arXiv subjects

Shuang Zhang

Publications and source records attributed to Shuang Zhang.

At least 37 records · Page 2Linked to original sources

arXiv2025

Quantized decay charges in non-Hermitian networks characterized by directed graphs

Non-Hermitian physics has unveiled a realm of exotic phenomena absent in Hermitian systems, with the non-Hermitian skin effect (NHSE) showcasing boundary-localized eigenstates driven by non-reciprocal interactions. Here, we introduce a new class of non-Hermitian systems exhibiting pure decay modes-eigenstates with pure, smooth exponential decay, devoid of the oscillatory wave patterns typical of traditional NHSE. Modeled as directed graphs with non-reciprocal hopping, these systems reveal quantized decay charges, defined as the sum of decay constants along edges at each node, offering a novel topological invariant. We derive universal conditions for these modes, enabling versatile configurations from one-dimensional rings, directed graphs with complicated connectivity, to higher-dimensional lattices. Experimental validation using microwave resonant circuits confirms the predicted pure decay profiles. This discovery paves the way for potential applications in photonics, signal processing, and beyond, harnessing the unique topological properties of non-Hermitian networks

quant-ph↗

arXiv2025

Sculpting Topological Modes on Photonic Chips by Artificial Gauge Fields

Significant efforts have been devoted to manipulating topological states, which often manifest as localized modes at interfaces between distinct topological phases. In this work, we demonstrate a versatile approach to sculpting topological modes (TMs) into any desired shapes by incorporating various artificial gauge fields (AGFs), including scalar, vector, and imaginary gauge potentials, and leveraging the power of artificial neural networks (ANNs). These AGFs enable precise tuning of the dissipation of the TMs across that of bulk modes, facilitating a transition from localized to fully delocalized states. Moreover, ANNs allow precise engineering of these eigenmodes to achieve tailored profiles of topological states, which remain spectrally isolated within the bandgap and exhibit minimal loss compared to other modes. Our theoretical results are experimentally validated on silicon photonic platforms, demonstrating flexible manipulation of TM profiles. This approach enables the design of topological states with customized properties, offering significant potential for diverse applications in photonics and beyond.

physics.optics↗

arXiv2025

LABNet: A Lightweight Attentive Beamforming Network for Ad-hoc Multichannel Microphone Invariant Real-Time Speech Enhancement

Multichannel speech enhancement (SE) aims to restore clean speech from noisy measurements by leveraging spatiotemporal signal features. In ad-hoc array conditions, microphone invariance (MI) requires systems to handle different microphone numbers and array geometries. From a practical perspective, multichannel recordings inevitably increase the computational burden for edge-device applications, highlighting the necessity of lightweight and efficient deployments. In this work, we propose a lightweight attentive beamforming network (LABNet) to integrate MI in a low-complexity real-time SE system. We design a three-stage framework for efficient intra-channel modeling and inter-channel interaction. A cross-channel attention module is developed to aggregate features from each channel selectively. Experimental results demonstrate our LABNet achieves impressive performance with ultra-light resource overhead while maintaining the MI, indicating great potential for ad-hoc array processing. The code is available:https://github.com/Jokejiangv/LABNet.git

cs.SD↗

arXiv2025

Observation of Cavity-Mediated Nonlinear Landau Fan and Modified Landau Level Degeneracy in Graphene Quantum Transport

Recent studies on cavity-coupled two-dimensional electron gas demonstrate that vacuum-field engineering can tailor electronic transport properties of materials. By achieving ultra-strong coupling between a terahertz resonator and mesoscopic graphene, we demonstrate that cavity vacuum fields can alter the effective degeneracies of Landau levels, resulting in a nonlinear Landau fan diagram for massless Dirac fermions while preserving quantum-Hall quantization. Specifically, by leveraging graphene's gate-tunability, we observe that quantum-Hall features, minimum longitudinal and quantized Hall conductance for a given filling factor, occur at carrier densities reduced by more than 20 percent compared to systems without cavity. Theoretical analysis attributes this effect to the virtual cavity photon mediated transitions between the non-equidistant Landau levels in graphene, significantly reducing their effective degeneracy. This study paves the way for investigating cavity quantum electrodynamics in highly tunable, atomically thin two-dimensional crystals.

cond-mat.mes-hall↗

arXiv2025

Adiabaticity violation under arbitrarily slow evolution

The quantum adiabatic theorem, a cornerstone of quantum mechanics, asserts that a gapped quantum system remains in its instantaneous eigenstate during sufficiently slow evolution, provided no resonances occur. Here we challenge this principle and show that adiabaticity can be violated even in arbitrarily slow processes. We introduce two new parameters, Instantaneous Transition Accumulation (ITA) and Instantaneous Transition Probability (ITP), to redefine the framework of adiabatic evolution. These parameters, grounded in cross-Berry connections and eigenstate amplitudes, reveal the dynamic and geometric factors governing adiabaticity. Using a new Phase Difference Manipulation (PDM) method, we control ITP and ITA to induce adiabaticity violation in a Landau-Zener (LZ) process. We experimentally demonstrate this counterintuitive phenomenon in a photonic waveguide system, where a slow LZ process defies adiabaticity, switching energy levels despite a fivefold slower evolution speed than a conventional adiabatic process. This discovery reshapes our understanding of quantum evolution and holds potential for quantum computing, topological physics, and photonic technologies.

quant-ph↗

arXiv2025

High-order virtual gain for optical loss compensation in plasmonic metamaterials

Metamaterials exhibit extraordinary properties yet suffer from pronounced wave dissipation, particularly in optical imaging and sensing systems. Recent advances leveraging complex frequency wave excitations with virtual gain effect, synthesized by multi-monochromatic waves, offer promising solutions for optical loss compensation. However, this approach faces limitations in extreme loss scenarios. The complex frequency wave requires sufficient virtual gain, i.e., temporal attenuation, to offset material loss, inevitably triggering rapid signal decay to zero before reaching a quasi-static state. To address this challenge, we introduce synthetic waves of high-order virtual gain to slow down the decay rate while preserving the loss compensation efficiency. We experimentally demonstrate 20-fold noise suppression in plasmonic resonance systems compared to conventional complex frequency excitations. This approach exhibits broad applicability across diverse fields, including imaging, biosensing, and integrated photonic signal processing.

physics.optics↗

arXiv2025

AI-Driven Segmentation and Analysis of Microbial Cells

Studying the growth and metabolism of microbes provides critical insights into their evolutionary adaptations to harsh environments, which are essential for microbial research and biotechnology applications. In this study, we developed an AI-driven image analysis system to efficiently segment individual cells and quantitatively analyze key cellular features. This system is comprised of four main modules. First, a denoising algorithm enhances contrast and suppresses noise while preserving fine cellular details. Second, the Segment Anything Model (SAM) enables accurate, zero-shot segmentation of cells without additional training. Third, post-processing is applied to refine segmentation results by removing over-segmented masks. Finally, quantitative analysis algorithms extract essential cellular features, including average intensity, length, width, and volume. The results show that denoising and post-processing significantly improved the segmentation accuracy of SAM in this new domain. Without human annotations, the AI-driven pipeline automatically and efficiently outlines cellular boundaries, indexes them, and calculates key cellular parameters with high accuracy. This framework will enable efficient and automated quantitative analysis of high-resolution fluorescence microscopy images to advance research into microbial adaptations to grow and metabolism that allow extremophiles to thrive in their harsh habitats.

eess.IV↗

arXiv2025

Tensor-monopole-induced topological boundary effects in four-dimensional acoustic metamaterials

Gauge field theory provides the mathematical and conceptual framework to describe and understand topological singularities such as Weyl points and magnetic monopoles. While singularities associated with vector electromagnetic gauge fields have been well-studied, those of higher-form tensor gauge fields, like the four-dimensional (4D) tensor monopoles predicted by string theory, have remained largely theoretical or limited to experimental demonstration in pure synthetic dimensions, thereby not allowing investigations of the associated boundary effects. Here, we present a 4D system with tensor monopoles using engineered acoustic metamaterials. Our momentum space combines three real momentum dimensions and a geometric parameter as the fourth. By varying this fourth momentum, we experimentally reveal two distinct topological surface states in 3D subsystems: Fermi-arc surface states in a gapless subsystem and Dirac-cone surface states in a gapped subsystem. Our work introduces a novel platform for exploring new topological structures associated with tensor gauge field and topological phenomena in higher dimensions.

cond-mat.mes-hall↗

arXiv2025

Boundary-Driven Complex Brillouin Zone in Non-Hermitian Electric Circuits

Complex-valued physical quantities, often non-conserved, represent key phenomena in non-Hermitian systems such as dissipation and localization. Recent advancements in non-Hermitian physics have revealed boundary-condition-sensitive band structures, characterized by a continuous manifold of complex-valued momentum known as the generalized Brillouin zone (GBZ). However, the ability to actively manipulate the GBZ and its associated topological properties has remained largely unexplored. Here, we demonstrate a controllable manipulation of the GBZ by adjusting the boundary Hamiltonian and leveraging the boundary sensitivity in a circuit lattice. Our observations reveal that the GBZ forms multiple separated manifolds containing both decaying and growing wave functions, in contrast to the previously observed non-Hermitian skin effect under open boundary condition (OBC). By continuously deforming the GBZ, we observe the topological phase transitions of innate topological structure of GBZ that are enriched by complex properties of non-Hermitian physical variables. Notably, such topological phase transition is governed by boundary conditions rather than bulk properties, underscoring the extreme boundary sensitivity unique to non-Hermitian systems.

physics.app-ph↗

arXiv2025

Spontaneous Symmetry Breaking of Cavity Vacuum and Emergent Gyrotropic Effects in Embedded moiré Superlattices

In an electronic system, spontaneous symmetry breaking can arise from many-body interaction between electrons, leading to degenerate ground states distinguishable by emergent effects otherwise prohibited by the symmetry. Here we show that ultrastrong coupling of a mesoscopic electronic system to the vacuum of a cavity resonator can lead to another paradigm of spontaneous breaking of spatial symmetries in both systems. As a pertinent example, we consider the orbital gyrotropic effects in a moiré superlattice embedded in a THz split ring cavity resonator. Our mean-field and exact diagonalization calculations consistently demonstrate a spontaneous parity symmetry breaking in both the electronic ground state and the cavity vacuum, leading to two degenerate hybrid ground states distinguished by their opposite orbital gyrotropic Hall and magnetic effects. These sizable responses in the cavity-embedded moiré superlattice are highly tunable by both the cavity field polarization and interlayer bias on the moiré superlattice, providing an advanced platform for manipulating gyrotropic effects.

cond-mat.mes-hall↗

arXiv2025

Understanding the Practices, Perceptions, and (Dis)Trust of Generative AI among Instructors: A Mixed-methods Study in the U.S. Higher Education

Generative AI (GenAI) has brought opportunities and challenges for higher education as it integrates into teaching and learning environments. As instructors navigate this new landscape, understanding their engagement with and attitudes toward GenAI is crucial. We surveyed 178 instructors from a single U.S. university to examine their current practices, perceptions, trust, and distrust of GenAI in higher education in March 2024. While most surveyed instructors reported moderate to high familiarity with GenAI-related concepts, their actual use of GenAI tools for direct instructional tasks remained limited. Our quantitative results show that trust and distrust in GenAI are related yet distinct; high trust does not necessarily imply low distrust, and vice versa. We also found significant differences in surveyed instructors' familiarity with GenAI across different trust and distrust groups. Our qualitative results show nuanced manifestations of trust and distrust among surveyed instructors and various approaches to support calibrated trust in GenAI. We discuss practical implications focused on (dis)trust calibration among instructors.

cs.HC↗

arXiv2024

From Pairwise to Ranking: Climbing the Ladder to Ideal Collaborative Filtering with Pseudo-Ranking

Intuitively, an ideal collaborative filtering (CF) model should learn from users' full rankings over all items to make optimal top-K recommendations. Due to the absence of such full rankings in practice, most CF models rely on pairwise loss functions to approximate full rankings, resulting in an immense performance gap. In this paper, we provide a novel analysis using the multiple ordinal classification concept to reveal the inevitable gap between a pairwise approximation and the ideal case. However, bridging the gap in practice encounters two formidable challenges: (1) none of the real-world datasets contains full ranking information; (2) there does not exist a loss function that is capable of consuming ranking information. To overcome these challenges, we propose a pseudo-ranking paradigm (PRP) that addresses the lack of ranking information by introducing pseudo-rankings supervised by an original noise injection mechanism. Additionally, we put forward a new ranking loss function designed to handle ranking information effectively. To ensure our method's robustness against potential inaccuracies in pseudo-rankings, we equip the ranking loss function with a gradient-based confidence mechanism to detect and mitigate abnormal gradients. Extensive experiments on four real-world datasets demonstrate that PRP significantly outperforms state-of-the-art methods.

cs.IR↗

arXiv2024

Photonic Terahertz Phased Array

Phased arrays are crucial in various technologies, such as radar and wireless communications, due to their ability to precisely control and steer electromagnetic waves. This precise control improves signal processing and enhances imaging performance. However, extending phased arrays to the terahertz (THz) frequency range has proven challenging, especially for high-frequency operation, broadband performance, two-dimensional (2D) phase control with large antenna arrays, and strong phase modulation. Here, we introduce a photonic platform to realize a THz phased array that bypasses the above challenges. Our method employs 2D phase coding with 2-bit across a broad THz frequency range from 0.8 to 1.4 THz. The core of our design is a pixelated nonlinear Pancharatnam-Berry metasurface driven by a spatially modulated femtosecond laser, allowing precise phase control of THz signals. We showcase the effectiveness of our method through four proof-of-concept applications: single beamforming, dual beamforming, imaging and vortex beam generation. The realized photonic platform provides a promising pathway for developing broadband phased arrays in the THz regime.

physics.optics↗

arXiv2024

Synthetic gain for electron-beam spectroscopy

Electron-beam microscopy and spectroscopy featuring atomic-scale spatial resolution have become essential tools used daily in almost all branches of nanoscale science and technology. As a natural supercontinuum source of light, free electrons couple with phonons, plasmons, electron-hole pairs, inter- and intra-band transitions, and inner-shell ionization. The multiple excitations, intertwined with the intricate nature of nanostructured samples, present significant challenges in isolating specific spectral characteristics amidst complex experimental backgrounds. Here we introduce the approach of synthetic complex frequency waves to mitigate these challenges in free-electron--light interaction. The complex frequency waves, created through causality-informed coherent superposition of real-frequency waves induced by free electrons, offer virtual gain to offset material losses. This amplifies and enhances spectral features, as confirmed by our electron energy loss and cathodoluminescence measurements on multi-layer membranes, suspended nanoparticles, and film-coupled nanostructures. Strikingly, we reveal that our approach can retrieve resonance excitation completely buried underneath the zero-loss peak, substantially enhance the quality of hyperspectral imaging, and resolve entangled multiple-photon-electron events in their quantum interaction. Our findings indicate the versatile utility of complex frequency waves in various electron-beam spectroscopy and their promising diagnostic capabilities in free-electron quantum optics.

physics.optics↗

arXiv2024

Lattice simulation of nucleon distribution and shell closure in the proton-rich nucleus $^{22}$Si

The proton-rich nucleus $^{22}$Si is studied using Nuclear Lattice Effective Field Theory with high-fidelity chiral forces. Our results indicate that $^{22}$Si is more tightly bound than $^{20}$Mg, thereby excluding the possibility of two-proton emission. The $Z = 14$ shell closure in $^{22}$Si is supported by the evolution of the $2^+$ state in the neighboring nuclei. We then focus on the charge radius and spatial distribution information of $^{22}$Si, considering the novel phenomena that may emerge due to the small two-proton separation energy and the shell closure. We present the distribution of the $14$ protons and $8$ neutrons obtained from our lattice simulation, revealing insights into the spatial arrangement of the nucleons. Moreover, the spatial localization of the outermost proton and neutron suggests that $^{22}$Si is a doubly magic nucleus. Furthermore, we develop the pinhole method based on the harmonic oscillator basis, which gives insight into the nuclear structure in terms of the shell model picture from lattice simulations. Our calculated occupation numbers support that $Z = 14$ and $N = 8$ are the shell closures and show that the $π1s_{1/2}$ orbital component is minor in $^{22}$Si.

nucl-th↗

arXiv2024

Joint Beamforming Optimization for Active STAR-RIS-Assisted ISAC Systems

In this paper, we investigate an active simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) assisted integrated sensing and communications (ISAC) system, where the dual-function base station (DFBS) operates in full-duplex (FD) mode to provide communication services and performs targets sensing simultaneously. Meanwhile, we consider multiple targets and multiple users scenario as well as the self-interference at the FD DFBS. Through jointly optimizing the DFBS and active STAR-RIS beamforming under different work modes, our purpose is to achieve the maximum communication sum-rate, while satisfying the minimum radar signal-to-interference-plus-noise ratio (SINR) constraint, the active STAR-RIS hardware constraints and the total power constraint of DFBS and active STAR-RIS. To tackle the complex non-convex optimization problem formulated, an efficient alternating optimization algorithm is proposed. Specifically, the fractional programming method is first leveraged to turn the original problem into a more tractable one, and subsequently the transformed problem is decomposed into several sub-problems. Next, we develop a derivation method to obtain the closed-form expression of the radar receiving beamforming, and then the DFBS transmit beamforming is optimized under the radar SINR requirement and total power constraints. After that, the active STAR-RIS reflection and transmission beamforming are optimized by majorization minimization, complex circle manifold and convex optimization techniques. Finally, the proposed schemes are conducted through numerical simulations to show their benefits and efficiency.

cs.IT↗

arXiv2024

Shortcuts to adiabatic non-Abelian braiding on silicon photonic chips

The non-Abelian braiding describes the exchange behavior of anyons, which can be leveraged to encode qubits for quantum computing. Recently, this concept has been realized in classical photonic and acoustic systems. However, these implementations are constrained by adiabatic conditions, necessitating long operation distances and impeding practical applications. Here, we conceive and demonstrate a shortcut to adiabatic (STA) braiding of telecommunication light in three-dimensional silicon photonic chips. Our device comprises tri-layer silicon waveguides stacked and embedded in the SU-8 polymer, employing an STA strategy to expedite the braiding operations and give rise to compact devices that function as photonic quantum X, Y, and Z gates. We further experimentally observed non-Abelian braiding behaviors based on this STA-braiding scheme. Remarkably, this achievement represents the most compact braiding apparatus ever reported, with a size reduction of nearly three orders of magnitude compared to previous works. This work presents a feasible approach to accelerating adiabatic braiding evolutions, paving the way for compact, CMOS-compatible non-Abelian photonic devices.

physics.optics↗

arXiv2024

The RoboDepth Challenge: Methods and Advancements Towards Robust Depth Estimation

Accurate depth estimation under out-of-distribution (OoD) scenarios, such as adverse weather conditions, sensor failure, and noise contamination, is desirable for safety-critical applications. Existing depth estimation systems, however, suffer inevitably from real-world corruptions and perturbations and are struggled to provide reliable depth predictions under such cases. In this paper, we summarize the winning solutions from the RoboDepth Challenge -- an academic competition designed to facilitate and advance robust OoD depth estimation. This challenge was developed based on the newly established KITTI-C and NYUDepth2-C benchmarks. We hosted two stand-alone tracks, with an emphasis on robust self-supervised and robust fully-supervised depth estimation, respectively. Out of more than two hundred participants, nine unique and top-performing solutions have appeared, with novel designs ranging from the following aspects: spatial- and frequency-domain augmentations, masked image modeling, image restoration and super-resolution, adversarial training, diffusion-based noise suppression, vision-language pre-training, learned model ensembling, and hierarchical feature enhancement. Extensive experimental analyses along with insightful observations are drawn to better understand the rationale behind each design. We hope this challenge could lay a solid foundation for future research on robust and reliable depth estimation and beyond. The datasets, competition toolkit, workshop recordings, and source code from the winning teams are publicly available on the challenge website.

cs.CV↗