Papers

Atmospheric ion escape driven by the solar wind is a key process controlling the long-term loss of the Martian atmosphere. Localized plasma clouds can carry substantial fluxes of planetary ions away from Mars, representing episodes of bulk escape. However, their origin has remained unclear due to the absence of simultaneous upstream measurements. Using joint observations from the MAVEN and Tianwen-1 missions, which provide real-time upstream monitoring, we present direct evidence that these plasma clouds are nonlinear wave packets generated by the Kelvin-Helmholtz instability (KHI). The spatial scale of KH waves is constrained for the first time via two-point measurements. Ion fluxes within plasma clouds are one to two orders of magnitude higher than those in typical steady-state escape channels. Our results indicate that KHI is an important process for solar wind coupling to planetary upper atmospheres and plays a crucial role in shaping atmospheric ion escape for unmagnetized planets.

We report the design, modeling, and on-wafer characterization of a photoconductive heterodyne mixer implemented as a true terahertz monolithic integrated circuit (TMIC). Unlike previous photoconductive heterodyne demonstrations, the proposed circuit is characterized using RF integrated circuit metrics including input return loss, RF/IF isolation, broadband impedance matching, and conversion loss. The mixer combines a microcavity photoconductor with a broadband coplanar matching network incorporating a Ti shunt resistor, an RF DC-blocking MIM capacitor, and an RF/IF decoupling capacitor. A circuit-level model including both the photoconductor and the distributed CPW accesses is developed and validated. The passive circuit is experimentally characterized up to 500 GHz using on-wafer VNA measurements and accurately reproduced by simulation. Under illumination, the model predicts an input reflection coefficient below -10 dB up to 215 GHz and better than -6.5 dB up to 500 GHz. Measured and simulated conversion losses agree within +/-1 dB over the entire 1-500 GHz range. Conversion loss varies from 22.5-25.5 dB below 320 GHz and 26-34 dB up to 500 GHz. The proposed TMIC demonstrates broadband operation and provides a validated circuit design methodology for future integrated THz photonic mixers.

Layered and periodically patterned heterostructures underpin advanced optical, photonic, and plasmonic (meta)materials, whose rational design demands electromagnetic solvers that are both numerically robust and tightly linked to the underlying material properties. Here, we present AFLOW-EMERALD (ElectroMagnetic modes EngineeRing in Advanced LayereD materials), an open-source, modular, Python-based computational framework for simulating electromagnetic wave propagation in finite and periodic layered (meta)materials. Built around a unified object-oriented architecture, AFLOW-EMERALD combines a numerically stable scattering-matrix method with plane-wave expansion and extends to rigorous coupled-wave analysis for laterally patterned structures such as gratings. The software computes optical spectra, spatial field distributions, and photonic band structures, including complex-k dispersion in lossy, dispersive media. A streamlined YAML workflow allows users to seamlessly import dielectric function datasets from experimental, literature, or first-principles sources. Owing to its modular design, AFLOW-EMERALD is readily extensible and suitable for integration into computational materials-design pipelines, providing a practical platform for the coupled material-geometry engineering of dielectric photonic crystals, plasmonic multilayers, hyperbolic metamaterials, and more complex architectures supporting, e.g., surface and volume plasmon-polariton modes.

Signal fading creates points along the fiber where phase cannot be extracted, so they are conventionally discarded. Instead, we propose a Kalman-based solution for {\phi}-OTDR full-fiber monitoring. Experiments demonstrate phase and temperature estimation with approximately 15 times better spatial density than if removing these points.

Predicting the transition of wind-forced, gravito-capillary surface waves from smooth to corrugated states remains a longstanding problem in nonlinear surface wave mechanics. Solving driven-dissipative, nonlinear potential flow equations we map these waves ($4-13$ cm) onto a Reynolds number – wave energy phase-space. We identify a transition band separating smooth from corrugated wave states - the wave steepness exhibits a non-monotonic dependence on Reynolds number within this. Subharmonic (in)stability analysis reveals that the fastest-growing mode intensifies corrugations on alternate faces of the carrier wave. Our results offer insights into parasitic capillary wave formation on steep carrier waves and are of interest to ocean remote-sensing.

The quality of multi-scale modelling techniques in molecular electronic structure calculations, such as embedding and subspace methods, relies upon the chosen active space. The automation of active space selection is vital for ensuring the accuracy, reproducibility, and scalability in such calculations. In this work, we introduce Tensor Network Active Space Selection using the Entanglement Feature. Through the isolation of strongly correlated electrons, this method provides a scalable foundation for embedding methods in multi-scale modelling. By representing the purities of all possible orbital partitions as a Matrix Product State, our method isolates regions of strong electron correlation without requiring manual preselection of target atoms or the calculation of expensive high-order density matrices. The results demonstrate that this approach leads to lower ground state energies and more accurate dipole moments than other fully automated selection schemes such as those based solely on single-orbital entropy or the selection of spatial orbitals around the HOMO/LUMO gap.

This work introduces a robust deterministic framework for approximating solutions of the Boltzmann equation with binary collisions by discretizing their dependence on time, position, and velocity using Galerkin methods. By employing a family of parametric Galerkin closures based on $\varphi$-divergences in velocity space, we derive rigorous hierarchies of moment equations that govern fluid dynamic variables. Addressing the limitation that these closures alone do not guarantee dissipation of a $\varphi$-divergence entropy for the true binary collision operator, we restore this property by formulating a compatible approximate collision operator tailored to each closure. This constructed operator intrinsically retains fundamental physical properties essential for high-fidelity flow simulations, including Galilean invariance, exact conservation of mass, momentum, and energy, and strict dissipation of a $\varphi$-divergence entropy. Furthermore, we show that the resulting closed moment systems are symmetric-dissipative, yielding Cauchy problems that are well-posed locally in time. To translate this mathematical foundation into an efficient computational tool, we discretize the position and time variables with an entropy-stable discontinuous Galerkin (DG) finite element method. The fully implicit, entropy-stable space-time approach enables time steps far beyond typical CFL-limited step sizes and the direct computation of steady states. The robustness and accuracy of the methodology are verified and validated through numerical simulations on the supersonic nozzle flow of argon, mass flow through a channel, and heat transfer between parallel walls, demonstrating agreement with analytical benchmarks, experimental measurements, and stochastic particle simulations.

A three-dimensional (3-D) hybrid numerical method (HNM) is presented for electromagnetic scattering in structures with multiple inhomogeneous layered media coupled to an arbitrary 3-D non-layered scattering region. It integrates the 3-D numerical mode-matching (NMM) method with a tree-cotree-based mixed finite element method (MFEM). In the NMM, the fields in the 3-D layered media are reduced to a superposition of 2-D waveguide eigenmodes, while the MFEM discretizes the 3-D scattering region. The HNM thus inherits the dimensionality-reduction advantages of both conventional hybrid MM/FEM and pure NMM. Numerical experiments show that the HNM provides an effcient alternative for scattering problems involving non-layered regions embedded in layered media.

The integration of thermoelectric devices into mainstream microelectronic technological platform could be a major breakthrough in various fields within the so-called Green-IT realm. In this article, the thermoelectric properties of heteroepitaxial SiGeSn alloys, a novel CMOS compatible material system, are evaluated to assess their possible application in thermoelectric devices. To this purpose, starting from the experimentally low lattice thermal conductivity of SiGeSn/Ge/Si layers of about $\sim$1-2 W/m$\cdot$K assessed by means of 3-$\omega$ measurements, the figure of merits are calculated through the use of Boltzmann transport equation, taking into account the relevant inter-valley scattering processes, peculiar of this multi-valley material system. Values for the figure of merit $ZT$ exceeding $1$ have been obtained for both p- and n- type material at operating temperatures within the 300—400 K range, i.e. at a typical On-Chip temperatures. In this interval, the predicted power factor also features very competitive values of the order of 20 $\rm{\mu W/cm\cdot K^2}$. Our finding indicates that this new class of Si-based materials has extremely good prospects for real-world applications, and can further stimulate scientific investigation in this ambit.

We study seven major crypto-perpetual liquidation cascades (2022-2025), and in the largest of them we can watch the mechanism directly. From the on-chain fill log of a fully transparent venue we measure the branching ratio of that event – the October 2025 crash, the largest on record – in flight, with both of its factors observed and no free constants. It ran deeply subcritical: the structural ratio and the amplification bookkeeping both place it at $\hat\lambda \approx 0.1-0.2$ throughout, while a third, flow-based estimator falls through the climax rather than rising. All three agree on subcriticality within the venue, not on a common numerical level. Alongside them, 88% of all post-onset forced selling landed within thirty minutes and 63% of it was absorbed off-book by the venue's backstop, which drives the branching ratio down precisely at the climax. Across the full set of seven, at onset – the minute ending the steepest hour of each crash – the order parameter (mean inter-asset coupling) jumps by between 1.6 and 4.4 baseline standard deviations into a near-fully-ordered phase, while the susceptibility proxy $\chi$ collapses in five of the seven events and diverges in none; the jump is invariant under subsampling. The transition is abrupt and scale-robust rather than critical, and its in-cascade signature lives in the liquidity sector: price impact spikes on two venues and two instruments while open interest clears by 25-70%. The natural mechanistic account, a Galton-Watson cascade with $\lambda = k \tilde\rho$, is then eliminated as a description of the pre-cascade state: both of its falsifiable predictions fail at simulated power >= 0.96, on proxied and on directly measured regressors alike. Severity is set by shock times map-in-path times liquidity withdrawal rather than by a diverging multiplier, which is why none of the scalar pre-state measures we can construct grades it.

Efficient simulation of nonlinear light propagation in complex photonic structures remains a major challenge because these systems combine intricate transverse geometries with propagation over distances spanning many diffraction lengths. Existing numerical methods often require computationally intensive uniform discretizations or struggle to accurately represent complex material boundaries, limiting the practical simulation of multiscale nonlinear photonic devices. Here we introduce a computational framework for solving the nonlinear Schrödinger equation that accelerates simulations by more than two orders of magnitude (over 100x) compared with conventional approaches while maintaining spectral-level accuracy, thereby reducing the computational time required to solve large-scale and multiscale problems from days to hours. The method is based on discrete exterior calculus, enabling geometry-conforming discretization directly on unstructured meshes without the weak formulations required by conventional finite-element methods. In contrast to Fourier-based spectral solvers, it avoids global oversampling, eliminates Gibbs-type oscillations at material interfaces, naturally incorporates absorbing boundary conditions, and preserves the topological structure of the underlying differential operators. A key feature of the framework is that higher-order propagation operators are generated algorithmically from lower-order discrete operators, providing a systematic route to extending simulations beyond the standard nonlinear Schrödinger equation. Benchmarks on fundamental solitons, asymmetric beams, and optical vortices confirm spectral-level accuracy while demonstrating computational speedups exceeding 100x.

This study investigates the generation and enhancement of quantum entanglement in an electro-optomechanical ring cavity system. The setup integrates two Coulomb-coupled mechanical resonators, which serve as the fundamental mechanism for the generation of bipartite and tripartite entanglement via charge mediated coupling. We then demonstrate the significant enhancement of this entanglement via a nonlinear parametric drive (an optical parametric amplifier, OPA), which injects a controllable nonlinearity into the cavity. We derive the system's Hamiltonian and the corresponding quantum Langevin equations, which are linearized around steady-state solutions to analyze Gaussian quantum fluctuations. Employing the covariance matrix formalism, we quantify bipartite entanglement via logarithmic negativity and tripartite entanglement via the minimum residual contangle. Our results unequivocally show that while the Coulomb interaction is indispensable for creating entanglement, the OPA acts as a powerful control tool, dramatically amplifying the degree of quantum correlations for all subsystems. We find that the strength of entanglement is highly sensitive to several parameters and can be optimized through the strategic selection of the OPA's gain and phase, the laser detuning, and the input power. A key finding is the existence of a trade-off, where parameters that maximize entanglement also constrain the stable operating regime of the system. Furthermore, thermal noise is shown to progressively degrade all quantum correlations, underscoring the necessity for low-temperature operation. These findings provide comprehensive guidance for parameter optimization, outlining a clear path from generation to enhancement, and highlight the potential of such hybrid systems as versatile platforms for controlling multipartite entanglement in quantum technologies.

High-power laser sources that exhibit low relative intensity noise and allow simultaneous dynamic control of their light level are required for a broad range of applications in various fields of physics. Acousto-optic modulators (AOMs) are widely used for active power stabilization and regulation due to their simple drive electronics requirements and high optical power handling capability in free-space. However, the rather slow propagation speed of the sound wave within the AOM crystal typically limits their control bandwidth to a few hundred kHz. In this work, we present a novel AOM-based control system that is capable of significantly suppressing intensity noise of high-power lasers up to the MHz range. By combining two standard feedback loops with one feedforward control branch and optimizing the beam path in the AOM crystal, ultra-low relative intensity noise levels down to $-155\, \text{dB}\,\text{Hz}^{-1}$ even at several hundred kHz are achieved. Our results are relevant for applications that require ultra-low intensity noise at Fourier frequencies up to the MHz range, such as optical lattice experiments with light ultracold atoms.

This paper investigates the numerical initialization of the one-dimensional Maxwell–Cattaneo–Vernotte (MCV) heat conduction model, addressing the critical mathematical challenge of defining the initial time derivative for non-equilibrium states. In modern high-frequency thermal engineering applications, traditional time-integration schemes and commercial finite-element solvers frequently introduce severe numerical artifacts when handling non-Fourier models. This study systematically evaluates three initialization strategies: a zero derivative, a spatially uniform non-zero derivative, and an exact space-dependent derivative. Using an explicit staggered finite-difference scheme, the transient responses to an exponentially distributed initial temperature field under adiabatic boundary conditions are compared against an analytical solution using the Galerkin method. The results demonstrate that assuming a zero or spatially uniform initial derivative introduces significant unphysical oscillatory deviations, leading to heat-flux prediction errors as the relaxation time increases. Conversely, mapping the exact space-dependent derivative onto the staggered grid preserves the local thermodynamic structure of the initial state, yielding robust transient responses that match the analytical benchmark without meaningful computational overhead. These findings establish a thermodynamically consistent initialization technique that can be extended to non-local models as well.

Higher-order network datasets are dispersed across publications, institutional archives, and software-specific collections, making them difficult to discover, compare, and reuse. We introduce the Aachen Higher-Order Repository of Networks (AHORN), a curated repository of standardized higher-order network datasets derived from publicly released sources. Each dataset entry links a converted dataset to its source, metadata, citation guidance, conversion code, and version history. The repository supports browsable and machine-readable discovery, revision-specific downloads, format validation, and exports for interoperable reuse. We describe the repository architecture, curation workflow, access tools, and the coverage and limitations of the catalog snapshot analyzed in this article.

Self-mixing interferometry is a measurement ap- proach in which a laser beam is re-injected into the emitting laser itself after reflection on a target. Information about the position of the target can be obtained from monitoring the voltage across the laser. However, analyzing this signal is difficult. In previous works, neural networks have been used with great success to process this data. In this article, we present an updated prototype of an integrated sensor based on self-mixing interferometry with embedded neural networks. It consists of a semiconductor laser (acting both as light emitter and detector) equipped with an embedded platform for data processing. The platform includes an ADC (Analog-to-Digital Converter) and an STM32U575ZI microcontroller. The microcontroller runs a residual neural network in charge of reconstructing the displacement of a target from the interferometric signal entering the ADC. We assess the robustness of the neural network to unwanted signal amplitude variations, the impact of different network weights quantization choices required to run the network on the microcontroller, and the energy consumption of the system. Finally, we provide a demonstration of target displacement reconstruction fully running on the embedded platform in real-time. Our results pave the way towards robust, low power and versatile sensors based on self-mixing interferometry and embedded neural networks.

Stochastic Differential Equations (SDEs) have become a cornerstone of scientific machine learning, though they are predominantly utilized as algorithmic tools for uncertainty quantification or distribution matching. In contrast, leveraging SDEs fundamentally to model macroscopic, nonlinear physics as stochastic processes remains largely unexplored. This work introduces a probabilistic, non-intrusive reduced-order model (ROM) for chaotic dynamical systems. We argue that projecting high-dimensional nonlinear dynamics onto a low-dimensional manifold introduces irreducible uncertainty, compounded by the chaotic attractors and multi-admissible futures inherent to turbulent flows. Consequently, a chaotic system governed by a partial differential equation can be effectively modeled by an SDE in a suitable latent space. To this end, a nonlinear autoencoder is employed to map the flow field into a low-dimensional representation, within which the temporal evolution is explicitly governed by an SDE. The predictable component of the dynamics is captured by a learned drift term, while state-dependent stochasticity is absorbed by a diffusion term. We demonstrate that this probabilistic framework successfully propagates highly nonlinear states, offering a robust alternative to traditional deterministic methodologies for chaotic regimes. Ultimately, our model generates new chaotic flow trajectories that remain locally and globally consistent with the true transition kernel learned from Direct Numerical Simulation (DNS) data. Even though these generated trajectories are unique and distinct from the training set, they preserve the underlying statistics and manifolds, validating the strong generative performance and robustness of our methodology.

Irregularities in electron density within the interplanetary medium (IPM) can cause fluctuations in the Doppler frequency of spacecraft radio signals. The amplitude of these fluctuations depends on factors such as the carrier frequency, propagation geometry, and link configuration. However, quantitative characterization of these effects across different frequencies in various occultation experiments is currently limited. We analyze five complementary datasets: two-way S-band observations from Chandrayaan-3 outside the lunar ionosphere, two-way S-band data from Chandrayaan-2 during lunar occultation, one-way S/X band measurements from the Venus Express Radio Science (VeRa)/Akatsuki Radio Science (Akatsuki) under IPM-only conditions, and one-way X-band Akatsuki data during solar occultation. The Chandrayaan-3 and Akatsuki IPM observations isolate IPM effects by excluding contributions from planetary atmospheres, the lunar ionosphere, and, except during solar occultation, the solar corona. Chandrayaan-3 data sample dynamically evolving Earth-Moon geometries and exhibit weak, mHz-level Doppler fluctuations, while Chandrayaan-2 observations provide near-lunar plasma benchmarks with higher amplitudes, during quiet time solar and geomagnetic conditions. Akatsuki and VeRa's IPM-only measurements capture long-path interplanetary effects, whereas Akatsuki solar occultation data reveal strong coronal signatures. Power spectral density analysis indicates Kolmogorov-like turbulence for lunar occultation and solar occultation cases, while IPM-only spectra show low-amplitude fluctuations. These results quantify the IPM contribution to Doppler noise, demonstrate the enhanced plasma sensitivity of two-way coherent links, and provide constraints relevant to turbulence modelling, precision spacecraft tracking, and the interpretation of radio occultation experiments.

Mesoscopic optical states are a promising resource for quantum communication, combining robustness against losses with the preservation of genuine quantum features. Here, we propose a quantum communication protocol in which information is encoded in the first and second moments of the photon-number distributions of classical optical states, and then decoded by photon-number-resolving detectors. Security relies on the nonclassical photon-number correlations of a twin-beam state transmitted alongside the signal in the quantum channel, providing an experimentally accessible security witness against both intercept-resend and beam-splitter attacks investigated in this work. Numerical simulations performed in experimentally accessible parameter regimes support the feasibility and security of the proposed communication protocol, yielding nonzero key generation rates under the considered eavesdropping attacks, and motivating its future experimental implementation.

Integration of quantum optical technique on-chip is crucial for large scale applications of quantum technology, which were proven in a free space environment to be superior to the corresponding classical technology. Squeezed states of light can be used for enhancing the sensitivity of quantum sensors and for fault-tolerant quantum computing. Although chip-based squeezed light generation has advanced significantly, practical impact remains limited because coupling losses between the chip and off-chip detectors destroy delicate quantum correlations, restricting the amount of observed squeezing. Here, we overcome this limitation by implementing the idea of on-chip quantum measurement with the aid of a parametric amplifier and applying it to the squeezed state generated by a silicon nitride (SiN) microring resonator. In our scheme, two matched SiN micro-rings are sequentially constructed. The first ring generates a squeezed state, whereas the second ring acts as a high-gain parametric amplifier (PA) that measures the squeezed state before the light experiences significant off-chip loss. This architecture is inherently loss-tolerant: the amplifier elevates the quantum noise well above the vacuum level, making the measurement insensitive to downstream losses. We directly observe a quantum noise reduction of 4.6 dB from the first ring, despite a chip-to-fiber coupling loss exceeding 5 dB. This work also demonstrates the first monolithic SU(1,1) interferometer with an estimated 5 dB signal-to-noise enhancement compared to traditional linear interferometers, and thus establishes a practical pathway for chip-based quantum sensors.

The Liquid Scintillator Neutrino Detector (LSND) experiment aimed at investigating neutrino oscillations, particularly the transformation of muon-type antineutrinos (\(\overline{\nu}_\mu\)) into electron-type antineutrinos (\(\overline{\nu}_e\)). This phenomenon challenges the Standard Model's assumption of massless neutrinos. The LSND employed a large organic liquid scintillator (LS) to detect low-energy neutrino interactions, enhanced by the addition of metal ions such as gadolinium (Gd) for improved signal sensitivity and noise suppression. Theoretical modeling and simulations are used in this paper to accurately interpret experimental results. The FLUKA Monte Carlo code was employed to simulate particle interactions and transport in the detector. Key processes modeled included neutrino interactions (\(\overline{\nu}_e + p \to e^+ + n\)), neutron capture (\(n + p \to d + \gamma\)), and the corresponding light output in the scintillator. The simulations accounted for quenching effects using Birks' law, enabling precise predictions of light yield and detector response to secondary particles. Neutrino fluxes from decay-at-rest (DAR) and decay-in-flight (DIF) processes were calculated, capturing the energy spectra of neutrinos generated by pion and muon decays. Pion production cross-sections and light output efficiency for various particles were also modeled to understand detector performance comprehensively. The theoretical modeling and simulation framework validated the experimental observations and provided insights into the detector's sensitivity and limitations. The LSND results hinted at deviations from the Standard Model, stimulating further investigations into neutrino oscillations and the potential existence of sterile neutrinos.

By investigating the origin of the evolutionary discrepancy between the H-function and entropy, we elucidate that the H-function fails to serve as a valid arrow-of-time criterion in the rigorously derived Boltzmann equation for the hard-sphere gas model under the Boltzmann-Grad limit.

Black phosphorus (BP) has attracted attention as a light-emitting layered semiconductor for mid-infrared (MIR) photonics owing to its direct and thickness-tunable bandgap energy, highly anisotropic optical transitions, and potentially suppressed Auger recombination. However, spontaneous and stimulated emission dynamics governed by carrier recombination in BP have remained unexplored because time-resolved emission spectroscopy is challenging in the MIR region. Here we develop a time-resolved MIR emission microscope combining wavelength upconversion with superconducting single photon detection. This approach enables observation of emission dynamics in photoexcited BP at a wavelength around 4.6 {\mu}m with sub-100-ps temporal resolution. Temperature-dependent measurements reveal a crossover from excitonic to electron-hole plasma emission at around 70 K, supported by independent results in the characteristic transition temperature, pump-fluence dependence, and rise and decay dynamics of MIR emission. In a suspended BP structure, we further observe a nonlinear increase in the emission intensity above a well-defined pump threshold. Spectral narrowing and intense picosecond emission pulses appear above the threshold, providing solid evidence of stimulated emission assisted by optical feedback from a Fabry-Pérot cavity. These results elucidate ultrafast carrier dynamics and optical gain formation in BP and establish time-resolved upconversion spectroscopy as a powerful approach for investigating MIR photonic materials and devices.

In this work, we show how the specimen drift can be actively compensated by controlling the stage with precision down to the picometre scale. We do this by dynamic control, a generic real-time feedback framework designed to actively stabilize electron microscopy experiments by continuously monitoring an experimental variable from the detector data stream and compensating its evolution during acquisition. The framework, applicable to a broad range of controllable experimental instabilities, includes automated calibration procedures, operates in parallel with image acquisition and is implemented as a software plugin without requiring any hardware modification of the microscope. Results for live drift correction are shown for a selection of TEM and STEM instruments using conventional mechanical stages as well as piezoelectric stages. Experimental results are presented for medium resolution TEM, high-resolution TEM, HR-STEM and in situ observations. With piezoelectric stages, specimen stabilization down to the picometre scale was achieved allowing drift-corrected atomic-resolution imaging. Specimen stage-based stabilization significantly improves long-exposure imaging and in situ experiments by increasing the effective exposure time, preserving the field of view, maintaining identical optical conditions and eliminating the need for numerical alignment of large datasets. Beyond the specific application presented here, dynamic control provides a versatile framework for real-time regulation of electron microscopy experiments and opens new perspectives for quantitative imaging, automated in situ studies and multimodal acquisitions.

Non-contact measurement of small vibrations perpendicular to a surface supports the evaluation of mechanical structures, but in camera-based interferometry, increasing the frame rate makes a trade-off with the field of view and spatial resolution. By recording only brightness changes, event cameras avoid this trade-off and reach high temporal and spatial resolution; our previously reported event topology-based visual vibrometer recovers vibration from apparent motion. This high-speed, high-resolution sensing is well suited to full-field measurement, yet such vibration produces too little apparent motion to capture its waveform. Here we show that event-based spatial-carrier interferometry reconstructs that waveform from moving interference fringes. That displacement moves the fringes, and signed event-density maps built from the event stream are demodulated at the spatial carrier to recover the interferometric phase and fix the otherwise ambiguous motion direction at turning points. Reconstructed waveforms agree with laser Doppler vibrometry over broad drive-frequency and amplitude ranges, with limits set by the maximum fringe speed and the sensor performance. Reconstruction is limited by a minimum aperture of about two fringe periods along the carrier and one along the fringes, which allows the surface to be mapped region by region. These results provide an empirical basis for full-field, spatially resolved interferometric vibrometry with event cameras as a non-contact measurement technique.

Space-time metamaterials offer unprecedented control over electromagnetic waves by enabling simultaneous manipulation of spatial and temporal degrees of freedom. However, analytical descriptions of their scattering processes remain fragmented, with existing approaches typically requiring configuration-specific derivations or transformations to specialized reference frames that become impractical for accelerated or multi-interface structures. In this tutorial, we introduce the space-time event scattering and extension method (STESEM), a universal framework for electromagnetic scattering at arbitrary space-time interfaces. By decomposing the scattering process into a local interaction event and a subsequent extension along invariant traveling-wave coordinates, STESEM formulates space-time scattering directly in the laboratory frame without requiring coordinate transformations. The method provides a unified description of scattering amplitudes, frequency transitions and phase transformations for arbitrary incident waveforms and interface trajectories. We demonstrate the framework by deriving the complete scattering responses of canonical space-time structures, including stationary and instantaneous interfaces, space-time corners, uniformly moving interfaces, wedges and accelerated boundaries. Beyond providing analytical solutions, STESEM reveals the physical principles underlying these distinct phenomena and shows that complex space-time scattering processes can be constructed from elementary moving-interface interactions. This framework establishes a systematic foundation for analyzing and designing advanced space-time metamaterials, enabling extensions toward dispersive, bianisotropic and higher-dimensional systems.

We present a generation-resolved analysis of shower-type, spin- and polarization-dependent quantum electrodynamics (QED) cascades initiated by head-on collisions of ultraintense laser pulses ($a_0 = 200$–$1000$) with $10$~GeV electron bunches. Using a Monte Carlo model that tracks cascade evolution across distinct generations, we shows that radiation reaction strongly suppresses high-generation yields. The positron energy spectrum exhibits a systematic softening with increasing $a_0$, and the average photon polarization $\overline{\xi}_3$ increases with pulse duration $\tau$ due to polarization-selective depletion in nonlinear Breit–Wheeler pair production. We identify a scaling relation $a_0^2\tau$ that governs both the maximum cascade generation $G_{\max}$ and the fraction of backward-emitted photons $F_r$, thereby establishing experimentally accessible diagnostics for laser intensity and pulse duration using two observables: $F_r$ and the positron peak energy $\varepsilon_+^{\rm peak}$. These generation-dependent signatures suggest a potential shot-resolved, post-interaction approach for characterization of ultraintense laser parameters in the strong-field QED regime.

We extend the classical relativistic Størmer problem by incorporating radiation reaction through the Landau–Lifshitz formulation, thereby providing a self-consistent description of dissipative charged-particle motion in a static dipole magnetic field. We derive the complete dimensionless equations and distinguish them from a reduced drag-only model that preserves the exact energy-loss law while omitting directional effects associated with magnetic field gradients. For planar motion, the reduced system yields exact instantaneous evolution laws for the particle energy and canonical angular momentum, together with averaged transport equations for regular bound librations. When the motion is constrained to the instantaneous circular branch, the secular evolution can be integrated in closed form and approaches a simple large-radius power law. This analytical solution provides a useful benchmark, although the circular branch is radially unstable and therefore does not describe generic nearby trajectories. Numerical integrations further illustrate the nonuniform dissipative deformation of planar rosette-like orbits. In three dimensions, the complete Landau–Lifshitz force produces local exponential damping of small vertical perturbations, with the leading contribution arising from the field-gradient term absent from the reduced model. These exact, averaged, conditional, and local results establish a controlled analytical framework for studying radiation-driven phase-space transport in strongly inhomogeneous magnetic fields and provide a foundation for future global simulations, kinetic descriptions, and calculations of the associated electromagnetic emission.

We identify enhanced strong coherent Surface-Enhanced Raman Scattering (SERS) interactions facilitated by hybridized metallo-dielectric cavities with a resonant fluorescent molecule. By illuminating a detuned electronic transition near saturation via a narrowband hybrid plasmonic mode, we observe enhanced splittings in the Stokes and anti-Stokes spectra, revealing strong optomechanical coupling and nonlinear vibrational modifications at intensities far below irreversible SERS damage thresholds. We compute the second-order photon correlations that allows identifying the nonclassical character associated to these strong optomechanical interactions and SERS configurations that enables them to optically characterize the anharmonic character of the vibrational modes.

Achieving both high lateral and high depth resolution is a longstanding goal in stereomicroscopy. Although meta-optics have revolutionized lens design by alleviating the physical constraints of conventional optical architectures, existing metalens-assisted stereomicroscopes still suffer from field of view (FOV) mismatch between meta-optical and conventional optical components in stereomicroscopes, thereby limiting their imaging performance. Here, we show that this mismatch can be fundamentally eliminated through a fully meta-optical architecture. The integrated system enables flexible control of numerical aperture and magnification with larger depth of field (DOF) and FOV than those of the metalens-assisted stereomicroscopes. Experimentally, we achieve an integrated meta-stereomicroscope with a lateral resolution of 435 nm, surpassing the performance of previously reported stereomicroscopes. Empowered by a stereo neural network, the system enables straightforward reconstruction of high-resolution three-dimensional surface morphology with a depth resolution of 1026 nm, demonstrating the capability to simultaneously achieve high lateral and depth resolution imaging. This integrated architecture operates in both transmission and reflection modes for biomedical imaging and industrial inspection, highlighting its broad applicability for real-time observation across biomedical and industrial scenarios.