Papers

The computational discovery of phonon-mediated superconductors is hindered by the prohibitive cost of density functional perturbation theory (DFPT). Here, guided by the metallized $\sigma$-bonding picture, we introduce the $\sigma$-bonding density of states ($\sigma$DOS) as an efficient physical descriptor to identify high-transition-temperature ($T_{\mathrm{c}}$) superconductors from density functional theory (DFT)-level electronic structure without explicit DFPT calculations. The evaluation of $\sigma$DOS can be further accelerated by a deep-learning DFT Hamiltonian method, enabling efficient large-scale screening for superconductors. Screening 2 million materials, we identify B$_{13}$Se as an ambient-pressure superconductor candidate with predicted $T_{\mathrm{c}} > 40$~K, together with a family of high-$T_{\mathrm{c}}$ B$_{13}X$ candidates, supporting the effectiveness of this discovery strategy. By bridging physics priors with AI acceleration, this study delivers an efficient and generalizable route for computational materials discovery in the AI era.

Physics-Informed Neural Networks (PINN) struggle with stiff, regime-changing transport equations due to instability, loss imbalance, and violations of physical consistency. This paper investigates these failures through the Marshak wave equations, a canonical benchmark from radiative transport, where initial and boundary conditions differ by up to 12 orders of magnitude, and proposes modifications to the standard PINN framework to overcome them. Three modifications are introduced: a ScaledSigmoid final activation enforcing physical bounds and positivity of the unknowns; a logarithmic MSE loss replacing the standard quadratic loss for initial and boundary conditions, enabling training across extreme scale disparities; and explicit enforcement of global conservation laws as an additional physics loss term. Monte Carlo sampling with exponential time weighting is used throughout. The proposed framework recovers the Marshak wave dynamics - including the hot, cold, and wave-front regions - in good agreement with a reference Implicit Monte Carlo solution (sub-millimeter absolute error on the front position, although the relative error remains substantial at early times), with run times under 5 minutes. Ablation studies confirm that each ingredient is essential: linear activation, absence of the logarithmic loss, or removal of the PDE term each independently cause the method to fail qualitatively. This work identifies and resolves three concrete failure modes of standard PINN on stiff hyperbolic systems with nonlinear coupling. The combination of bounded activations, scale-aware loss functions, and conservation law enforcement constitutes a framework validated on the present one-dimensional Marshak wave problem, with potential extension to other coupled stiff transport systems in engineering.

The spatio-temporal evolution of the current filamentation instability in a relativistic beam–plasma system is studied analytically and with two-dimensional particle-in-cell simulations. A partial differential equation for the transverse vector potential is derived for a sharp-front relativistic beam entering cold, unmagnetized plasma, including a second-order spatial derivative term that governs the spatial growth near the beam front. The equation is solved analytically for constant, linearly growing, and oscillatory initial noise when this term is neglected, and numerically when it is included, as no closed-form solution then exists. For constant initial noise, the numerical solution reproduces the simulated magnetic-field structure, unlike the analytical solution without the term. This shows that the longitudinal field modulation is intrinsic to the instability, present even for a noise with constant amplitudes. The noise profile as well can influence the spatial-temporal evolution of the instability, which we discuss further considering linearly growing and oscillatory noise. The field grows spatially behind the beam front and saturates at a length $L_{\mathrm{sat}}\propto(v_{0b}+2)v_{0b}/\gamma_{0b}^{3}$, where $v_{0b}$ and $\gamma_{0b}$ are the beam velocity and Lorentz factor, beyond which growth is purely temporal. The saturation length increases linearly in time at a constant rate $\mathrm{d}L_{\mathrm{sat}}/\mathrm{d}\tau\approx0.42\,c$, matching the analytical estimate. The temporal growth rate remains unchanged, so the term modifies the spatial transport of the instability rather than its local amplification. For beam velocities above $0.6c$, the model deviates from the simulations as oblique modes and nonlinear filament dynamics outside the single-mode treatment become important.

Small quantitative structure-activity relationship (QSAR) studies are difficult when close molecular analogues have different activity labels. This paper asks whether a quantum kernel can add similarity information to a Morgan/Tanimoto fingerprint model, and which molecules account for the change. QBioFusion-QSAR uses quantum multiple kernel learning (QMKL): a support vector machine combines a Morgan/Tanimoto kernel with a quantum fidelity kernel constructed from fold-local components derived from RDKit and Mordred descriptors and Deep-PK features. Linear and radial basis function descriptor kernels are included as classical controls. On the 54-molecule PsychLight-A benchmark, Morgan/Tanimoto was the strongest single representation. In the primary stratified five-fold evaluation, QMKL increased accuracy from 0.815 to 0.833 and Matthews correlation coefficient (MCC) from 0.613 to 0.645. Matched-regularization auditing attributed the change to N-Me-5-HT and N-Me-tryptamine changing from false-negative to true-positive predictions; activity-cliff subset MCC increased from 0.07 to 0.22. Repeating the five-fold protocol over ten random partitionings showed that learned QMKL did not exceed Morgan/Tanimoto on mean MCC; paired held-out bootstrap intervals for the matched comparison also span zero. These results support QBioFusion-QSAR as an auditable QMKL framework for identifying localized residual quantum-kernel contributions in small-data, activity-cliff-aware ligand classification.

Wildfire research, modeling, and education require geospatial data from multiple sources that vary in formats, coordinate systems, spatial resolutions, and temporal cadences. This preprocessing burden limits reproducible reuse. We present FireDataForge, an open-source Python framework that automates retrieval and harmonization of 11 wildfire-related sources spanning fire behavior, weather, land cover, vegetation, elevation, built environment, wildland-urban interface, fire history, and satellite imagery. Given an MTBS Event ID, FireDataForge retrieves relevant datasets, aligns them to a common grid, and outputs analysis-ready NumPy arrays with embedded metadata. Batch processing of historical fires demonstrates support for fire behavior simulation, educational visualization, machine learning, and AI-assisted wildfire analysis.

Hard carbons are a class of disordered materials with widespread application in energy storage. Despite decades of research, their atomistic formation mechanisms have remained elusive, due to the difficulty of both in situ experimental characterization and first-principles simulations. Here, we describe the formation mechanism of hard carbon from the thermal decomposition of polyvinylidene chloride (PVDC), using first-principles-quality simulations with a bespoke machine-learned interatomic potential model. Our results indicate a two-stage process, consisting of (i) radical-mediated dehydrochlorination, which generates reactive unsaturated carbon sites, and (ii) progressive carbon-carbon cross-linking followed by thermally activated rearrangement into an extended sp$^{2}$-bonded network. We provide an atomistic account of non-hexagonal ring motifs emerging during pyrolysis, supporting the empirically-derived theory that these motifs induce the intrinsic curvature that frustrates graphitic ordering in hard carbons.

The recently developed Q-variable formalism generalises the Elsässer representation by providing a wave-aligned representation applicable to a broad class of magnetohydrodynamic disturbances, including Alfvénic, fast, slow, and kink waves. While this framework has proven useful for the study of wave dynamics and turbulence, its behaviour in the presence of plasma discontinuities has not yet been established. In this work, we derive the complete set of Rankine-Hugoniot jump conditions in terms of the Q-variables by rewriting the ideal MHD equations in a form suitable for shock-frame jump analysis. This yields explicit jump relations for mass, momentum, magnetic flux, and energy. We then demonstrate analytically that these relations are exactly equivalent to the classical MHD Rankine-Hugoniot conditions. This reformulation provides a wave-aligned representation of MHD discontinuities and offers a natural framework for discussing directional wave content and branch-restricted limits when $\alpha$, the wave-branch parameter entering the Q-variable definition, is chosen consistently with the relevant characteristic speed. The resulting formulation is well suited for the analysis of wave-shock interactions in magnetised plasmas, with potential applications to the solar wind, magnetospheric systems, and large-scale models of structured plasma environments such as UAWSOM.

We study plasmonic excitations in twisted bilayer graphene within a non-Hermitian framework that incorporates effective gain and loss. Using a non-Hermitian extension of the Bistritzer–MacDonald continuum model together with a biorthogonal Kubo formalism for the optical conductivity, we determine how the moiré electronic structure enters the plasmonic response of the active bilayer. We find that non-Hermiticity modifies the collective spectrum, yielding optical and acoustic plasmon branches, with the acoustic branch exhibiting strong subwavelength confinement. In the parity-time-symmetric configuration, gain–loss engineering can reduce the effective spatial damping and enhance the propagation length within the ideal linear model. The same regime produces strongly localized transverse-magnetic near fields. We argue that the enhancement is not a generic consequence of adding gain to a bilayer, but results from the combined influence of moiré-band reconstruction, biorthogonal optical matrix elements, and non-Hermitian modification of the plasmon pole. We also discuss the limitations imposed by disorder, substrate loss, gain saturation, and stability of the parity-time-symmetric regime. These results identify twisted bilayer graphene as a promising, but experimentally demanding, platform for tunable non-Hermitian plasmonics in moiré quantum materials.

Segmenting the temporomandibular joint (TMJ) disc from MRI is essential for accurate diagnosis of internal derangement, yet it remains unreliable in practice due to its small size, low contrast, and morphological variability. Existing methods, primarily adapted from general segmentation architectures, often produce fragmented or anatomically inconsistent masks, leading to unstable measurements of disc position and shape for downstream diagnosis. To address these challenges, we propose TISC, a TMJ disc segmentation framework that integrates semantic anchoring with clinical metadata-guided boundary refinement. The framework first establishes robust disc localization in the foundation model feature space via a Prototypical Semantic Anchoring (PSA) module that aggregates adjacent-slice MedDINOv3 features and derives a prototype-driven similarity map. It then performs targeted boundary refinement through a Clinical-Metadata Point Refinement (C-MPR) module, with point-wise predictions modulated by Mouth Open Limitation (MOL), a clinical indicator associated with disc displacement without reduction. On a large-scale cohort of 2,488 PD MRI volumes from 1,300 patients, our method achieves up to a 4.96 Dice improvement over strong baselines across diverse architectures, delivering more anatomically coherent and clinically reliable TMJ disc segmentation.

Topology has become a central concept in understanding physical phenomena, leading to important advances in condensed matter and photonics. Recent work has established a universal upper bound on the energy gap of Chern insulators in electronic systems, revealing a fundamental connection between topology, quantum geometry, and optical absorption. Here, we generalize this framework to photonic systems, deriving rigorous upper bounds on gap Chern numbers without requiring explicit topological analysis. Our approach enables the estimation of the topological charge of band gaps in both dispersive and nondispersive regimes.

Electron transport in a Hall thruster is investigated at the test particle level using prescribed electric fields derived from the electron drift instability (EDI) resolving three dimensional particle-in-cell (PIC) simulation. Four primary electric field configurations are considered: static averaged field, full PIC field, proper orthogonal decomposition (POD) reconstructed field, and a simplified analytical Ey field. Two additional control cases, the magnetic-field-only case and the denoised PIC field, are also included. Transport statistics show that the averaged field produces only weak axial cross field transport. In contrast, the full PIC field produces clear fluctuation driven transport, characterized by pronounced negative axial displacement, enhanced channel entry, finite channel residence, particle energization, and appreciable anode directed loss. POD analysis shows that the transport relevant EDI electric field structures are distributed over multiple coupled modes, and that a moderate truncation order of approximately 20 modes is required to recover the main transport signatures. The analytical Ey model separately examines the influence of azimuthal electric field fluctuations on axial electron transport and shows that fluctuation amplitude is a primary determinant.

Salt fingering drives diapycnal scalar exchange across thermohaline interfaces that are statically stable but double-diffusively unstable. Oceanic interfaces are finite-depth structures and may carry roughness inherited from waves, shear, intrusions, or prior mixing. We test how the horizontal spectrum of that roughness controls the route from a two-layer interface to a finite-depth salt-finger plume forest. Direct simulations of the modeled Boussinesq equations are performed at $\mathrm{Pr}=7$, $\tau=0.01$, and $\mathrm{R}_\rho=1.2$, with matched domain, grid, amplitude, boundary treatment, and analysis measures. The imposed spectra are high-annulus, low-mode, and mixed; a second mixed realization tests robustness. The imposed spectrum selects distinct routes to vertical exchange. High-annulus roughness remains compact and branch-locked through $t=60$, without a tracked broad-branch transition. Low-mode roughness begins on the broad branch, produces the strongest salinity transport at $t=45$, and reaches the finite-depth boundary region first. Mixed roughness follows a velocity-led pathway: vertical velocity selects the broad branch before salinity, while salinity develops the richest planform spectral population. At $t=45$, the mixed salinity effective mode count is $86.66$, compared with $3.26$ for high-annulus forcing and $5.46$ for low-mode forcing. Angular and signed-branch measures show branch-dependent diagonal organization, and probe/volume measures show that local plume-passage asymmetry does not imply large global upper/lower imbalance. The replicate preserves the mixed route with shifted transition times. Thus a finite-depth thermohaline interface can retain spectral memory, controlling whether salt-finger mixing remains localized, penetrates rapidly, or forms a scalar-rich plume forest through delayed modal handoff.

Optical frequency combs on photonic integrated platforms are revolutionizing precision metrology, bio-imaging, atomic and molecular sensing, and ultrafast photonics, yet most remain confined to the near-infrared. This restriction prevents access to the ultraviolet, visible, and mid-infrared bands critical for a vast array of quantum, atomic, and molecular systems. The fundamental obstacle has been the lack of a nanophotonic waveguide that simultaneously provides an ultra-broad transparency window, engineered dispersion, ultra-low propagation loss, and a strong Kerr nonlinearity, all while suppressing detrimental two-photon absorption at short wavelengths. Here, we overcome this challenge by exploring tantalum pentoxide for ultra-broadband supercontinuum spanning continuously from the ultraviolet to the mid-infrared, leveraging its broad transparency window (300-8000 nm), a high nonlinear refractive index three times larger than that of silicon nitride, and a wide bandgap that suppresses two-photon absorption. Critically, by using a photolithography assisted chemo-mechanical etching process that avoids a lossy SiO2 upper cladding, we achieve dispersion engineered waveguides with record-low propagation losses of 0.066 dB/cm at telecom wavelengths and 0.43 dB/cm at 780 nm, significantly facilitating the supercontinuum spectral extension into the ultraviolet and the mid-infrared. Pumping these anomalous-dispersion waveguides with femtosecond pulses at 1550 nm yields a gap-free, 3.2-octave supercontinuum spanning from 350 to 3200 nm via a soliton-based dynamics at only 54 pJ pulse energy, representing the broadest comb spectrum on this platform. We further demonstrate a relatively flat spectrum with a -30 dB bandwidth of 1182 nm by engineering normal dispersion, validate the comb coherence via heterodyne detection, and achieve soliton-effect pulse self-compression from 126.7 fs to 19.2 fs.

Sums of independent exponential random variables lead to the Erlang distribution, providing a direct probabilistic route from exponential waiting times to the integer-shape gamma law. This paper investigates how this classical construction changes when the exponential waiting-time density is replaced by the $q$-exponential density of nonextensive statistics. Our main result is an analytical asymptotic expression for the outflow of a mass-conserving cascade of reservoirs driven by a $q$-exponential waiting-time kernel. In the critical case $q=5/3$, the large-cascade flow rate converges to a stable Lévy density whose time argument is shifted by a Galilean-type transformation. This shifted Lévy law gives the asymptotic hydrograph of the cascade. We also found that for the entire regime $1<q<2$ the macroscopic dynamics are governed by $\alpha$-stable Lévy laws. This proves that anomalous non-Gaussian dispersion can emerge from pure mass-conserving convolutional chains without invoking fractional derivatives.

Weak dissipation can control wave propagation, mode competition, and instability thresholds in plasmas, yet the physical origin of large branch-to-branch differences in collisional damping is often obscured by dielectric-tensor calculations. We show that weak collisional damping in cold plasmas is governed by wave-energy partition. In the one-rate cold-plasma model, the damping rate of a collisionless eigenmode is exactly the collision frequency multiplied by the fraction of the total wave energy stored in plasma motion. This result recasts the standard perturbative damping formula into a compact and physically transparent law, immediately explaining why field-dominated branches such as whistlers can be much less damped than the collision frequency, whereas quasi-electrostatic modes can exhibit damping of comparable magnitude. Analytic examples for Langmuir, transverse electromagnetic, whistler, and extraordinary waves show that the energy-partition form classifies weak collisional damping across distinct branches and provides a simple diagnostic for mode competition in multibranch plasma-wave systems.

The phonon laser realized in a trapped ion, i.e., a self-sustained mechanical oscillator, has demonstrated the unique characteristics in practically detecting externally applied electric signals without the prerequisite of sideband cooling. Entering the quantum regime via sideband cooling is expected to further improve its sensing performance. Here we report the first experimental realization of a quantum-regime single-ion phonon laser ($\bar{n}<10$) using a trapped $^{40}\mathrm{Ca}^+$ ion and demonstrate electrometry based on its phase-space symmetry-breaking response to weak resonant electric fields. By tuning the phonon-laser parameters, we reveal that the sensing performance is fundamentally governed by the finite-time relaxation dynamics of the underlying open quantum system. We find that a slow Liouvillian relaxation, correlated with the finite experimental interaction window, effectively enhances the dynamic susceptibility while maintaining the structural robustness of the limit cycle. This regime, when applied to the detection of electric fields, produces a shot-noise-limited peak sensitivity of $14.15 \pm 0.77~\mu\mathrm{V/m}/\sqrt{\mathrm{Hz}}$ and a minimum detectable field variation of $\delta E_{\mathrm{min}} \approx 1.83~\mu\mathrm{V/m}$. Our results establish quantum phonon lasers as a practical platform for advanced sensing and highlight the central role of Liouvillian dynamics in non-equilibrium electrometry.

The invariant-imbedding T-matrix method (IITM) is a standard tool for light scattering by large, sharply faceted, non-axisymmetric particles (atmospheric ice crystals and mineral dust) where the surface-based extended boundary condition method loses accuracy. Its accuracy is limited by "staircasing": the dielectric contrast of a faceted particle is integrated across boundaries that cut the quadrature grid, so standard quadrature converges at low algebraic order. We show that this non-smoothness has a single geometric origin, the tangencies of the integration sphere to the faces and edges of the particle, which produce jumps, kinks, and half-integer branches according to the tangency type, in all three integration directions. A boundary-conformal scheme removes them using closed-form azimuthal coefficients, panel splitting at the analytically known tangency loci, and a square-root substitution $x \mapsto x_c + t^2$ that absorbs the half-integer branches. For a hexagonal prism the azimuthal integration becomes exact and the zenithal and radial directions recover spectral and fourth-order convergence; because the construction depends only on the contact geometry, it extends to any convex polyhedron, demonstrated on the solid hexagonal bullet (a faceted ice habit with tilted faces). The zenithal crossing is a square-root branch rather than a kink, so the established interval-splitting alone gives only $\mathcal{O}(N^{-3})$, while the radial step removes the half-integer edge branch that caps the Riccati recurrence on faceted particles. The convergence orders are fixed by the local contact geometry and verified size-independent up to $k\,r_{\max} = 20$; what grows with size is the resolution needed to reach each asymptotic regime, not the order.

Interfacial dynamics play a central role in transport processes across the plasma-liquid interface. While the strong electric field in the plasma sheath can destabilize the liquid surface and induce species transfer from the liquid into the plasma, the mechanistic relationship between surface instability and interfacial transport remains poorly understood. Here, we investigate the transport of sodium species in an atmospheric-pressure helium plasma in contact with a negatively DC-biased NaCl electrolyte using high-speed imaging, laser Mie scattering, and optical emission spectroscopy. The results show that Na transport is mediated by droplet emission from the liquid surface and proceeds through three sequential stages: surface deformation, Taylor cone formation, and electrospray. The threshold voltage required for Na I optical emission decreases with decreasing surface tension, in good agreement with the marginal condition for electrohydrodynamic (EHD) instability predicted by linear perturbation analysis. These findings demonstrate that EHD-driven droplet emission is the primary mechanism carrying sodium ions from the liquid into the plasma, where they are neutralized and excited. More broadly, this work establishes surface instability as the active transport channel governing the injection of dissolved species from the liquid into the plasma, creating a unique reaction network of plasma chemistry.

Nonlocal metasurfaces enable all-optical processing of spatial information in optical fields. Here, we demonstrate a topology-optimised metasurface that switches between phase-contrast and brightfield imaging modalities via polarisation control, eliminating the need to reposition optical components or use computational techniques to image transparent samples. Specifically, for one polarisation state, an asymmetric transfer function about normal incidence performs a first order derivative on the phase, producing pseudo-3D phase-contrast images of transparent biological samples while the orthogonal state returns the result of the identity operator. This work extends inverse-design methods to reconfigurable phase-contrast microscopy and quantitative analogue optical computation with applications in biological imaging, medical diagnostics, and materials characterisation.

Large-scale intermittency in the vertical velocity (LSI) has received significant attention in studies of coherent structures and their detection using data-driven approaches. However, a theory that predicts the origin of LSI from the Navier-Stokes equations or some approximated version of them at very high Reynolds numbers is yet to be achieved. This letter proposes such a theory for a neutrally stratified wall-bounded turbulent flow based on a dominant balance between inertial and pressure forces. Using multiple flume and wind tunnel experiments, it is shown that the flatness factor ($FF_w$) measuring LSI collapses to a universal trend for all flow configurations within the inertial sublayer (ISL) before reaching a common minimum value above the ISL. A theory that predicts $FF_w$ using second-order statistics and explicitly accommodates large-scale energy anisotropy is tested against a wide range of Reynolds numbers from laboratory to field settings with varied surface roughness conditions. The theory also demonstrates why $FF_w$ cannot be described using down-gradient closure approximations routinely employed in large-scale meteorological and climate models.

The Mpemba effect is commonly associated with anomalous thermal relaxation, in which a system prepared at a higher temperature reaches equilibrium faster than one prepared at a lower temperature. In modern formulations, however, its defining feature is broader: a state initially farther from equilibrium can relax faster than a closer one, or, equivalently, relaxation trajectories can cross. Here, we show that magnetic-field-dependent delayed fluorescence in triplet-fusion systems realizes a generalized Mpemba effect driven by external control of spin-selective kinetics. Using a diffusion-controlled geminate-recombination extension of the Johnson–Merrifield model, we demonstrate that delayed-fluorescence trajectories obtained at different magnetic fields cross when geminate fusion is effective. We further derive a compact kinetic criterion for such crossing in terms of the competition between intermediate-time decay rates and long-time power-law amplitudes. This criterion captures the interplay between effective fast and slow relaxation contributions. Within this kinetic framework, the final state is independent of the external control parameter and is defined as the fully relaxed state in which no separated triplet population remains. The generalized Mpemba effect therefore arises from the redistribution of transient relaxation pathways associated with geminate recombination, whereas bulk diffusion-controlled processes contribute only to the final relaxation. These results link anomalous relaxation in spin-dependent photokinetics to modern formulations of the generalized Mpemba effect and show how trajectory crossing can emerge in systems governed by diffusion-controlled geminate recombination and non-Markovian kinetics.

Chemical reaction networks (CRNs) are crucial for understanding reaction mechanisms and guiding chemical synthesis, yet the computational exploration remains limited by the combinatorial growth of chemical space, the reliability of reaction path screening, and the cost of evaluating thermodynamic and kinetic properties. Here, we present ByteCRN, an end-to-end framework for computational CRN exploration that combines chemically informed reaction enumeration with generative transition state modeling. A key component of our framework is a generative rectified flow architecture for both transition state generation and reaction validation, where it maps reactant-product pairs to candidate transition state structures and verifies connectivity by mapping back to reactants and products. This unified generative strategy replaces the most expensive steps of conventional computational workflows, namely iterative transition state search and intrinsic reaction coordinate validation, within a complete CRN construction pipeline. ByteCRN delivers a 10–100-fold acceleration over traditional workflows while maintaining high predictive fidelity for individual reactions. At the network scale, it effectively prunes $\sim$70-90% of the enumerated reactions, streamlining the exploration of complex reaction space. Its utility is illustrated through the discovery of novel pathways involving cyanoacetaldehyde and the successful modeling of the challenging $\gamma$-ketohydroperoxide network, demonstrating a practical, scalable approach to autonomous chemical exploration.

The two-birds-one-stone mineralization of CO2 by olivine, is a promising method to both capture carbon directly from the atmosphere and at the same time locking it for storage or utilization. Converting olivine to the nanoscale considerably enhances the kinetics without the need for high temperatures or pressures. Here we present the fabrication of olivine nanoparticles from a natural rock that were fabricated in a gas aggregation magnetron nanoparticle generator. The nanoparticle yield was optimized by enhancing the argon plasma sputter plasma by hydrogen introduction and varying the aggregation distance. The hysteresis of the argon sputter plasma with respect to power is a promising property towards energy efficiency. The formation of well-defined olivine nanoparticles and their subsequent absorption of atmospheric CO2 was confirmed by a suite of techniques. The olivine sputter target surface revealed an intricate interplay between the sputter plasma and olivine composition in terms of crystallinity and morphology. More broadly, this work forms the next step in the practical application of Olivine nanoparticles for economical carbon capture and storage, it also is the starting point for the use of this specific nanoparticle technology for mineral-to-nanoparticle conversion.

In recent times there has been growing interest in Raman optical activity (ROA) for its label free detection of absolute configuration, conformation, and stereochemical structure in chiral biosamples and drug molecules. Since ROA signals are generally small, techniques such as stimulation by a probe beam can be used to enhance the signal strength. However, with a classical probe, the measurement precision is still fundamentally limited by its shot noise. To solve this problem we propose the use of two-mode squeezed vacuum and show that it can achieve sub-shot noise limited measurement sensitivity. Using quantum estimation theory, we derived the quantum Fisher information and the quantum Cramér-Rao bound (QCRB) for stimulated ROA measurement to quantify the precision enhancement. This improvement comes from photon-number correlations which suppress the intensity fluctuation common to both modes. We further show that balanced detection of the output intensity difference is a practical measurement scheme that approaches the QCRB and becomes optimal in the small-chirality limit. This opens a promising path toward more sensitive Raman chiroptical spectroscopy of weak and photosensitive samples.

Individual daily mobility exhibits a striking scaling law: the probability of returning home after a tour of $l$ locations decays as $P_{\rm ret}(l)\sim l^{-\gamma}$. While the tour-terminate-continue (TTC) model reproduces this behavior, it relies on this power law as an empirical input, leaving the microscopic origin of $\gamma$ unresolved. Here we show that this scaling emerges from a utility trade-off governed by cognitive constraints. By invoking the principle of least effort, we demonstrate that individual activity priorities follow Zipf's law, $p(r)\sim r^{-\nu}$, which directly dictates the sublinear accumulation of tour utility, $U_L(l)\sim l^{1-\nu}$. Luce's choice rule then yields $P_{\rm ret}(l)\sim l^{-(1-\nu)}$, giving the exact exponent $\gamma = 1 - \nu$. Agent-based simulations confirm this analytical relation. Our framework bridges the gap between individual cognitive constraints and the scaling law of tour behavior, providing a microscopic theoretical underpinning for human mobility.

Many textbooks discuss the diamagnetic response of a “classical atom” to a small, adiabatically slowly applied magnetic field. Here we solve this problem for an arbitrarily large field. This gives a more satisfying justification for the assumptions made in the small field regime, explains the role of adiabaticity, identifies the symmetries persisting at large fields, and illustrates the range of applicability of the Larmor's theorem.

Noise sets the fundamental limits of resolution and sensitivity in Dynamic Atomic Force Microscopy (DAFM). While thermal fluctuations are conventionally assumed to be the dominant noise source, this work demonstrates that tip–sample interactions in ambient conditions introduce a non–thermal noise component that significantly exceeds the thermal background. Using a model system of sodium dodecyl sulfate (SDS) on graphite, we characterize this noise through force spectroscopy, 3D imaging modes, and Kelvin Probe Force Microscopy (KPFM). This interaction–induced noise arises from the stochastic formation and rupture of nanoscopic liquid necks, serving as a direct fingerprint of local wettability and dissipative dynamics. Crucially, we find that this “noise channel” provides chemical contrast that is distinct from and complementary to the electrostatic potential mapped by KPFM. By deciphering the physical origin of these fluctuations, we establish that noise is not merely an instrumental artifact but a rich spectroscopic signal, and we propose that Frequency Modulation (FM–DAFM) offers a superior approach to decouple these dissipative effects for high–resolution imaging.

This paper presents a modular S-/X-band shared-aperture phased-array antenna (SAPAA) for satellite-communication ground-station reception. The proposed architecture uses a repeatable unit cell that supports independent S- and X-band operation within the same physical aperture and enables arbitrary aperture scaling. Dual-polarized radiators are combined with calibrated complex receive coefficients to synthesize linear polarization (LP), right-hand circular polarization (RHCP), and left-hand circular polarization (LHCP). The design burden of the electrically large shared aperture is reduced by using theoretical estimates for scan matching and inter-band isolation before full shared-aperture verification. Simulated and measured results demonstrate axial ratios below 0.1 dB in the target S- and X-band receiving bands over a +/-50 deg scan range. The prototypes are validated using two approaches: passive measurements, where the element responses are measured individually, and RF system-on-chip-based active measurements, where all available receive channels are measured simultaneously. The results confirm that the proposed SAPAA provides wide-angle scanning, very high polarization purity, and polarization-reconfigurable operation for multi-mission SATCOM ground terminals.

We holographically generate optical modes associated with bipolar-coordinate solutions of the Helmholtz equation. Unlike conventional Gaussian beam families, these modes support multicenter phase discontinuities. We investigate and demonstrate that they support multicentered phase singularities, including optical dipoles and two-centered charge distributions. We further identify a family of conveyor-belt modes whose intensity structure follows an extended trajectory connecting the charge centers. Experimental generation using a spatial light modulator is presented and compared with theoretical predictions. These results establish bipolar-coordinate optical modes as a new class of structured light fields for singular optics, beam shaping, optical manipulation, and the controlled generation of multicentered topological structures.

Capable of capturing both bound and continuum quantum dynamics, Gaussian wavepackets are highly attractive basis functions for simulating laser-driven processes in atoms and molecules. Unfortunately, fully flexible Gaussian wavepackets are exceedingly challenging to propagate in a numerically stable manner within the framework of conventional time-dependent variational principles. In this chapter, we discuss the sources of the numerical issues and review an alternative approach, Rothe's method, that offers a route to improved numerical stability. Recent proof-of-concept simulations based on Rothe's method indicate that Gaussian wavepackets provide results on par with highly accurate grid-based methods for both electronic and rovibrational quantum dynamics, including ultrafast nonlinear processes that involve the continuum such as high-harmonic generation. Remarkably few Gaussian wavepackets are needed to achieve the high accuracy of grid-based approaches, indicating that further algorithmic developments and efficient implementations may enable efficient simulations of not only electronic and rovibrational phenomena but also fully coupled electronic-nuclear quantum dynamics with significantly reduced memory demands. We also point out remaining practical challenges, including matrix elements of the squared Hamiltonian and the treatment of Coulomb cusps.