Search Results (287)

The fractional Whitham–Broer–Kaup model governs nonlinear wave propagation in memory-dependent media, including porous structures, viscoelastic fluids, and irregular seabeds, yet the full dynamical spectrum from quasi-periodicity to deterministic chaos, the role of stochastic forcing, and reliable identification from noisy data remains insufficiently explored, particularly how the fractional order $\beta$ influences these regimes. This study addresses these gaps through a comprehensive, multi-method dynamical analysis of a representative nonlinear oscillator embodying key FWBK features. Three-dimensional attractor visualizations, return maps, and surrogate data tests demonstrate a transition from quasi-periodic toroidal attractors to fully developed chaos via torus breakdown, confirming that observed complexity originates from deterministic nonlinearity. Poincaré sections reveal multistability and KAM-type structures, where coexisting attractors depend on initial conditions, while increasing noise progressively disrupts coherent dynamics. The OGY control method effectively stabilizes unstable periodic orbits across chaotic regimes with minimal perturbation, and Lyapunov analysis indicates that stochastic forcing attenuates chaos while enhancing dissipation. The Fokker–Planck framework shows that noise reshapes probability landscapes, driving transitions from unimodal to bimodal distributions. Comparative analysis of SINDy, JMAP and VBA highlights trade-offs in interpretability, computational efficiency, and uncertainty quantification, while an integrated Bayesian–PCE–Sobol approach quantifies parametric uncertainty and reveals time-dependent sensitivity variations. Additionally, the overlapping of soliton solutions extracted via the enhanced modified Sardar sub-equation method reveals structural relationships among soliton families and their stability under interaction. Soliton branches that maintain high overlap under noise correspond to stable regimes, while those losing coherence indicate the onset of chaos. Furthermore, while the reduced dynamics in $\eta$-space are independent of $\beta$, the fractional order controls spatial compression and temporal scaling in physical coordinates, directly influencing observable wave localization. These results imply that fractional effects can modify chaos transitions, support controllability through OGY, and influence noise–instability interactions depending on $\beta$. This framework provides a robust, transferable methodology for analyzing and controlling nonlinear oscillatory systems under deterministic and stochastic conditions, with direct applications to FWBK-based models in coastal engineering, fiber optics, and quantum interference systems. Full article

This paper proposes a passive in-orbit calibration method for phased array antennas using GNSS carrier-phase measurements. By performing synchronous observation and exploiting the short-baseline property between the positioning antenna and array elements, the first differencing operation eliminates space propagation errors and clock biases. By further utilizing receiver channel consistency, the second differencing operation cancels out the receiver channel errors, thereby extracting the relative receive-chain phase error of the element under test. Under typical operating conditions, the calibration accuracy can reach an RMS error of approximately $3.02\mathrm{mm}$, corresponding to a phase accuracy of $5.72°$ in the GPS L1 band. This accuracy is close to the $5.625°$ minimum phase step of a 6-bit digital phase shifter, and can be further improved under higher $C/N_0$ and well-controlled residual error conditions. Without requiring a dedicated GNSS band excitation signal, this method avoids co-frequency self-interference with the positioning antenna, which provides an auxiliary approach for in-orbit calibration of phased array receive chains. Full article

Space-based optical detection is a critical capability for Space Situational Awareness, yet the scarcity of real on-orbit observation data significantly hampers the development and validation of object detection and tracking algorithms. To address this need, this paper proposes a high-fidelity image simulation method designed to provide reliable data sup-port for algorithm development and evaluation. The method systematically integrates or-bit propagation, high-precision astrometric corrections, imaging visibility constraints, and multi-source noise modeling. A unified Point Spread Function convolution streak model is established to consistently represent the motion blur of both stars and space objects during exposure. Additionally, simplified parametric stray light background models covering the Sun, Moon, and Earth airglow are constructed. Quantitative comparison with real image data from the Kaiyun-1 satellite demonstrates good agreement in star positions, streak morphology, and centroid localization accuracy. Preliminary validation against real data demonstrates that the proposed simulation framework can provide effective image data for testing and performance assessment of space-based situational awareness algorithms. Full article

The topological properties of vector optical fields are traditionally considered strictly conserved during continuous deformations and linear propagation. However, while structured light has been extended into nonlinear regimes, previous studies have predominantly focused on the intensity modulation of specific orbital angular momentum (OAM) components and the pure frequency conversion of structured light. The critical question of whether macroscopic topological invariants remain robust or experience fundamental breakdown during nonlinear light–matter interactions remains largely unexplored. To address this specific gap, we propose and generate multiple fractional vector optical fields (MF-VOFs), establishing their dynamic topological evolution and inherent conservation laws in free space. It should be noted that our experimental results are limited to free-space propagation. Strikingly, we report a significant departure from this paradigm during light–matter interactions: topological nonconservation anomalies manifest when these optical fields interact with nonlinear materials via second- and third-harmonic generation. Through a comprehensive quantitative analysis of the OAM spectrum, we confirm that the asymmetrical reconstruction and spatial transition of the total OAM along the propagation direction serve as the physical origins driving this topological symmetry breaking. These findings provide a fundamentally novel perspective on topological manipulation in nonlinear optical processes, offering advanced strategies for complex structured light generation and high-dimensional optical information processing. Full article

Ion-acoustic waves in dense quantum plasmas are strongly influenced by Fermi degeneracy, Landau quantization, and finite-temperature effects, and in many relevant environments, they also experience memory and nonlocal transport processes that cannot be captured within the planar integer Korteweg-de Vries (KdV) paradigm. In the present work, we revisit this problem by considering a two-fluid, partially degenerate electron-ion plasma in which electron trapping in the presence of a quantizing field and finite temperature is taken into account. Starting from the normalized fluid-Poisson system appropriate for such magnetized quantum plasmas, the reductive perturbation technique is used to derive the planar integer KdV equation for weakly nonlinear ion-acoustic disturbances. Within this integer-order KdV framework, we recast the evolution equation as a planar dynamical system, construct the associated Hamiltonian and effective Sagdeev-like potential, and demonstrate the existence of compressive solitary waves and nonlinear periodic modes via homoclinic and periodic phase-space orbits. Exact multi-soliton solutions and interaction states are then obtained by combining Hirota’s direct bilinear method with generalized Wronskian representations, allowing us to describe not only standard one-, two-, and three-soliton profiles but also positon-negaton interactions relevant to magnetized, partially degenerate plasmas. To incorporate hereditary and history-dependent effects that arise from anomalous transport and nonlocal temporal response in dense environments, we extend the model by introducing a Caputo time-fractional derivative, thereby obtaining a time-fractional KdV (FKdV) equation that continuously connects the classical KdV limit to fractional dynamics. The FKdV equation is analyzed using the Tantawy technique. This semi-analytical iterative scheme yields rapidly convergent series approximations for the fractional ion-acoustic soliton and provides explicit control of the approximation error. The fractional solutions show that varying the order of the Caputo derivative modifies the amplitude, width, and temporal relaxation of the solitary structures and can even split the pulse into two distinct lobes, in contrast with the nearly rigid propagation predicted by the integer-order KdV equation. Taken together, these results clarify how Landau quantization, finite electron temperature, and fractional-order memory jointly shape the morphology, robustness, and interaction properties of ion-acoustic structures in strongly magnetized quantum plasmas of astrophysical and high-energy-density laboratory interest. Full article

Free-space optical (FSO) downlinks from satellites enable high data rates but are highly sensitive to cloud-induced attenuation and blockage. We present an integrated all-sky imaging framework for optical ground stations that converts station-local sky observations into direction- and lead-time-dependent cloud-free line-of-sight (CFLOS) decision support along predicted satellite links. The framework combines geometric calibration of hemispheric imagery, two-line element (TLE)-based orbit propagation, stereographic remapping into a common processing domain, short-horizon autoregressive sky-frame prediction using a diffusion-based sequence model, cloud/no-cloud segmentation, and a corridor-based CFLOS decision rule along the projected satellite path. The contribution lies in the operational integration of these components into a unified CFLOS-oriented sensing, prediction, and evaluation chain for optical downlink support. The framework is demonstrated at the German Aerospace Center (DLR) optical ground-station site in Trauen and evaluated using a geometry-controlled reference-track protocol across image sequences acquired at 15 s, 30 s, and 45 s cadence. Under this protocol, nowcasting-based CFLOS decisions outperformed a constant-persistence baseline across all evaluated lead times. At a 90 s lead time, the method achieved an F1-score of 0.857 and a balanced accuracy of 0.865, corresponding to gains of +0.083 and +0.089 over persistence, respectively. Positive performance margins are maintained across the full evaluated range up to a 450 s lead time. These results show that all-sky image sequences can be translated into physically interpretable CFLOS decision support and provide a basis for future network-level site-selection and handover strategies. Full article

The rapid expansion of artificial intelligence and cloud computing is straining terrestrial data center infrastructure, motivating exploration of space-based data centers (SBDCs) as a scalable and energy-efficient alternative. While orbital platforms offer unique advantages, including continuous solar energy, radiative cooling, and global coverage, their practical deployment is constrained by unresolved reliability challenges across the mission lifecycle. This study presents a lifecycle-oriented reliability and risk assessment for SBDCs spanning launch, orbital operation, maintenance, and end-of-life phases, using a structured systems-level analysis of failure modes and operational dependencies. This paper focuses on compute-centric SBDC architectures, treating storage solely as a supporting resource. We identify and classify space-environment-specific risks, including launch-induced mechanical stress, radiation-driven degradation, thermal extremes, and single points of failure in power and communication subsystems. By integrating engineering constraints with economic considerations, we develop a unified risk-chain framework that shows how reliability limitations propagate from component design to system cost and operational viability. The analysis reveals a critical trade-off: achieving terrestrial-grade reliability in orbit requires substantial redundancy and radiation hardening, increasing mass and cost and reducing economic feasibility, whereas lower-reliability designs introduce operational and financial risks that challenge sustainability. These findings establish reliability as the central determinant of SBDC viability, providing an applied foundation for fault-tolerant, modular, and lifecycle-aware design strategies essential for transitioning orbital cloud infrastructure from concept to scalable reality. Full article

Orbit determination in Earth–Moon space is challenged by dynamic-model mismatch and unstable GNSS observation conditions, especially under weak and intermittent signals. To address this issue, this paper proposes a GNSS single-point positioning (SPP)-aided orbit determination method based on adaptive sliding-window filtering. A tightly coupled framework is constructed by integrating orbital dynamics propagation with SPP pseudo-range observations, allowing propagation errors to be corrected in real time through measurement updates. To enhance adaptability under time-varying observation conditions, a dynamic sliding-window strategy is introduced, in which the observation-noise covariance is adjusted according to carrier-to-noise ratio ($C/N_0$) variations. Simulations for three representative Earth–Moon trajectories, including a near-rectilinear halo orbit (NRHO), a distant retrograde orbit (DRO), and a Halo orbit, show that the proposed method significantly outperforms the conventional tightly coupled solution. The three-dimensional RMS position error is reduced from 6.65 m to 1.27 m for NRHO, from 6.57 m to 1.27 m for DRO, and from 5.91 m to 1.44 m for Halo, corresponding to improvements of 80.9%, 80.4%, and 75.4%, respectively. Under a simulated 200-epoch GNSS interruption in the Halo case, the method also improves outage robustness and post-recovery performance, reducing the three-dimensional RMS error by 23.2% in the interruption-centered interval and by 26.1% over the full arc. Full article

Physical-layer key generation (PLKG) is a technique that produces symmetric encryption keys by exploiting the inherent characteristics of wireless channels. It offers advantages including high physical-layer security, elimination of pre-shared keys, dynamic upgradability, and resistance to quantum attacks, making PLKG a promising security solution for next-generation (6G) networks. However, satellite communication channels exhibit high dynamics and long propagation delays. Characteristics such as large Doppler shifts, short coherence times, and orbital predictability pose severe challenges to PLKG, including reciprocity degradation, low key generation rate (KGR), and susceptibility to channel-prediction attacks. This work proposes a delay-Doppler domain time-hopping key generation scheme (KE-DD-TH) based on Orthogonal Time Frequency Space (OTFS) modulation for high-speed links between Low-Earth-Orbit (LEO)/Medium-Earth-Orbit (MEO) satellites and ground terminals in Ka/Ku bands. The scheme performs non-uniform sampling on the DD domain grid of OTFS symbols using an ephemeris-driven pseudo-random time-hopping sequence generated by cascaded linear feedback shift registers (LFSRs) and a nonlinear matrix transformation. Both legitimate parties estimate the channel only at time-hopping instants and multiply two adjacent estimates to construct an “equivalent channel” matrix, yielding a random source with high entropy, high reciprocity, and low predictability. The eavesdropper’s key disagreement rate (KDR) remains close to 0.5 under all signal-to-noise ratio (SNR) conditions, corresponding to the ideal random-guessing baseline. This indicates that Eve obtains negligible mutual information, i.e., $I(K_A;K_E)\approx 0$. By contrast, the conventional KE-DD scheme allows Eve’s KDR to degrade to 0.014 at 30 dB SNR, indicating near-complete key recovery. The generated keys pass all 12 randomness tests of the NIST SP 800-22 statistical test suite. Full article

This paper introduces a higher-order orbital framework in fixed point theory based on a closed four-step orbital functional. Existing approaches, such as triangle-perimeter contractions, mainly rely on three-point configurations and first-order geometric interactions. In contrast, the proposed functional incorporates four successive iterates together with a nonlocal comparison term involving second-order orbital displacements. Using this structure, we define a new class of large closed four-step orbital contractions and establish a corresponding fixed point theorem in complete metric spaces under a boundedness assumption on one orbit. The proof is based on a propagation mechanism that transfers contractive behavior along the orbit generated by the mapping. Several examples demonstrate that the proposed framework extends classical contraction settings such as Banach and triangle-perimeter contractions. Furthermore, an application to a nonlinear Volterra integral equation provides explicit analytical estimates showing how the four-step orbital contraction structure can be verified in functional settings. These results provide a higher-order orbital extension of existing contraction principles and may contribute to further developments in generalized metric spaces and nonlinear analysis. Full article

We propose a terahertz achromatic polarization-multiplexed structured light metasurface based on the particle swarm optimization (PSO) algorithm, operating from 0.8 to 0.95 THz. A dielectric silicon meta-atom array combined with propagation phase modulation is employed to achieve broadband wavefront control under two orthogonal linear polarizations. By constructing a phase-response database and using PSO for global optimization of phase compensation factors at multiple frequencies, the metasurface simultaneously satisfies different target phase profiles while suppressing chromatic aberration. Two multifunctional devices are designed. The first generates a conventional focused spot under x-polarized incidence and a first-order Bessel beam under y-polarized incidence. The second produces a focused vortex beam with topological charge l = 1 under x polarization and a focused vortex beam with l = 2 under y polarization. Full-wave simulations demonstrate stable focal positions, low inter-channel crosstalk, and good achromatic performance across the operating band. The Bessel beam preserves its nondiffracting core, while both vortex channels exhibit clear phase singularities and well-defined orbital angular momentum states. Most operating frequencies maintain relatively high focusing efficiency. Compared with conventional cascaded optical components, our design provides a compact and stable platform for terahertz structured light generation, orbital angular momentum multiplexing, nondiffracting imaging, and multidimensional polarization information processing. Full article

Accurate impact localization on spacecraft structural panels subjected to contact loading by on-orbit servicing robots is critical for real-time structural health monitoring (SHM), yet remains challenging due to heterogeneous elastic wave propagation in complex aluminum structures with stiffener ribs and bonded joints. Conventional Received Signal Strength Indicator (RSSI)-based weighted centroid methods rely on fixed path-loss exponents that cannot accommodate spatially varying wave attenuation, resulting in position-dependent localization errors that worsen significantly near structural discontinuities. This paper proposes a Crow Search Algorithm (CSA)-optimized adaptive weighted centroid algorithm using distributed Fiber Bragg Grating (FBG) sensors, featuring three principal innovations: (i) a novel FBG wavelength-shift-to-RSSI amplitude mapping derived from elastic wave attenuation theory, bridging optical fiber sensing with centroid localization; (ii) per-event online weight optimization via CSA that adapts sensor contributions to each individual impact’s strain-wave signature; and (iii) a multi-objective fitness function simultaneously optimizing localization accuracy, noise robustness, and temporal consistency. The proposed method is validated across 200 impact events distributed over five representative positions on a 1 m³ Al6061 satellite-like structure with 64 FBG sensors (8 × 8 grid, 125 mm pitch), under three Gaussian noise levels (σ = 1%, 3%, 5% of signal RMS), and benchmarked against classical weighted centroid (WC), PSO-WC, GA-WC, DE-WC, and GWO-WC using paired t-tests (p < 0.01). CSA-WC achieves a mean localization error of 4.63 mm—an 83.29% improvement over classical WC and the lowest error among all five compared algorithms—with an average computation time of 0.14 s per event, satisfying real-time monitoring requirements. Full article

We study the phase-space dynamics of quantum systems with $\mathrm{SU}(1,1)$ group symmetry using coherent-state representations on the Poincaré disk. The resulting evolution equation combines transport terms with nonlocal contributions generated with the spectral functions of the Casimir operator, which admit a natural interpretation as pseudodifferential operators associated with the hyperbolic Laplace–Beltrami operator. Using this pseudodifferential structure, we classify the phase-space generators according to the type of the underlying PDE: compact quadratic dynamics ($\widehat{H}\propto {\widehat{K}}_0^2$) yield a degenerate hyperbolic operator of the transport type, and noncompact dynamics ($\widehat{H}\propto {\widehat{K}}_2^2$) give rise to a mixed-order differential–pseudodifferential operator. For numerical evaluation, we reformulate the propagator as an oscillatory integral and develop two complementary strategies: a Fourier-series reduction exploiting the periodicity of compact orbits and a Levin-type spectral collocation method for the noncompact case. Both approaches are stable, accurate, and free of the stiffness issues that afflict direct PDE evolution on the Poincaré disk. Full article

As a prominent frontier in ultrafast laser–matter interaction, femtosecond laser filamentation holds great potential for atmospheric pollutant detection and remote sensing. However, its practical application in the open atmosphere is severely hampered by atmospheric turbulence, which induces beam wander, wavefront distortion, and intensity scintillations. In this study, we numerically investigated the propagation dynamics of femtosecond laser filaments in a turbulent medium and elucidated the underlying physical mechanisms. The results show that, compared to linear propagation, the nonlinear self-guiding effect inherent to filamentation effectively suppresses turbulence-induced beam wander. Furthermore, by employing vortex beams carrying orbital angular momentum (OAM), we significantly suppressed the stochastic generation of multiple filaments, thereby notably improving the stability of long-range filament propagation in complex atmospheric conditions. These findings provide new insights into the physical mechanisms and novel strategies for improving the robustness of laser filamentation technology in real-world turbulent environments. Full article

Semantic communications have emerged as a key paradigm for intelligent sixth-generation (6G) wireless networks, which aim to convey the meaning of information rather than accurate bit sequences. However, in open-space low Earth orbit (LEO) satellite links, the broadcast nature and wide beam coverage expose semantic transmissions to severe eavesdropping risks. This paper establishes a unified theoretical and algorithmic framework for secure semantic downlink transmission in satellite networks. In particular, we first develop an integrated mathematical model that couples the semantic representation process, physical-layer satellite propagation characteristics, and information-theoretic secrecy into a single analytical formulation. By defining a joint semantic security cost function, the antagonistic trade-off between semantic fidelity and secrecy capacity is quantitatively characterized under realistic power, beamforming, and propagation constraints. To balance semantic fidelity and information secrecy, a reinforcement-learning-based optimization framework is proposed, wherein an actor–critic agent learns optimal power allocation and semantic weighting strategies through continuous interaction with the environment. This learning-based optimization approach enables autonomous control without requiring explicit channel distribution knowledge or offline parameter tuning. Extended simulation results show that the proposed approach consistently enhances both semantic fidelity and secrecy performance compared with conventional power-control schemes and demonstrate its potential as a foundational architecture for secure and intelligent semantic communications in next-generation satellite networks. Full article