Search Results (3,608)

Reliable high-fidelity video transmission over noisy quantum channels remains challenging, especially due to temporal dependencies introduced by modern video compression standards. These codecs, such as versatile video coding (VVC), employ inter-frame prediction and group-of-pictures (GOP) structures, which are highly sensitive to channel noise and can lead to error propagation across frames. Conventional quantum encoding schemes, such as Hadamard-based superposition encoding, use fixed real-valued basis transformations that provide limited phase diversity and underutilize the multi-qubit state-space, reducing robustness under noisy quantum channels. To overcome these limitations, this study proposes a multi-qubit complex-valued orthogonal unitary superposition (COUS) encoding framework for quantum video transmission. In the proposed system, VVC-compressed video bitstreams are first protected using classical channel encoding, then segmented and mapped onto multi-qubit COUS quantum states, enabling joint amplitude and phase representation with improved resilience to quantum noise. At the receiver, transmitted quantum states undergo sequential COUS decoding, channel decoding, and VVC bitstream reconstruction to recover the original video frames. The simulation results show that COUS-based multi-qubit system outperforms the Hadamard encoding-based multi-qubit system, achieving peak signal-to-noise ratio (PSNR) up to 47.22 dB, structural similarity index measure (SSIM) up to 0.9905, and video multi-method assessment fusion (VMAF) up to 96.49. Even single-qubit COUS encoding achieves 3–4 dB channel SNR gain, while higher-qubit configurations further enhance robustness and reconstructed video quality. These results confirm that the proposed framework is scalable, noise-resilient, and provides high-fidelity quantum video transmission over noisy channels. Full article

We present a method to control broadband terahertz generation rapidly during the interaction of a strong laser field with a gas. To achieve it, we utilize a few-cycle double-pulse, which is a combination of two identically colored femtosecond fields with a time delay, as a driving laser field. By varying the laser delay, the magnitude of the amplitude of generated terahertz field changes drastically, making it suitable for use as a terahertz optical ultrafast switch, with an optical period of only a few femtoseconds from ON-OFF-ON and an enhancement ratio of 100. Furthermore, a change in time delay can alter the terahertz field waveform, easily generating terahertz electric fields with positive and negative polarity or any phase in the range of [0, 1.0$\pi$]. The strength of such terahertz source can be boosted by raising the laser wavelength. Our study will provide an effective approach for ultrafast terahertz modulation. Full article

Phase-resolved wave estimation during operation of floating structures based on motion measurements provides an efficient, low-cost approach to enhancing operations. Prolate spheroidal wave functions (PSWFs) enable the reconstruction of wave profiles in short time windows with the help of a wave-to-motion response amplitude operator (RAO). Although fully linear hydrodynamic modeling can efficiently derive the RAO of floating structures, its applicability is highly limited to rather linear operation conditions. This study extends the PSWF methodology for wave estimation by combining it with the statistical linearization approach, which allows nonlinearities to be incorporated into the RAO based on the measured motion. The combined methodology is verified with motions for a floating cylinder and sphere, whose motions were calculated using a time domain simulation based on Cummins equation. Viscous drag and nonlinear hydrostatic forces were investigated. The results showed that the combined methodology increased the accuracy of the resulting wave profiles, measured in terms of correlation and spectral differences. Combining PSWFs and statistical linearization reproduced wave profiles with correlation values above 0.9 in waves with periods greater than 9 s. Combining both nonlinear effects for the sphere slightly increased the method’s accuracy due to the reduced motion amplitudes. Full article

This paper presents a theoretical analysis of frequency shifts in broadband acoustic field interference structures caused by an internal soliton wave in shallow water. It analyzes the spectral signature of interference-maxima frequency shifts within a coupled-mode framework that describes the scattering of acoustic normal modes under soliton-induced perturbations. Using the weak coupling approximation, analytical expressions are obtained for modal phase variations and the spectral peak frequency associated with the temporal evolution of frequency shifts induced by internal soliton waves. The analytical estimates obtained in the weak coupling approximation are extensively validated using numerical simulations under realistic ocean conditions without invoking it. This paper’s theoretical analysis demonstrates that internal soliton wave-induced mode coupling produces frequency shift spectrum signatures that strongly depend on soliton parameters. These results suggest that it is potentially feasible to estimate key soliton parameters, such as propagation direction, velocity, and effective amplitude, from measured frequency shifts. Numerical simulations demonstrate the feasibility of solving this inverse problem. These findings highlight the potential of frequency shift analysis as a practical, robust tool for remote sensing of internal wave dynamics in ocean acoustics. Full article

Distance measures play a crucial role in fuzzy decision-making, pattern recognition, and uncertainty modeling. However, some existing distance measures for Complex Picture Fuzzy Sets (CPiFSs) have shown limitations and may produce counterintuitive results in certain cases. Moreover, only a few studies have explored such measures. To overcome these issues, in this study, some novel measures of distance for CPiFSs are proposed to effectively handle two-dimensional uncertainty characterized by amplitude and phase components. The proposed measures are developed by integrating both magnitude and phase information in a unified mathematical framework, ensuring improved discrimination capability and structural consistency. We rigorously prove that the suggested measures fulfill the essential properties of a distance function. Additionally, the normalization characteristics and stability behavior are analytically examined to ensure robustness in practical implementations. The proposed measure of distance is then applied to a multi-criteria decision-making (MCDM) case study, where alternatives are evaluated under Complex Picture Fuzzy information to demonstrate its practical effectiveness and ranking consistency. Using a CPiFS-based TOPSIS framework, distances from the positive and negative ideal solutions are computed via the developed metric, and the relative closeness coefficient is employed to obtain a stable and discriminative ranking of alternatives. Furthermore, comparative analysis with several existing distance measures demonstrates the stability and superiority of the proposed method in distinguishing complex fuzzy information. Full article

Precise sculpturing of light empowers light with abundant phenomena across fundamental physics and practical applications. The emergence of metasurfaces provides a pivotal solution to the limitations of traditional optical components, which make it difficult to meet the integration requirements of diverse applications, and they are distinguished by their ultra-thin profiles, low optical losses, and high degree of controllability. In this paper, we elucidate the core physical principles to manipulate phase, amplitude, and polarization with meta-optic architecture, along with nonlocal effects. Specifically, we revisit the research progress and typical applications of meta-waveguides, meta-fibers, meta-lasers, meta-spectrometers, and meta-sensing. Finally, it looks forward to the future development direction of meta-optics in exploring the limits of light field control, chip-scale functional integration, and discovering new physical effects, providing theoretical and technical references for the development of metaphotonic devices. Full article

We explore a phenomenological extension of the Polyakov–Nambu–Jona-Lasinio (PNJL) model by introducing a curvature-sensitive effective contribution to the Polyakov-loop potential, motivated by the hypothesis that the non-perturbative QCD vacuum in the confined phase may retain a residual sensitivity to cosmic expansion. In a spatially flat FLRW background, this modification reduces to a term proportional to $\alpha {(H/H_0)}^{d}f(\Phi ,{\Phi }^{*})$, which naturally vanishes in the deconfined regime and behaves as an effective dynamical vacuum component at late times, without invoking a fundamental cosmological constant. The construction provides an effective thermodynamic description of the QCD sector within an adiabatic framework and introduces a minimal phenomenological extension characterized by the exponent d and the amplitude parameter $\alpha$. We analyze the cosmological implications at the background level and compare the model with low-redshift observations, including cosmic chronometers, Type Ia supernovae, HII galaxies, and quasars. Using Bayesian Monte Carlo techniques, we constrain the model parameters and compare its performance with the ΛCDM. Our results indicate that the modified PNJL cosmology provides a statistically competitive fit to current data while allowing small departures from the ΛCDM within observational uncertainties. We also investigate the impact of the coupling on the QCD phase diagram and the critical end point. The framework offers a tractable effective approach to connect confinement physics with late-time cosmology and suggests directions for further theoretical development in QCD under curved backgrounds. Full article

Understanding the effects of light on the body at different times of the 24 h solar day is a topic of increasing interest. In this paper, we use a mathematical model from the literature to simulate what would be expected of the human circadian clock on different light schedules. We first reproduce an influential experiment which found eBooks, when compared to a paper book, delayed sleep by roughly 10 min and melatonin onset by 1.5 h. The model is able to match the delay in sleep onset but struggles to reproduce the melatonin phase delay. However, certain initial conditions and parameters are capable of phase shifts consistent with the original study’s magnitude, suggesting that the original study’s finding may have been influenced by the pre-study entrainment or variability among the participants. We next simulate the same protocol under higher daytime light levels (increasing baseline illumination from 90 to 500 lux) and find that brighter daytime exposure reduces both sleep onset latency and the variability in phase delay attributable to evening eBook light. Finally, we explore how the timing of a bright light pulse during the day changes outcomes, such as sleep onset and circadian amplitude, and how these effects interact with light during the other hours of the 24 h day. Together, these modeling results suggest robust daytime light exposure confers resilience against the circadian-disruptive effects of evening light, generating testable predictions regarding the timing and intensity of beneficial light interventions for maintaining circadian alignment. Full article

Adversarial transferability makes black-box attacks practical and exposes weaknesses of deep neural networks for computer vision, image recognition, and visual understanding. Among various transferability-enhancing methods, input transformation is one of the most effective strategies. However, existing methods often ignore the decoupling of style and semantics in the input image, as well as the need for customized transformation strategies, resulting in limited performance gains or suboptimal outcomes. In this paper, we propose a novel Fourier-based perspective for input transformation generalization in the context of vision adversarial attacks. The main observations are that the Fourier amplitude captures stylistic information and the phase encompasses richer semantics which are crucial for visual understanding. Motivated by this, we develop a Fourier-based strategy, which performs a stylistic transform and semantic mixup on the input examples to improve transferability. To avoid inconsistent semantics of augmented images for the surrogate model, we mix the original images with the augmentations to maintain semantic consistency and mitigate imprecise gradients. Extensive experiments on ImageNet-compatible datasets demonstrate that our method consistently outperforms existing input transformation attacks. Full article

Herein, we present the analysis, design, optimization, and fabrication of a broadband, stepped-impedance Wilkinson power divider. The proposed structure employs stepped-impedance transmission lines and open-circuited stubs, achieving a simple and compact implementation while maintaining a wideband frequency response. Initially, transmission-line-based circuit analysis was performed to extract the design equations, followed by simulation and optimization to enhance impedance matching and output-port isolation over a broad bandwidth. Finally, the proposed divider was fabricated using microstrip-line technology, and experimental measurements were conducted using the Agilent E5071C vector network analyzer. The simulation and measurement results showed efficient wideband operation over the 1–4 GHz frequency range. Specifically, the measured return loss at the input port was <−10 dB; the corresponding return loss at the output ports was <−15 dB. The measured insertion loss was −3.73 ± 0.42 dB. The isolation between the output ports was <−10 dB, reaching approximately −30 dB at 2.1 GHz and −25 dB at the center operating frequency (f₀ = 2.5 GHz). The amplitude and phase imbalances were 0 ± 0.2 dB and 0^o ± 0.8^o, respectively. Furthermore, the overall size of the proposed wideband Wilkinson power divider was 0.35λg × 0.21λg. Compared to previous designs, the divider proposed in this study exhibits an improved and more symmetric frequency response, as well as a substantially reduced size, making it suitable for several modern wireless technologies such as Wi-Fi, Bluetooth, GPS, DCS, WCDMA, and sub-6 GHz 5G communication systems. Full article

Background/Objectives: Bimanual movements with a 90° relative phase are typically unstable but can be facilitated by Lissajous visual feedback, which integrates the movements of the two hands into a single visual representation. We examined whether such visual integration leads to a unified sensorimotor representation by testing whether unilateral tactile stimulation suppresses motor output bilaterally during bimanual force production. Methods: Fifteen healthy participants produced rhythmic bimanual index finger flexion with a 90° relative phase under two feedback conditions: Lissajous feedback and individual visual feedback. In each trial, vibrotactile stimulation was applied to either hand or not applied at one of four phases of the force cycle. Force trajectory error and post-stimulus electromyographic (EMG) activity of the first dorsal interosseous muscle were analyzed. Results and Discussion: Lissajous feedback reduced force trajectory error compared with individual feedback. Tactile stimulation did not produce bilateral suppression of motor output. This indicates that visual integration of bimanual movements does not lead to global bilateral suppression of motor output induced by unilateral tactile stimulation. A significant reduction in post-stimulus EMG amplitude was observed only when the right hand was stimulated during one phase of the Lissajous feedback task. This suppression may reflect the unmasking of the tactile stimulus-induced inhibition within sensorimotor processes in the left hemisphere when visual feedback of the two hands is merged into a single representation. Full article

Magnetic hysteresis strongly influences energy dissipation and efficiency in power magnetic components under time-varying excitation. This work proposes a compact dynamic hysteresis model using a Hammerstein structure, consisting of a closed-form arctangent static operator followed by a first-order relaxation dynamic stage. The formulation enables direct datasheet-based parameterization and avoids iterative differential solvers or distributed hysteron representations, resulting in low calibration effort and computational cost. The static hysteresis behavior is characterized using four static parameters directly identified from manufacturer B-H datasheets, while dynamic effects are captured using two global calibration parameters derived from datasheet loss curves. This formulation enables accurate reconstruction of major and minor hysteresis loops, while introducing frequency-dependent phase lag and dynamic loop opening. Model performance is evaluated under diverse excitations, including sinusoidal, amplitude-modulated, FORC and chirp signals, showing waveform deviations below 7.2% peak-to-peak NRMSE relative to classical hysteresis models. Energy-loss predictions are validated against manufacturer datasheet curves for ferrite material 3C90 across multiple frequencies, yielding a root-mean-square relative error of 8.3% with 89% of operating points within ±20% deviation. The proposed model provides a datasheet-driven framework for hysteresis and energy-loss prediction in power magnetic components. Full article

To address the polarization fading noise in coherent detection phase-sensitive optical time-domain reflectometry (Φ-OTDR) for distributed low-frequency vibration sensing, a Φ-OTDR sensing scheme integrating polarization diversity reception and the variational mode decomposition (VMD) algorithm is proposed. The mechanism of polarization fading induced by fiber birefringence and external perturbations is systematically analyzed. A signal–noise mathematical model for polarization diversity reception is established, and the adaptive decomposition capability of the VMD algorithm for non-stationary phase signals is elaborated. This scheme can accurately separate the additional noise introduced by polarization diversity reception from the target low-frequency vibration signals. Experimental results demonstrate that, compared with the single-path detection scheme, the proposed method eliminates the amplitude attenuation of beat frequency signals caused by polarization mismatch at the optical path level. Meanwhile, it effectively suppresses both the additional noise introduced by polarization diversity and the low-frequency phase drift resulting from unstable laser frequency. It achieves precise phase restoration of vibration signals excited at 50 Hz under three typical sensing distances of 5 km, 10 km, and 30 km. Additionally, it successfully restores low-frequency vibration signals as low as 0.6 Hz at the sensing distance of 30 km. Full article

Research on methods for detecting microwave-based noncontact vibration has garnered significant attention in recent years. To simplify system complexity and reduce costs, which would enable broader application of radar technology in daily life, we propose a low-complexity, high-precision continuous-wave (CW) radar system for noncontact vibration detection. This system employs a hardware-based approach for phase comparison to extract vibration information, enabling simultaneous detection of both vibration amplitude and frequency under a CW radar architecture. In this study, we establish a phase discrimination error model to characterize the inconsistent detection sensitivity of the hardware phase comparator in different phase intervals, and we further propose a phase compensation scheme to mitigate the nonlinearity of phase discrimination and the “null-point” problem in continuous phase comparison, consequently improving the sensitivity and precision of the proposed radar system. Through loudspeaker vibration and experiments on human vital signs, the system maintains a vibration amplitude detection accuracy above 90.3% within 1.8 m while achieving respiratory rate and heartbeat rate detection accuracies of 96.34% and 98.02%, respectively. Full article

With the increasing demand for intelligent fault monitoring, acoustic-based diagnosis has emerged as a promising solution for industrial applications such as pipeline leakage and electrical equipment fault detection. However, complex working conditions and domain shifts significantly degrade model performance, especially when unseen target domain data is unavailable. To address this, we propose an amplitude-phase collaborative augmentation network named AP-CANet tailored for acoustic fault diagnosis. Specifically, the network adaptively aligns amplitude and phase features across multiple source domains and performs label-consistent sample augmentation to enrich data diversity while preserving semantic consistency. A frequency–spatial interaction module further integrates global spectral information with local temporal details to improve feature discriminability. Moreover, we introduce a manifold triplet loss that scales shortest path distances in the feature manifold, encouraging the model to better capture subtle distinctions among hard samples and improving intra-class compactness and inter-class separability. We evaluate the proposed method on two publicly available datasets: the Pipeline Leak Acoustic Dataset (GPLA-12) and the Electrical Sound Dataset (MIMII-DG). Experimental results demonstrate superior performance under domain-shift scenarios, highlighting the method’s potential for scalable and low-cost acoustic fault diagnosis in real-world industrial environments. Full article