arXiv subjects

Wenwen Liu

Publications and source records attributed to Wenwen Liu.

13 recordsLinked to original sources

arXiv2026

Gauge-Engineered Tunable Mode Selection in Non-Hermitian Directed-Graph Networks

Programmable mode selection is essential for integrated photonic networks, yet selectively isolating individual modes without delicate balancing of gain and loss remains challenging. Here we introduce a gauge-engineering method in non-Hermitian directed-graph networks that support geometry-protected pure decay modes:eigenstates exhibiting smooth exponential amplitude decay along directed paths. In fully connected configurations, a single dominant mode emerges naturally, separated from the remaining modes by a large, tunable energy gap. By introducing synthetic gauge fields through phase-compensated non-reciprocal hopping, any desired pure decay mode can be promoted to the dominant position while its amplitude profile is preserved, which can be naturally interpreted by spectral graph theory. The approach further extends to simultaneous selection of paired modes in half-connected graphs and customizable multi-mode distributions in higher dimensions via orthogonal folding. Our method enables robust, loss/gain-free control over mode profiles, advancing applications in single-mode lasers, sensors, and quantum processing.

quant-ph↗

arXiv2026

AnyBand-Diff: A Unified Remote Sensing Image Generation and Band Repair Framework with Spectral Priors

Existing diffusion models have made significant progress in generating realistic images. However, their direct adaptation to remote sensing imagery often disregards intrinsic physical laws. This oversight frequently leads to spectral distortion and radiometric inconsistency, severely limiting the scientific utility of generated data. To address this issue, this paper introduces AnyBand-Diff, a novel spectral-prior-guided diffusion framework tailored for robust spectral reconstruction. Specifically, we design a Masked Conditional Diffusion backbone integrated with a dual stochastic masking strategy, empowering the model to recover complete spectral information from arbitrary band subsets. Subsequently, to ensure radiometric fidelity, a Physics-Guided Sampling mechanism is proposed, leveraging gradients from a differentiable physical model to explicitly steer the denoising trajectory toward the manifold of physically plausible solutions. Furthermore, a Multi-Scale Physical Loss is formulated to enforce rigorous constraints across pixel, region, and global levels in a joint manner. Extensive experiments confirm the effectiveness of AnyBand-Diff in generating reliable imagery and achieving accurate spectral reconstruction, contributing to the advancement of physics-aware generative methods for Earth observation.

cs.CV↗

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

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

Enumerating Partial Duals of Hypermaps by Genus

The concept of partial duality in hypermaps was introduced by Chmutov and Vignes-Tourneret, and Smith independently. This notion serves as a generalization of the concept of partial duality found in maps. In this paper, we first present an Euler-genus formula concerning the partial duality of hypermaps, which serves as an invariant related to the result obtained by Chmutov and Vignes-Tourneret. This formulation also generalizes the result of Gross, Mansour, and Tucker regarding partial duality in maps. Subsequently, we enumerate the distribution of partial dual Euler-genus for hypermaps and compute the corresponding polynomial for specific classes of hypermaps through three operations: join, bar-amalgamation, and subdivision.

math.CO↗

arXiv2024

Boosting Architectural Generation via Prompts: Report

In the realm of AI architectural design, the importance of prompts is becoming increasingly prominent. With advancements in artificial intelligence and large-scale model technology, more design tasks are being delegated to machine learning algorithms. This necessitates a method for designers to guide algorithms in producing their desired designs. Prompts serve as a guiding and motivational mechanism, playing a crucial role in AI-generated architectural design. This paper categorizes and summarizes common vocabulary used in architectural design, discussing how to craft effective prompts and their impact on the quality and creativity of generated results. Through careful prompt design, designers can better control the generated architectural design images, thereby achieving designs that are more aligned with requirements and innovative.

cs.HC↗

arXiv2024

Pure skin effect obeying power partition in directed graphs

Non-Hermitian physics has received great attention recently. In particular, band structures in non-Hermitian systems can be engineered to exhibit various topological effects. Among them, one of the most intriguing phenomena is the non-Hermitian skin effect (NHSE). Here, we investigate NHSE in systems featuring directed chains or directed graphs, where the arrows denote the directions of the non-reciprocal hopping between neighbouring nodes. We show that the systems exhibit pure skin modes with non-oscillatory wavefunctions, in contrast to previously studied NHSE. Interestingly, the sum of the decay constants along different directions for each skin mode obeys a power partition rule, i.e. their sum is a fixed value and the value of each constant only depends on the ratio between the non-reciprocal hopping parameters and is independent of detailed graph configurations. Such Pure Skin Effect (PSE) can be explained by using a generalized method for solving the Generalized Brillouin-zone with multiple bulk states.

quant-ph↗

arXiv2023

A Summary of Privacy-Preserving Data Publishing in the Local Setting

The exponential growth of collected, processed, and shared data has given rise to concerns about individuals' privacy. Consequently, various laws and regulations have been established to oversee how organizations handle and safeguard data. One such method is Statistical Disclosure Control, which aims to minimize the risk of exposing confidential information by de-identifying it. This de-identification is achieved through specific privacy-preserving techniques. However, a trade-off exists: de-identified data can often lead to a loss of information, which might impact the accuracy of data analysis and the predictive capability of models. The overarching goal remains to safeguard individual privacy while preserving the data's interpretability, meaning its overall usefulness. Despite advances in Statistical Disclosure Control, the field continues to evolve, with no definitive solution that strikes an optimal balance between privacy and utility. This survey delves into the intricate processes of de-identification. We outline the current privacy-preserving techniques employed in microdata de-identification, delve into privacy measures tailored for various disclosure scenarios, and assess metrics for information loss and predictive performance. Herein, we tackle the primary challenges posed by privacy constraints, overview predominant strategies to mitigate these challenges, categorize privacy-preserving techniques, offer a theoretical assessment of current comparative research, and highlight numerous unresolved issues in the domain.

cs.CR↗

arXiv2023

Unveiling Real Triple Degeneracies in Crystals: Exploring Link and Compound Structures

With their non-Abelian topological charges, real multi-bandgap systems challenge the conventional topological phase classifications. As the minimal sector of multi-bandgap systems, real triple degeneracies (RTPs), which serve as real 'Weyl points', lay the foundation for the research on real topological phases. However, experimental demonstration of physical systems with global band configurations consisting of multiple RTPs in crystals has not been reported. Here we present experimental evidence of RTPs in photonic meta-crystals, characterizing them using the Euler number, and establishing their connection with both Abelian and non-Abelian charges. By considering RTPs as the basic elements, we further propose the concept of a topological compound, akin to a chemical compound, where we find that certain phases are not topologically allowed. The topological classification of RTPs in crystals demonstrated in our work plays a similar role as the 'no-go' theorem in Weyl systems.

cond-mat.mes-hall↗

arXiv2022

A Benchmarking Dataset with 2440 Organic Molecules for Volume Distribution at Steady State

Background: The volume of distribution at steady state (VDss) is a fundamental pharmacokinetics (PK) property of drugs, which measures how effectively a drug molecule is distributed throughout the body. Along with the clearance (CL), it determines the half-life and, therefore, the drug dosing interval. However, the molecular data size limits the generalizability of the reported machine learning models. Objective: This study aims to provide a clean and comprehensive dataset for human VDss as the benchmarking data source, fostering and benefiting future predictive studies. Moreover, several predictive models were also built with machine learning regression algorithms. Methods: The dataset was curated from 13 publicly accessible data sources and the DrugBank database entirely from intravenous drug administration and then underwent extensive data cleaning. The molecular descriptors were calculated with Mordred, and feature selection was conducted for constructing predictive models. Five machine learning methods were used to build regression models, grid search was used to optimize hyperparameters, and ten-fold cross-validation was used to evaluate the model. Results: An enriched dataset of VDss (https://github.com/da-wen-er/VDss) was constructed with 2440 molecules. Among the prediction models, the LightGBM model was the most stable and had the best internal prediction ability with Q2 = 0.837, R2=0.814 and for the other four models, Q2 was higher than 0.79. Conclusions: To the best of our knowledge, this is the largest dataset for VDss, which can be used as the benchmark for computational studies of VDss. Moreover, the regression models reported within this study can be of use for pharmacokinetic related studies.

q-bio.QM↗

arXiv2022

CNN-based Prediction of Network Robustness With Missing Edges

Connectivity and controllability of a complex network are two important issues that guarantee a networked system to function. Robustness of connectivity and controllability guarantees the system to function properly and stably under various malicious attacks. Evaluating network robustness using attack simulations is time consuming, while the convolutional neural network (CNN)-based prediction approach provides a cost-efficient method to approximate the network robustness. In this paper, we investigate the performance of CNN-based approaches for connectivity and controllability robustness prediction, when partial network information is missing, namely the adjacency matrix is incomplete. Extensive experimental studies are carried out. A threshold is explored that if a total amount of more than 7.29\% information is lost, the performance of CNN-based prediction will be significantly degenerated for all cases in the experiments. Two scenarios of missing edge representations are compared, 1) a missing edge is marked `no edge' in the input for prediction, and 2) a missing edge is denoted using a special marker of `unknown'. Experimental results reveal that the first representation is misleading to the CNN-based predictors.

eess.SY↗

arXiv2019

Structured illumination microscopy based on fiber devices

We present a simple and compact approach of structured illumination microscopy by using three $2\times2$ fiber couplers and one $1\times4$ MEMS optics switch. One uniform and three fringe illumination patterns were produced by placing seven output fiber tips at the conjugate Fourier plane of the illumination path. Stable and relatively high-speed illumination switching was achieved by the optics switch. Super-resolution and optical sectioned information was reconstructed from 4-frame data by using algorithms based on a joint Richardson-Lucy deconvolution method and a Hilbert transform method. By directly removing the out-focus components from the raw images provides better imaging results.

physics.optics↗

arXiv2018

Compact and low-cost structured illumination microscopy using an optical fiber coupler

In this paper, a compact and low-cost structured illumination microscope (SIM) based on a 2X2 fiber coupler is presented. Fringe illumination is achieved by placing two output fiber tips at a conjugate Fourier plane of the sample plane as the point sources. Raw structured illumination (SI) images in different pattern orientations are captured when rotating the fiber mount. Following this, high resolution images are reconstructed from no-phase-shift raw SI images by using a joint Richardson-Lucy (jRL) deconvolution algorithm. Compared with an SLM-based SIM system, our method provides a much shorter illumination path, high power efficiency, and low cost.

physics.ins-det↗