Papers

Poorly soluble species can have mean populations below one in small systems such as nanopores. In this regime, the grand-potential minimum, which identifies the most probable particle number, differs from the ensemble-averaged solute loading. We use grand-canonical Wang-Landau sampling (GCWLS) to calculate the density of states $\Omega(N_\mathrm{A}, N_\mathrm{B})$ for a binary Lennard-Jones mixture of solute B in solvent A, both in bulk and in slit pores. One set of GCWLS simulations gives ensemble averages over a range of chemical potentials, whereas conventional grand-canonical Monte Carlo (GCMC) simulation requires a separate simulation at each state point. Independent GCMC simulations confirm the GCWLS ensemble averages. The solvent number distribution is nearly Gaussian, whereas the dilute solute distribution is skewed and Poisson-like. The most probable solute number therefore lies below the ensemble-averaged loading $\langle N_\mathrm{B}\rangle$ and is zero whenever $\langle N_\mathrm{B}\rangle<1$. Reading the solute loading from the grand-potential minimum underestimates it and can falsely indicate that no solute is present. Defining the oversolubility as $\mathcal{O}_\mathrm{B}=x_\mathrm{B}^{\mathrm{conf}}/x_\mathrm{B}^{\mathrm{bulk}}$, where $x_\mathrm{B}$ is the solute mole fraction, we find $\mathcal{O}_\mathrm{B}\approx12$ in a pore of 3.5 particle diameters width when both wall interactions are repulsive. Adding wall-solute attraction moderately raises it to $\approx13$, whereas wall-solvent attraction lowers it to $\approx3.4$. This comparison shows that the wall-solvent interaction controls most of the enhancement. As the pore widens, $\mathcal{O}_\mathrm{B}$ decreases toward unity. In bulk and in nanopores alike, the solubility of poorly soluble species should be obtained from ensemble averages rather than from grand-potential minima.

This study experimentally and theoretically investigates the electrically induced transition of a gas-focused liquid jet into a rim-emitting sheet. Ultra-high-speed imaging was used to examine the effects of applied voltage, gas and liquid flow rates, and liquid properties on sheet formation and breakup. Fully developed, quasi-stable sheets formed with ethanol, whereas isopropanol exhibited only initial sheet formation. Increasing voltage promoted sheet stretching, finer and more numerous rim jets, and a narrower spray. Higher gas flow rates shifted the transition towards the nozzle and produced finer structures, while higher liquid flow rates generated larger sheets with thicker rims. A first-order theoretical model assumes an equipotential interface and neglects finite charge relaxation, hydrodynamic perturbations, and nonlinear evolution. It balances destabilizing Maxwell-pressure perturbations against restoring capillary-pressure perturbations on a conducting cylindrical jet. The model identifies the elliptic azimuthal mode, m = 2, as the first unstable mode leading to sheet formation and predicts a critical electric Bond number of 3. Predicted onset voltages agree with measurements within 20%, and the threshold was consistent with published ramified-electrospray observations. The agreement with experiments supports electrocapillary symmetry breaking as the mechanism of onset and provides a compact, physically grounded criterion for predicting the transition from electrified jets to rim-emitting sheets.

This work investigates the incidence of rapid ice-loss events in the Arctic, in which a substantial fraction of September sea-ice is lost in only a few years. Such events are seen to occur in climate model simulations forced with increasing greenhouse gas concentrations, but not as yet in the relatively short observational record. We train a convolutional neural network (CNN) using six large climate model ensembles to diagnose vulnerability to rapid ice-loss events. The trained model is shown to separate higher and lower risk states in out-of-sample climate models via a leave-one-out cross-validation. The model emphasises the role of persistently thin sea-ice, remaining sea-ice extent and sustained high upper ocean heat content as predictors of rapid ice-loss. The CNN is applied to observational data over the satelite-era showing a signal for rapid ice-loss prior to a drop around 2007 and an increasing risk from around 2015 to present. Such rapid-ice loss events would likely have dramatic consequences for Arctic ecosystems, coastal communities and global shipping.

The Spin Physics Detector (SPD) experiment at the NICA collider of the Joint Institute for Nuclear Research (JINR) aims to study the spin structure of the nucleon and spin-related phenomena. The experimental conditions, including the high interaction rate and the large number of readout channels, require a triggerless data acquisition system with high throughput and a scalable architecture. This work presents a hardware implementation of the readout chain that extends the previously proposed SPD DAQ architecture. The chain is based on two levels of concentrators. The L1 concentrator provides the interface between the front-end electronics and the next system level and distributes synchronous signals. The L2 concentrator aggregates data streams from several L1 concentrators before transmitting them to the computing system. A key feature of the L2 implementation is the offloading of data reception, buffering, and aggregation from the host CPU to the FPGA, motivated by the large number of small packets generated by the readout electronics. The developed hardware platforms and their operating logic are presented, together with experimental results for the main interfaces and data-path components. The obtained results demonstrate the feasibility of the proposed hardware architecture and its application in a scalable SPD data acquisition system.

Terahertz time-domain spectroscopy records the electric field of terahertz transients and underpins applications from materials science to non-destructive testing. Asynchronous optical sampling enables systems without moving parts, but its acquisition rate remains fundamentally limited by the repetition-rate of the driving femtosecond lasers. Here, we demonstrate asynchronous terahertz-field sampling with two chip-based soliton microcombs. Their ultrahigh 25 GHz pulse repetition-rate drastically reduces dead-time during acquisition, and stabilization via sideband injection-locking enables coherent averaging without active feedback loops. At 10 kHz acquisition rate, we achieve a dynamic range of 74 dB in a single 100 $\mu$s scan, and 100 dB after 50 ms of coherent averaging with a 1.6 THz bandwidth. Acquisition rates of up to 100 kHz are demonstrated, limited only by detection electronics. Together with a proof-of-concept silicon wafer thickness measurement, these results establish soliton microcombs as compact sources for rapid terahertz-field sampling.

Silicon microring resonators are promising components for photonic reservoir computing because their nonlinear optical response can transform signals and retain information about recent inputs. Under constant optical excitation, their coupled free-carrier and thermal dynamics can generate self-pulsing: a periodic output response. However, constant-input behavior does not reveal how these dynamics respond to randomly modulated signals or whether their memory is useful for temporal processing. Here, we characterize a single silicon microring resonator and a passive network of microring resonators under random input modulation. The temporal component associated with self-pulsing remains observable under random modulation, but the largest fading memory occurs near the self-pulsing boundary, where no resolved self-pulsing-like oscillation is present. reservoir computing metrics, such as memory capacity, map this accessible memory, and its decay provides effective timescales associated mainly with free-carrier and thermal relaxation. Finally, we use NARMA reconstruction to test whether the measured memory profile supports nonlinear temporal processing. Responses with a resolved self-pulsing-like component perform worse on this task, and the intrinsic memory profile is not matched to the required input history. These results show that reservoir computing metrics can characterize nonlinear microring resonator dynamics even when the physical system is not an effective standalone reservoir for the selected task.

Ensemble forecasts from the ECMWF's Integrated Forecasting System (IFS) and the Artificial Intelligence Forecasting System (AIFS-ENS) are compared using a multi-dimensional evaluation framework. Within this framework, the uncertainty is interpreted as the linear subspace spanned by the ensemble members in phase space, from which various geometric properties are extracted. As revealed by the analysis, the error does not entirely lie in this subspace, but is reasonably well calibrated in all directions. Moreover, the framework allows to quantify that this subspace critically depends on the number of ensemble members, suggesting that the current setups only partially represent the uncertainty subspace. This phase-space interpretation furthermore allows a direct comparison of the error-representation patterns of AIFS-ENS and IFS by computing the principal angles between the subspaces: IFS and AIFS ensemble subspaces do not entirely overlap in phase space, even though they were shown to have similar abilities to represent the amplitude and the structure of the error.

We demonstrate that, in thermal atomic vapors, the electromagnetically-induced-transparency (EIT) transmission peak exhibits saturation. Investigating the amplitude of the velocity-selected double-resonance transmission peak-a purely kinematic effect arising from finite wavevector mismatch-we identify a threshold atomic column density Ns. For column densities N below Ns, the amplitude of the transmission peak maximum increases with column density. Once it exceeds Ns, the peak amplitude maximum remains constant, while the corresponding detuning shifts away from resonance and scales as the square root of ln(N over Ns). Furthermore, We find that the operating point for optimum photon-shot-noise-limited sensitivity deviates from that of the transmission peak maximum. Our study provides guidance for optimizing EIT readout in vapor cell and for precision measurements built upon this scheme.

Pedestrians in a crowd largely walk in small groups, dyads above all, and modelling how these groups arrange themselves is a step towards realistic models of the crowd as a whole. A dyad walks side by side in a dilute crowd and one behind the other in a dense one, an abreast to in-file transition recently measured in real life across the full range of naturally occurring crowd conditions (van der Laan and Corbetta, PLOS ONE 2026). The cost-function models of dyad formation by Zanlungo and coworkers (Phys. Rev. E 2014; EPL 2015) hold the pair abreast and have no in-file minimum at any finite density. Building on them, we propose and analyse a qualitative model in which the transition appears as an effective density parameter grows: the two formations become minima that coexist over a window of densities and exchange stability within it. We quantify this transition by computing the Orientation Log-Odds $\Pi_\text{OLO}$ as predicted by the model. This paper is a first step towards quantitative models of dyads and of their formation transitions.

The fingering instability of thin-film flow is a significant obstacle to producing uniform and stable films in industrial processes. In the framework of lubrication theory, we investigate the linear stability of a gravity-driven thin film with an inclined contact line using numerical and asymptotic methods. The contact-line singularity is regularized by imposing the Greenspan slip model. As demonstrated by the results, although the contact-line inclination slightly enhances long-wavelength instability, it significantly suppresses the growth of spanwise finite-wavelength perturbations. Moreover, the most unstable wavenumber shifts toward the long-wave region as the inclination angle increases. The inclination of the contact line introduces complex eigenvalues, leading to traveling-wave modes, in contrast to the standing-wave modes observed for horizontal contact lines. We also performed asymptotic analysis in the limit of small wavenumbers, confirming the enhanced long-wave instability. The physical mechanisms underlying these stability characteristics are elucidated, revealing that the effects of contact-line inclination come from the eigenmode distortion and additional streamwise flux.

The polarization state of light provides direct access to ultrafast electronic, magnetic, and structural dynamics in materials. Transient wide-field microscopy with simultaneous amplitude, phase, and polarization sensitivity enables spatially resolved measurements of these dynamics, but its sensitivity is often limited by technical noise and background fluctuations. Here, we demonstrate transient holographic full-polarization microscopy with substantially reduced instrumental noise and sensitivity approaching the shot-noise limit. We compare holographic geometries using one, two, and four reference beams and find that the single-reference configuration provides the most favourable shot-noise-limited sensitivity for the derived polarization observables. Combined with two-camera detection, it simultaneously captures both orthogonal polarization components without distributing reference photons among multiple carriers. A self-referenced noise-reduction framework combining singular value decomposition and background subtraction further suppresses correlated noise. For spatially averaged regions, the baseline noise is reduced by factors of three-sixty, enabling detection of weaker transient responses at lower excitation densities and in weakly absorbing materials.

This paper presents aeroelastic experiments conducted in the ONERA S3Ch transonic wind tunnel using a supercritical OAT15A airfoil mounted on a rig allowing independent control of pitch and heave degrees of freedom (DOF). The study investigates fluid-structure interaction (FSI) mechanisms and lock-in phenomena between transonic buffet and structural modes. Aerodynamic and structural responses were monitored using steady and unsteady pressure sensors, high-speed stereoscopic Particle Image Velocimetry (PIV), accelerometers, and optical sensors. Four configurations were tested: rigid (0 DOF), pitch-only (1 DOF pitch), heave-only (1 DOF heave), and combined pitch-heave (2 DOF). The test campaign spanned selected Mach numbers, angles of attack, and structural natural frequencies for each configuration. Results show that buffet-induced lock-in occurs abruptly when the Mach number increases, but only when the pitch DOF is enabled, in both the 1-DOF pitch or 2-DOF configuration. These findings establish that pitch-buffet frequency proximity is a necessary condition for lock-in. In the 2-DOF configuration, continuous Mach number excursions revealed a three-way coupling involving the buffet, pitch, and bending modes, with the bending mode modulating the coupled dynamics. This coupling generates large-amplitude limit-cycle oscillations (LCO) within seconds, persisting over a narrow Mach range before buffet cessation.

Adaptive search and travel strategies enable biological swimmers to explore complex environments, but remain difficult to encode in minimal synthetic microswimmers. Here, we unveil multiple dynamical and orientational states of rod-like Janus microswimmers actuated via electric fields: planar active, oriented chiral and persistent rods. We discover a hidden dynamical state after pre-orienting them, which allows us to switch on demand from strong chiral to persistent motion. We harness this phenomenological orientation and chirality switch for exploration in microstructured porous arrays. Here, strong chirality promotes local scanning but drives circular trapping and poor net displacement, whereas the pre-aligned dynamical state enables efficient obstacle sorting, and trap escape. Comparing experiments with simulations of active Brownian particles in the very same experimentally-extracted obstacle geometries, we quantify navigation efficiency via first-passage time statistics, revealing how chirality tuning optimizes the trade-off between local exploration and long-range transport.

Bubbly flows involve strongly coupled bubble motion, deformation, and hydrodynamic interactions, making high-fidelity simulation computationally expensive. We propose a neural surrogate that jointly predicts bubble trajectories and interface deformation in a compact, shared representation, replacing costly mesh-resolved simulation with fast generative inference. Because two-phase flow dynamics is nonlinear and chaotic, we treat forecasting as a conditional generative problem rather than deterministic regression, predicting entire future windows in a single pass. We train and evaluate the surrogate on BubbleSH, a Front-Tracking dataset of rising deformable bubble swarms, assessing performance using trajectory, shape, and distributional metrics over kinematic, morphological, and interaction-based properties. The surrogate reproduces key flow statistics while running several orders of magnitude faster than the underlying DNS solver.

Context: Solar magnetism exhibits long-term variations on timescales of decades to centuries. Aims: The main aim is to study how the supercriticality of the dynamo affects the variability of magnetic fields on timescales relevant to the Sun. Methods: Three-dimensional rotating magnetohydrodynamic simulations in a spherical wedge geometry are used to produce self-consistent convection-driven dynamos. The supercriticality of the dynamo is controlled by varying the magnetic diffusivity. Results: The main result is that long-term variability of the dynamo increases with decreasing supercriticality of the dynamo and that cases nearest to the onset of dynamo action show extended grand minima-like periods of low activity. The simulations fall in three classes where the least supercritical cases show the largest variations of magnetic activity and where the flow including differential rotation is almost unaffected by the magnetic field. In the cases with the highest supercriticality the magnetic field is permanently strong and differential rotation permanently quenched, both having relatively little temporal variation. In an intermediate regime both the magnetic fields and differential rotation exhibit strong anticorrelated fluctuations. Conclusions: The occurrence of grand minima in the Sun has been conjectured to be due to a weakly supercritical dynamo. The current results support this idea and suggest that the absence of grand minima in earlier global dynamo simulations is because their large-scale dynamos were too supercritical. Furthermore, the current results suggest that the effect of the magnetic field on differential rotation is negligible if the average rms-field is less than about 2~kG.

We formulate an axisymmetric spherical torus (ST) six-component magnetofluid equilibrium model for p_11B plasmas composed of thermal and suprathermal proton, boron, and electron fluids. The model is designed for p_11B parameter regimes where ion energies, strong current drive, energetic electron populations, and ion-electron temperature separation can render a single_fluid static_equilibrium description inadequate. It generalizes rotating_plasma equilibrium theory by incorporating relativistic thermal enthalpy corrections to the electron fluids via h(T/m_ec^2) and by constructing modified flux functions Y_{\alpha} associated with canonical angular momentum for each component {\alpha}. The equilibrium is determined by a Grad-Shafranov-like Ampere law for the poloidal magnetic flux Psi, algebraic density relations constrained by quasineutrality, and prescribed profile functions F_{\alpha}(Y_{\alpha}), T_{\alpha}(Y_{\alpha}) and K_{\alpha}(Y_{\alpha}). The manuscript includes the relativistic magnetofluid equations, the axisymmetric equilibrium formulation, the six_fluid computational method, and four numerical equilibria: two reactor_relevant ST p_11B parameter sets and two EHL-2 ST cases. The examples span toroidal beta b_T = 0.058_0.253, plasma currents I_p = 2.697_12.59 MA, and suprathermal electron temperatures T_eh = 287 keV_2.37 MeV, with h up to 19.1. Over these parameter ranges, Ampere's law accuracy, electrostatic potential accuracy, and component_resolved radial force balance can have errors ranging from 3% to below 0.1%. These results indicate that high-temperature p_11B ST equilibria can differ qualitatively from the single_fluid tokamak equilibria and require analysis of equilibrium component_resolved force balance, relativistic electron enthalpy, and explicit reproducibility diagnostics.

We investigate the computational capabilities of a one-dimensional lattice of negatively coupled circle maps in its traveling wave regime. We interpret propagating waves as information carriers and exploit their interactions to implement Boolean logic. The logical states are encoded by the propagation direction of the traveling waves, while the presence or absence of a wave at a designated output location represents the logical output. Using controlled wave collisions, we demonstrate the realization of NAND and NOR gates along with other basic gates. Since NAND and NOR operations are functionally complete, the results establish that the traveling wave regime of the negatively coupled circle-map lattice supports universal Boolean computation in principle. The demonstrated logical operations remain valid over a finite range of the coupling strength \epsilon and map parameter \omega, indicating robustness of the computational scheme to parameter variations. Our results therefore demonstrate that computational functionality can emerge from the collective nonlinear dynamics of a coupled map lattice, providing a con- nection between the dynamical properties of traveling wave states and collision based information processing.

Quantum random number generators are crucial for information security, yet existing implementations are hindered by bulky optics, device imperfections, and state alignment constraints. Here, using a compact metasurface platform, we achieve polarization-independent certified randomness by establishing a quantitative quantum graph framework. By mapping multi-channel nanophotonic responses onto graph vertices, we assign metasurface measurements an operational information-theoretic meaning, directly connecting weighted graph degrees to conditional min-entropy estimation. The resulting graph-certified measurements yield robust private randomness even under entanglement-based attacks without complex optics. Experimentally, we fabricate 4- and 6-channel dielectric metasurfaces to implement high-dimensional positive operator-valued measure graphs, successfully certifying randomness with heralded single photons and Poissonian light. By integrating complex quantum measurements into a single passive layer, our metasurface quantum graphs provide a scalable route for integrated quantum technologies.

We have developed an apparatus for the measurement of the acousto-electric effect (AEE) from room temperature to liquid nitrogen temperatures. The AEE is excited by bulk acoustic waves (BAWs) for which a lithium niobate piezoelectric actuator is employed. A very low background noise level is realized through careful electrical and mechanical design of the setup. The validity of the setup is tested by measuring the AEE in heavily doped P-type and N-type silicon. The opposite sign of the AEE signal was seen for both samples, showing dependence of the signal on the type of charge carrier being dragged by acoustic waves. The signal showed quadratic dependence on the driving voltage, which is consistent with the AEE literature. Further, a temperature dependence of the AEE signal was measured, which exhibits a monotonic increase with a rise in temperature. The ability to probe the AEE in bulk samples at low temperatures makes this setup a promising tool to investigate the AEE and related phenomena in different materials at cryogenic temperatures.

High-density plasma discharges in hydrogen operating at low pressures are of considerable interest for negative ion production used in many applications. Their weak collisionality requires a kinetic, nonlocal description, and a popular approach is to model such discharges numerically using the particle-in-cell (PIC) method combined with Monte Carlo collisions (MCC). However, the most commonly used explicit momentumconserving variant of this method is highly inefficient because it must resolve both the Debye length and the plasma period. In this context, the implicit energy-conserving PIC/MCC scheme appears to be an attractive alternative, as it can model the plasmas of interest using their actual parameters without resorting to artificial scaling techniques. This work considers simulations of two types of high-density plasma discharges performed using electromagnetic or electrostatic energy-conserving PIC/MCC codes in hydrogen, and discusses the observed negative ion production.

Providing more coherent light with space-time coupling offers unprecedented opportunities across diverse scientific disciplines and areas of technology. However, in many applications, tailored laser beams with partial coherence in space and time are desired. Here, we demonstrate a programmable approach for simultaneously shaping the intensity and coherence distributions of spatiotemporally coupled partially coherent wave packets. By jointly engineering the fractal speckle of a dynamic scatterer and applying tailored modulation of the illumination function, we experimentally generate partially coherent laser beams with arbitrarily designed intensity and nontrivial coherence distributions. The proposed approach is compatible with ultrafast laser pulses, enabling the on-demand generation of partially coherent space-time wave packets. The resulting spatiotemporally partially coherent wave packets exhibit non-separable space-time intensity profiles together with engineered spatiotemporal correlation distributions. This work provides a versatile framework for tailoring partially coherent light in space and time, with varied applications in relativistic laser-matter interaction, passive imaging and optical manipulation.

Morphogenesis is driven by the interplay of genetic regulation and tissue mechanics. In vivo video data is limited, particularly under genetic mutations and environmental perturbations, making generalization beyond the most representative conditions in the dataset challenging. However, at tissue scales, the dynamics of Drosophila can be described as a continuum flow, motivating the usage of representations learned across other physical systems as priors for developmental dynamics. We investigate finetuning Walrus, a Continuum Dynamics Foundation Model pretrained across a broad set of simulated continuous systems, on tissue velocity fields from only 12 wild-type Drosophila blastoderm videos. We evaluate autoregressive prediction both in-distribution and zero-shot under unseen temperature and genetic perturbations. Zero-shot refers to evaluation on perturbation conditions never seen during wild-type finetuning, without any additional training. In-distribution, a Fourier Neural Operator model trained from scratch achieves best performance on VRMSE. However, Walrus (CRPS) is the strongest model under the most severe distribution shift of unseen samples of mutated embryos and temperature conditions. Interestingly, predictions capture the shape of the mean surface tissue velocity trajectory and its separation between 17{\deg}C and 27{\deg}C, including the timing of the peak at Germ Band Extension onset, a biologically meaningful milestone of embryo development. Our results provide preliminary support that representations learned from different dynamical systems can transfer to experimental morphogenesis in developmental regimes, provided they admit a continuum description. More broadly, our results motivate further study of physics foundation models as a new complementary tool for the simulation of morphogenesis in low-data regimes.

A ghost-cell immersed boundary method is proposed for the two-dimensional shallow water equations with a variable bed (topography), solved with an explicit Godunov-type finite volume scheme (unsplit second-order MUSCL, HLLC flux, hydrostatic reconstruction) on Cartesian grids. Ghost-cell methods leak mass through the wall. To find a robust and conservative treatment, eight constructions of the ghost values and a cut-cell form of the continuity equation were applied to seven test problems, which include wetting and drying on sloping beds and a laboratory dam break. In the resulting scheme, the ghost values are interpolated bilinearly at the image point; solid and dry nodes are excluded, and the weights of the remaining nodes are renormalized. Mass is conserved by solving the continuity equation in cut-cell form, while the momentum equations are left unchanged. The proposed scheme is about as accurate as the ghost-cell method without this modification and preserves a lake at rest whose shoreline crosses an immersed wall. Because only the continuity equation is modified, it avoids the treatment of the momentum equations on cut cells (wall pressure, cell merging) that a full cut-cell method requires.

Aim. We try to understand the interaction of eccentricity tide and convection in icy satellites. Method. We use the numerical calculation of rotating convection with eccentricity tide in a spherical shell. Results. We have the following results. (1) Energy scaling exponent about buoyancy force (or tidal force) decreases with increasing tidal force (or buoyancy force). (2) The combined tide-convection flow is not identical to superposition of two pure flows in respect of energy spectrum. (3) Tide controls large-scale of fluid motion but convection is important for small scale, and the mode-mode transition occurs at intermediate scales. (4) Tide suppresses heat transport efficiency. (5) Dissipation of kinetic energy scales as square of tidal force with a very weak dependence on buoyancy force, which has little impact on dissipation but suppresses the tidal influence on dissipation.

Prestack seismic inversion often suffers from inherent ill-posedness and is significantly affected by complex factors such as the wavelets, parameter coupling, heterogeneous media, fault displacements, and stratigraphic variations, making it difficult for the conventional inversion methods to accurately recover subsurface information. To address these challenges, this paper proposes a global inversion method based on multi-dimensional matrix multiplication to optimize the inversion results under structure constraints. This method first represents the inversion model as a four-dimensional tensor representing spatial and parameter dimensions. By performing multi-dimensional matrix multiplication operations in various directions of the model, a multi-dimensional tensor of observed data is effectively constructed. Secondly, multi-dimensional regularization are introduced. By analyzing the impact of different dimensional constraints on the inversion results, targeted parameter selection and adjustment are achieved, significantly enhancing the stability of the inversion process and effectively suppressing noise. Finally, stratigraphic and fault constraints extracted from seismic interpretation are incorporated to improve the geological coherence and reasonableness of the inversion results. Both synthetic and field data experiments demonstrate that the proposed method effectively enhances the robustness of inversion in complex structural areas while maintaining high computational efficiency, validating its effectiveness in practical applications.

Strong-field physics uses intense optical fields to probe and control electron motion on ultrafast timescales. Recent advances in bright squeezed vacuum have brought macroscopic quantum states of light into the ultrafast strong-field regime, opening prospects for high-harmonic generation and photoionization. Yet linking its phase-space structure to subcycle electron dynamics remains challenging. Here, we demonstrate strong-field tunneling ionization of xenon using a phase-referenced combination of coherent and squeezed fields, with the coherent field defining the ionization clock and quadrature fluctuations of the zero-mean squeezed field providing control. The squeezed field selectively modulates atomic tunneling barriers and electron wave packets, imprinting signatures on photoelectron momentum distributions, number statistics, and energy spectra. Using coincidence measurements of photon number and phase-sensitive photoelectron momentum distributions, we perform quantum state tomography of the driving field by reconstructing its Wigner function. These results establish a bidirectional interface between quantum optics and nonperturbative strong-field electron dynamics, in which the driving quantum field shapes subcycle electron motion while photoionization provides a phase-sensitive probe of the field's quantum state. This work opens new routes toward controlling electron dynamics with quantum light and phase-sensitive quantum state metrology through ultrafast strong-field electron dynamics.

Small particles respond to light through electric and magnetic patterns called multipoles. Their interference determines the direction of scattered light and affects the decay of nearby emitters. Larger nanoantenna arrays, metasurfaces, and other nanophotonic systems demand increasingly costly simulations to meet strict performance and reliability requirements. We show how to represent these responses with quantum bits (qubits) and use quantum circuits to calculate scattering and the Purcell effect, the change in an emitter's decay rate caused by its surroundings. The circuits can encode known multipoles or estimate unknown ones from Maxwell's equations at the particle surface. We test the method against classical theory using an ideal quantum simulator and real IBM and IonQ quantum computers. For a silicon nanoparticle of radius 78 nm illuminated at 679 nm, IonQ gives a forward directivity of 2.984, close to the ideal dipolar value 3, quantifying the concentration of scattered light in the forward direction. For an emitter 10 nm from a gold nanoparticle and emitting at 510 nm, IBM measurements yield a calculated total decay rate 20.48 times its vacuum value versus 20.47 from theory, with correction for errors in reading the qubit states. We also establish how the number of multipoles and the required accuracy set the demands on qubits and measurements. These results motivate quantum-assisted design studies of directional radiation and emitter decay in nanophotonic systems.

Some voters conceal their opinions, causing a mismatch between visible and private opinions in polls. Conventional voter models do not account for such concealment. Here, we introduce a shy voter model that incorporates a hidden state in addition to two visible states, as an extension of the conventional majority-rule voter model. The model exhibits continuous and hybrid transitions, yielding a rich phase diagram organized by the hidden fraction, i.e., the fraction of voters in the hidden state. For a large hidden fraction, the system undergoes a hybrid transition from the ordered state to the symmetric (disordered) state, whereas for a small hidden fraction, it exhibits a continuous transition, with a tricritical point separating the two regimes. Near criticality, both the order-parameter variance and the susceptibility diverge. The hidden fraction also governs the entropy flux, a quantity that is not directly observable in real-world situations. Thus, opinion concealment qualitatively reshapes opinion dynamics, while the present framework provides a basis for further extensions toward more realistic forms of social interactions.

The results from [Fluid Dyn 61, 20 (2026)], concerning the generalized Chapman-Enskog method and a nonlocal (i.e., non-diffusive, spatially integral) viscous stress tensor in the Navier-Stokes equation, are extended to the case of arbitrary gradients of not only hydrodynamic velocity but also temperature. The resulting equations simplify the description of tangential discontinuities and separated flows. For the specific case of an incompressible medium, a nonlocal vorticity transport equation is derived that is structurally identical to the Biberman-Holstein equation for resonant radiation transport in plasmas and gases. A power-law form has been determined for the velocity distribution function of long-free-path vorticity carriers that satisfies empirical Richardson t^3 law for the mean square of relative separation of a pair of particles in a turbulent liquid or gaseous medium.

We present two and three dimensional direct numerical simulations of planar intrusions injected from a continuously supplied, narrow source into a linearly stratified ambient at the level of neutral buoyancy. The evolution passes through three phases. A laminar leading vortex dipole first advances at constant speed with a varicose wave train behind it; the trailing jet then undergoes a sinuous instability whose initial growth rate and wavelength agree with inviscid unstratified planar-jet theory evaluated on the local jet; the flow finally relaxes into a buoyancy-controlled wedge whose area grows linearly in time. Three-dimensional simulations show that the transition remains organized by the planar instability, while three-dimensionality reshapes the near-source region into a slowly evolving, actively mixing zone that entrains an additional twenty to one hundred percent of the source flux depending on source width. Rescaled with this measured effective flux, the downstream intrusion collapses reasonably well onto the similarity solution for a wide-source intrusion.