polaritonic photoluminescence with up to 10^4-fold enhancement. This deterministic architecture provides a controllable pathway to access picocavity-like behavior and opens new opportunities for single-molecule spectroscopy and the exploration of nano-cQED.

Hydrophobic solid-water interfaces underpin processes in nanofluidics, electrochemistry, and energy technologies. Microscopic insights into these systems are often inferred from our understanding of the air-water interface, which is assumed to exhibit similar behavior. Here, we challenge this paradigm by combining heterodyne-detected vibrational sum-frequency generation spectroscopy with machine-learning molecular dynamics simulations at first-principles accuracy to investigate the graphene-NaCl(aq) interface as a prototypical hydrophobic solid-water system. Spectroscopic results suggest that ions have a minimal effect on the structure of the interfacial water, while simulations reveal that Na$^{+}$ and Cl$^{-}$ accumulate densely at the surface. Together, these findings reveal a new adsorption mechanism that departs from the established air-water interface paradigm, where interfacial ion adsorption is typically associated with, and often detected through, pronounced alteration of the interfacial water alignment and orientation. This difference arises because ions cannot penetrate the solid boundary and reside at a similar depth as the interfacial water molecules. As a consequence, large ion populations can be accommodated within the extended two-dimensional hydrogen-bond network at the interface, causing only minor local distortions but significant changes to its longer-range connectivity. These results reveal a distinct mechanism of electrolyte organization at aqueous-carbon interfaces, relevant to energy applications, where performance is highly sensitive to the local organization of interfacial water.

Solar hard X-ray observations provide diagnostics of the hottest plasmas and of nonthermal electron populations present during solar flares and coronal mass ejections. HXR images of specific energy ranges often contain overlapping contributions of these components, complicating their interpretation. This is even more challenging as HXR imagers generally use an indirect imaging system. Our work aims to separately image individual spectral components, such as thermal loops, superhot sources, and nonthermal footpoint sources, rather than obtaining images of specific energy ranges that show a combination of all components. We introduce a new method called spectral component imaging and apply it to observations provided by the Spectrometer/Telescope for Imaging X-rays (STIX) aboard Solar Orbiter. First, the flare integrated HXR spectrum is fitted with individual spectral components to get the relative contributions of each component in each native STIX energy channel. In a second step, a set of linear equations is created based on these weights and the observed, energy-dependent STIX visibilities. The visibilities of the individual spectral components are derived by means of a linear least-squares approach and are subsequently utilized for image reconstructions. We demonstrate the effectiveness of spectral component imaging on four different flares observed by STIX. This method provides powerful diagnostics, particularly for flares with hot and superhot components, allowing us to spatially separate these two thermal components. We apply our methodology to the nonthermal peak of the X7.1 flare SOL2024-10-01, and we find that the superhot component is located 4.8 Mm away from the hot thermal loops. The thermal energy of the superhot component is approximately 20% of the energy content of the hot component, highlighting the significance of superhot components in the total flare energy budget.

Color codes present distinct advantages for fault-tolerant quantum computing, such as high encoding rates and the transversal implementation of Clifford gates. However, existing matching-based decoders for the color codes such as the restricted decoder (Kubica and Delfosse, 2023), suffer from limited decoding performance. Inspired by the global decoding insight of the unified decoder (Benhemou et al., 2023), this paper introduces a correlated decoder for the 4.8.8 color code, which improves upon the conventional restricted decoder by leveraging correlations between restricted lattices, and is derived by mapping the correlated matching decoder for the surface code onto the color code lattice. Analytical and numerical results show that the correlated decoder achieves higher thresholds than the restricted and unified decoders, while matching the performance of the unified decoder at very low physical error rates. Under the code capacity and phenomenological noise models, the estimated thresholds for the color code against bit-flip error are 10.38% and 3.13%, respectively. Furthermore, by applying the surface-color code mapping, the thresholds of 16.62% and 3.52% are obtained for the surface code against depolarizing noise.

Spinning ice discs in nature have been reported for more than a century, yet laboratory experiments have yielded diverse observations and contradictory explanations, leaving the mechanism behind the disc motion elusive. Here we combine numerical simulations and scaling analysis to investigate a freely moving ice disc in a lab-scale water tank. We observe the disc remaining stationary or experiencing spontaneous motion, depending on the disc-water temperature difference and water depth. The motion is initiated by a buoyancy-driven, downward plume arising from water's density anomaly – its density peaks near $4^\circ$C. Crucially, the plume breaks rotational and mirror symmetries after descending beyond a critical distance due to a thermoconvective instability, thereby inducing the disc to move autonomously. Our findings quantitatively unify disc behaviors observed across independent experiments and establish a predictive criterion for the onset of disc motion. More broadly, we point to a route for thermally-driven transport: coupling of bulk thermoconvection and moving bodies, relevant to geophysical processes such as continental drift and iceberg capsizing.

Pedestrians in crowds frequently move as part of small groups, constituting up to 70% of individuals. Dyads (groups of two) are most frequent. Understanding quantitatively the dynamics of dyads walking in crowds is therefore an essential building block towards a fundamental comprehension of crowd behavior as a whole, and mandatory for accurate crowd dynamics models. Unavoidably, due to the non-deterministic behavior of pedestrians, characterizations of the dynamics must be probabilistic. In this work, we analyse the dynamics of over 6M dyads: a statistical ensemble of unprecedented resolution within a multi-year real-life pedestrian trajectory measurement campaign (21M trajectories, from Eindhoven Station, NL). We provide phenomenological models for dyad behavior depending on the surrounding crowd state. We present a thorough collection of fundamental diagrams that probabilistically relate both dyad velocity and formation to the state of the surrounding crowd (density, relative velocity). Depending on the surrounding crowd, dyads adjust interpersonal distance and may shift in formation, possibly moving from abreast states (which favors social interaction) to in-file (which favors navigating dense crowds). To quantitatively investigate formation changes, we introduce a scalar indicator, which we dub Orientation Log-Odds (OLO), that quantifies the relative log-likelihood of abreast versus in-file formations. Conceptually, the OLO quantifies the energy difference between abreast and in-file configurations under a Boltzmann-like assumption. We model how OLO depends on the crowd state, showcasing that its derivative is a product of two velocity-density fundamental diagrams. Together, these results provide a statistically robust, data-driven description of dyad configuration dynamics in real-world crowds, establishing a foundation towards new predictive, group-aware crowd models.

Recent photoelectron spectroscopy of B$_{80}^-$ was interpreted in terms of a fullerene-like cage structure. During our systematic investigation of medium-sized boron clusters, we identified a $D_{3h}$-symmetric bilayer isomer whose simulated photoelectron spectrum reproduces the principal features of the experimental photoelectron spectrum within 0.04 eV. The bilayer is energetically competitive with previously proposed structures and remains dynamically stable up to 1400 K according to ab initio molecular dynamics and vibrational analyses. Its electronic structure exhibits a 0.72 eV HOMO-LUMO gap and strong interlayer aromaticity, reflected by a NICS(0) value of $-44.3$ ppm in the interlayer B-B bonding region. These findings reveal a stable bilayer motif in the B$_{80}$ energy landscape and support its viability as a possible alternative structural assignment for the experimentally observed B$_{80}^-$.

We present an inverse method to compute freeform optical surfaces that transform a light distribution, parameterized by two source planes, into two separate target distributions. The surfaces can be reflectors or lenses, and control both the spatial and directional source and target coordinates of light rays. From energy conservation we derive Jacobian equations for optical mappings, and the optical path length provides generating functions for the optical surfaces. A three-stage least-squares algorithm numerically solves the resulting equations. We present examples with complex source and target distributions.

Electrokinetic flows in microchannels with opposite charge asymmetry, i.e., unequal and contrasting surface charges on opposing channel walls, significantly influence microfluidic hydrodynamics and can be exploited for enhanced control of mass transfer, mixing, and heat transport in microfluidic applications. This study numerically investigates electroviscous flow of a liquid electrolyte through an oppositely charged non-uniform microslit. The governing Poisson, Nernst-Planck, and Navier-Stokes equations are solved using the finite element method to determine the coupled electrokinetic fields for a wide range of dimensionless parameters: Reynolds number (Re = 0.01), Schmidt number (Sc = 1000), inverse Debye length (K = 2-20), top-wall surface charge density (St = 4-16), surface charge density ratio (Sr = -2 to 0), and contraction ratio (dc = 0.25). For completeness, results for like-charged devices, where both walls carry surface charges of the same sign (Sr = 0-2), are also included. The results show that maximum enhancement in total electrical potential (|{\Delta}U|) and pressure drop (|{\Delta}P|) reaches 296.82% at K = 20, St = 4, -2 \le Sr \le -1.25, and 14.57% at St = 16, Sr = 0, K = 2-20, respectively. The electroviscous correction factor Y exhibits maximum increases of 14.02% at K = 2, St = 16; 11.81% at K = 2, Sr = 0; and 14.57% at Sr = 0, St = 16, when Sr increases (-0.75 to 0), St increases (4 to 16), and K decreases (20 to 2), respectively. The overall maximum increment in Y is 15.13% at K = 2, Sr = 0, St = 16, relative to the non-electroviscous flow case. These findings demonstrate that opposite charge asymmetry, though weaker than similar asymmetry, still strongly influences electroviscous flow in non-uniform microchannels.

We consider theoretical models of the nanolaser and logic gates on carbon nanotubes (CNTs). In our work, it is shown at pumping the nanoresonator of the nanolaser on CNT by optical radiation using a quantum dot as nano light emitted diode (LED), the coherent flow of surface plasmon-polaritons arises when the generation threshold is exceeded. The coherent plasmonic flow from the partially reflecting mirror of the nanolaser enters the attached CNT plasmonic waveguide. Plasmonic logic gates NOT and OR based on CNTs represent the complete functional basis for binary logic. The proposed nanolaser and logic gates on CNTs can be used in plasmonic circuitry in the telecommunication frequency band.

Twin-wire laser directed energy deposition (TW-LDED) provides a promising route for alloying and fabrication of compositionally graded structures. However, inherent multiparameter coupling in twin-wire systems critically exacerbates both process instabilities and compositional inhomogeneity. This unresolved issue escalates into a fundamental technological bottleneck, as the underlying physical mechanisms remain poorly understood. This study developed a high-fidelity multi-physics and multiphase simulation framework coupled with experimental validation to reveal thermal-fluid behavior and heat-mass transfer mechanisms in TW-LDED using Inconel 718 and SS316L fine wires. Three distinct transition modes were identified: twin-wire melt droplet, twin-wire liquid bridge, and droplet-bridge mixed transitions, with the twin-wire liquid bridge regime delivering optimal stability and uniform mixing. Parametric analysis demonstrates that increasing wire feeding speed or decreasing wire initial height promotes stable liquid bridge formation, while small laser spots at low feeding speeds induce excessive volumetric energy density and bridge instability. Simulation and single-track experiments confirm that liquid bridge transitions reduce dimensional fluctuations by 85% while enhancing compositional homogeneity. Conversely, the melt droplet-bridge transition mode creates periodic flow switching and compositional discontinuities along the scan direction. Finally, a 60 mm functionally graded ring was successfully fabricated using optimized parameters, achieving uniform elemental distribution in the transition zone without significant segregation, validating the feasibility of TW-LDED for functionally graded components.

High-harmonic generation (HHG) in two-dimensional materials offers a compelling route toward compact extreme ultraviolet sources and probing electron dynamics on the attosecond scale. However, achieving precise control over the emission and disentangling the complex interplay between intraband and interband quantum pathways remains a central challenge. Here, we demonstrate through first-principles simulations that HHG in monolayer WS2 can be subjected to precise, complementary control by combining all-optical two-color laser fields with mechanical strain engineering. This dual-mode strategy provides distinct, orthogonal control over harmonic yield, polarization, and spectral features. We reveal that sculpting the two-color field's relative phase provides a sub-femtosecond switch for the quantum coherence of electron-hole pairs, thereby optimizing harmonic emission. Crucially, we uncover that tensile strain modulates the total harmonic yield and specifically amplifies the perpendicular harmonic component by nearly a factor of two. This enhancement arises through a dual mechanism - while strain-modified band dispersion enhances the intraband current, a significant reshaping of the Berry curvature (BC) substantially increases the anomalous velocity contribution to the interband response. This quantum geometric effect manifests as a robust, monotonic dependence of the harmonic yield on strain and a significant amplification of the perpendicularly polarized harmonics, providing a clear experimental signature for probing quantum geometric effects. Our findings establish a versatile framework for optimizing solid-state HHG and introduce a powerful all-optical method to map strain and quantum geometric properties of materials, positioning monolayer WS2 as a model system for exploring attosecond physics at the nexus of bulk and atomic scales.

Neutrino telescopes are large-scale detectors designed to observe Cherenkov radiation produced from neutrino interactions in water or ice. They exist to identify extraterrestrial neutrino sources and to probe fundamental questions pertaining to the elusive neutrino itself. A central challenge common across neutrino telescopes is to solve a series of inverse problems known as event reconstruction, which seeks to resolve properties of the incident neutrino, based on the detected Cherenkov light. In recent times, significant efforts have been made in adapting advances from deep learning research to event reconstruction, as such techniques provide several benefits over traditional methods. While a large degree of similarity in reconstruction needs and low-level data exists, cross-experimental collaboration has been hindered by a lack of diverse open-source datasets for comparing methods. We present NuBench, an open benchmark for deep learning-based event reconstruction in neutrino telescopes. NuBench comprises seven large-scale simulated datasets containing nearly 130 million charged- and neutral-current muon-neutrino interactions spanning 10 GeV to 100 TeV, generated across six detector geometries inspired by existing and proposed experiments. These datasets provide pulse- and event-level information suitable for developing and comparing machine-learning reconstruction methods in both water and ice environments. Using NuBench, we evaluate four reconstruction algorithms - ParticleNeT and DynEdge, both actively used within the KM3NeT and IceCube collaborations, respectively, along with GRIT and DeepIce - on up to five core tasks: energy and direction reconstruction, topology classification, interaction vertex prediction, and inelasticity estimation.

Detecting Pancharatnam-Berry geometric phases of light typically requires interferometry or diffraction through a specially truncated aperture. Here, we introduce a simpler method that allows direct and fully visual detection of geometric phases in structured light without using interferometers or beam truncation. Our approach takes advantage of the geometric phase that naturally arises in SU(2) structured beams, where spatial wave packets follow caustic trajectories during propagation. By observing the evolution of these caustic-linked wave packets, we directly visualize both the geometric phase and the Gouy phase. This visual detection method provides new insight into geometric phases in complex optical fields and expands the possibilities for designing optical systems that exploit phase geometry.

The fundamental division of the total quantum evolution phase into geometric and dynamical components is a central problem in quantum physics. Here, we prove a remarkably simple and universal law demonstrating that this partitioning is governed, at every instant, solely by a single geometric quantity: the Bargmann angle (Bures angle). This result provides a universally applicable and rigorous way to define the exact fraction of the total phase that is geometric versus dynamical in origin, thereby establishing a new quantitative link between the dynamics of quantum evolution and the geometry of the state space. This finding has immediate practical consequences, furnishing a real-time measure of the geometricity of an evolution for designing high-fidelity geometric quantum gates with optimized robustness, and opening new avenues for quantum speed limit and coherent control.

The interaction between free electrons and optical modes underlies a variety of quantum and nanoscale light-matter phenomena, yet the associated momentum exchange with the sample largely remained overlooked. Here, we experimentally demonstrate the momentum transfer from free electrons to planar samples during optical mode excitation using momentum-resolved electron energy-loss spectroscopy. The momentum transfer to the sample modifies the apparent dispersion relation which is significant when the planner sample is tilted. Under specific conditions, the sample receives momentum opposite to the electron beam direction.

Zigzag edges of graphene have long been predicted to exhibit magnetic electronic state near the Fermi level, which can cause spin-related phenomena and offer unique potentials for graphene-based spintronics. However, the magnetic conduction channels along these edges have yet been reported experimentally. Here, we report the observation on signatures of magnetism in zigzag graphene nanoribbons (zGNRs) embedded in hexagonal boron nitride (h-BN). The in-plane bonding with BN can stabilize the edges of zGNRs, and thus enable a direct probing of the intrinsic magnetism. Firstly, the presence of magnetism of a zGNR was confirmed by scanning NV center microscopy. And then, zGNR was fabricated into a transistor with a width of ~9 nm wide and a channel length of sub-50 nm. By performing magneto-transport measurements, Fabry-Pérot interference patterns were observed in the transistor at 4 Kelvin, which indicates a coherent transport through the channel. A large magnetoresistance of ~175 {\Omega}, corresponding to a ratio of ~1.3 %, was observed at the same temperature. More importantly, such magneto-transport signal is highly anisotropic on the magnetic field direction, and its appearance extends well above room temperature. All these evidences corroborate the existence of robust magnetic ordering in the edge state of zGNR. The findings on zGNR embedded in h-BN provide an effective platform for the future exploration of graphene-based spintronic devices.

Motivated by recent experimental breakthroughs toward a realization of a solid-state Thorium-229 nuclear clock, we review the technology, basic physics motivation, and limitations of the present generation of atomic clocks. We then discuss prospects for a new generation of clocks based on an anomalous low-energy 8.4 eV nuclear transition in Th-229, with an extremely long lifetime of 641 seconds when doped into CaF crystals. To realize such solid-state nuclear clocks one must confront basic nuclear, AMO, and solid state physics questions. Key challenges are understanding and minimizing the effects of inhomogeneous broadening, associated with strains and electric field gradients due to both the Th dopants and intrinsic crystal defects.

The time-dependent Schrödinger equation (TDSE) in real space is fundamental to understanding the dynamics of many-electron quantum systems, with applications ranging from quantum chemistry to condensed matter physics and materials science. However, solving the TDSE for complex fermionic systems remains a significant challenge, particularly due to the need to capture the time-evolving many-body correlations, while the antisymmetric nature of fermionic wavefunctions complicates the function space in which these solutions must be represented. We propose a general-purpose neural network framework for solving the real-space TDSE, Fermionic Antisymmetric Spatio-Temporal Network, which treats time as an explicit input alongside spatial coordinates, enabling a unified spatiotemporal representation of complex, antisymmetric wavefunctions for fermionic systems. This approach formulates the TDSE as a global optimization problem, avoiding step-by-step propagation and supporting highly parallelizable training. The method is demonstrated on five benchmark problems, achieving excellent agreement with reference solutions across all cases. These results demonstrate the method's accuracy and flexibility within the bound-state manifold across various dimensions and interaction regimes. While the current localized Ansatz inherently restricts the description of extensive ionization and continuum states, the method demonstrates the capability to stably simulate coherent multi-electron dynamics over extended time windows. Our framework offers a highly expressive alternative to traditional basis-dependent or mean-field methods, opening new possibilities for ab initio simulations of time-dependent quantum systems, with applications in quantum dynamics, molecular control, and ultrafast spectroscopy.

Closed-Form Kepler solutions in projective coordinates are used to define a corresponding set of eight orbit elements and obtain their governing equations for arbitrarily-perturbed two-body dynamics. The elements and their dynamics are singularity-free in all cases besides rectilinear motion (when angular momentum vanishes). The classic J2-perturbed two-body problem is developed and used for numerical verification.

This study numerically examines the steady unconfined laminar flow of incompressible non-Newtonian power-law fluids past a pair of side-by-side counter-rotating circular cylinders using the finite element method. The cylinders simultaneously rotate at equal angular speeds in opposite directions, with the upper cylinder (UC) rotating clockwise and the lower cylinder (LC) counterclockwise. The numerical simulations are performed over wide parameter ranges: power-law index ($0.2 \le n \le 1.8$), rotational rate ($0 \le \alpha \le 2$), gap ratio ($0.2 \le G \le 1$), and Reynolds number ($1 \le Re \le 40$). The detailed influence of these flow parameters on key flow characteristics, including streamlines, surface pressure, centerline velocity, and individual as well as total drag and lift coefficients, is systematically analyzed. For stationary cylinders ($\alpha = 0$), a twin-vortex structure forms in the wake, which progressively vanishes with increasing rotation ($\alpha = 2$). The surface pressure coefficient attains its maximum values for shear-thickening fluids ($n > 1$) at higher rotational speeds, irrespective of the gap ratio. The total drag coefficient ($C_D$) decreases with increasing $\alpha$ and $n$, whereas the lift coefficient ($C_L$) exhibits a more intricate dependence on the flow parameters. The results provide fundamental insights into the interplay between rotation, non-Newtonian rheology, and geometric confinement in determining the hydrodynamic behavior of rotating cylinder systems.

A dual-mode asymmetric transmission (AT) nanodevice based on the asymmetric and orthogonal grating-film-grating (AO-GFG) structure is proposed and systematically investigated theoretically. The device supports two distinct localized surface plasmon resonance (LSPR) modes for forward transmission, corresponding to the polarization-dependent (M1) and the polarization-independent (M2) resonances, respectively. This results in the fact that when x-polarized light is incident, only M2 exists; when y-polarized light is incident, both M1 and M2 exist. Besides, both modes yield the maximum isolation ratio of more than 10 dB. The electric field distributions further indicate that M2 exhibits strong confinement and efficient tunneling through the metallic film, while M1 shows weaker but more polarization-sensitive hybridization. The coexistence and tunability of these two modes constitute the physical basis of dual-mode AT, highlighting the AO-GFG structure as a promising platform for high-isolation and polarization-tunable plasmonic devices in the visible and near-infrared regions.

Light-atom chromophores can display properties often associated with heavy-atom compounds, such as intersystem crossing leading to phosphorescence and singlet oxygen generation, yet their use remains comparatively underexplored. Here, we report the synthesis of HM610, a derivative of the benzylidenehydrazinylthiazole light-atom chromophore backbone. Spin-orbit couplings (SOCs), computed with the sf-X2C-S-TDDFT method, follow Slater-Condon rules and predict moderate values. Trajectory surface hopping simulations further illustrate the role of dynamical effects in promoting ISC, yet these results together establish that HM610 has only limited potential as a triplet sensitizer without further structural modification, such as heavy atom substitution. Based on the benchmarked (TD)DFT protocol, a computational set studying six systematic analogues allowed us to study the influence of electron-donating (-OMe) and electron-withdrawing (-CF3) substituents on the common backbone, revealing the impact of substitution on the geometry and photophysics of light-atom analogues of HM610 and paving the way for future studies where the introduction of heavy atoms and their impact on triplet sensitization by this family of chromophores can be probed.

Integrated photonics is increasingly demanded in applications such as large-scale data centers, intelligent sensing, and next-generation wireless communications, where compact, multifunctional, and energy-efficient components are essential. Inverse-designed photonics, empowered by optimization and learning algorithms, have emerged as a powerful paradigm for realizing compact and multifunctional integrated photonic components. In this work, we develop a staged-annealing topological optimization (SATO) framework tailored for the design of integrated terahertz (THz) beam-shaping devices. Employing this inverse-designed framework, we experimentally demonstrate a class of compact THz vortex beam emitters on an all-silicon on-chip platform. These devices efficiently convert the in-plane fundamental transverse electric (TE) waveguide mode into free-space vortex beams with mode purity up to 87% and energy conversion efficiency up to 74% across the target wavelength range (680 {\mu}m to 720 {\mu}m). The inverse-designed emitters exhibit ultracompact footprints (lateral size < 4{\lambda}) and a free-standing configuration, enabling the generation of dual-directional vortex beams carrying opposite topological charges. The proposed SATO framework provides a generalizable and fabrication-compatible approach for THz photonic device engineering, offering a scalable pathway toward complex structured beam manipulation in next-generation wireless communication systems and on-chip integrated THz photonic systems.

Electrocorticographic brain computer interfaces are powerful emergent technologies for advancing basic neuroscience research and targeted clinical interventions. However, existing devices require trade-offs between coverage area, electrode density, surgical invasiveness and complication risk: limitations that fail to meet the demands of next-generation BCI. Here, we report a guidewire-driven deployable ECoG BCI device that can be epidurally implanted using minimally invasive procedures. Our ultra-flexible but strong thin-film electrode array, which packs 256 electrodes into 4 cm2, can be folded, pulled through millimetre-sized skull holes, and unfurled seamlessly onto the brain dura mater. When deployed on the canine brain, it captures abundant high-quality auditory neural signals with distinct features of hearing that can be used to classify sound types with over 80% accuracy using various standard machine learning models. Our device is biocompatible for chronic monitoring, easy and fast to deploy and importantly, resolves the key trade-offs limiting current BCI technologies.