arXiv subjects

Xiaoyan Zhou

Publications and source records attributed to Xiaoyan Zhou.

At least 19 recordsLinked to original sources

arXiv2026

MicroVRide: Exploring 4-in-1 Virtual Reality Micromobility Simulator

Micromobility vehicles, such as e-scooters, Segways, skateboards, and unicycles, are increasingly adopted for short-distance travel due to their low weight and low emissions. Despite their growing popularity, we lack controlled, low-risk environments to study rider experiences and performance. While virtual reality (VR) simulators offer a promising approach by reducing safety risks and providing immersive experiences, micromobility simulators remain largely underexplored. We introduce MicroVRide, a modular 4-in-1 VR micromobility simulator that supports e-scooters, Segways, electric unicycles, and one-wheeled skateboards on a single platform. The simulator preserves vehicle-specific physical constraints and control metaphors, enabling the study of diverse riding behaviors with minimal hardware reconfiguration. We contribute the simulator design and report a preliminary within-subject study (N = 12) that demonstrates feasibility and reveals distinct experiential profiles across vehicles.

cs.HC↗

arXiv2026

Enhancing Volumetric Optical Chirality through 2D-3D Structural Design Evolution

Circular dichroism (CD) sensing plays a pivotal role in probing molecular chirality in biomedical sciences. However, engineering superchiral electromagnetic fields that can reliably amplify the faint signatures of chiral analytes remains profoundly challenging. Central to this difficulty is the need to balance two competing demands: maximizing the enhancement of chiral fields while maintaining a sufficiently large interaction volume for effective molecular interrogation. Here, we introduce a figure of merit (FOM) that captures the enhancement and spatial coverage of superchiral fields to benchmark different chiral-field configurations. We examine the effects of helix-geometry evolution on the FOM, including 2D to 3D chirality induction, winding-number escalation, helical-order enhancement, and transverse dilation. By tuning these structural degrees of freedom, the sensing volume can be enlarged without compromising the distribution and enhancement strength of fields. The optimized triple-strand helix markedly enhanced the analyte CD signal, yielding a FOM of 2.43*10^10 nm3, which surpassed prior 2D and 3D configurations by over an order of magnitude. The proposed FOM exhibits a strong linear correlation (R^2 = 0.9256) with the analyte CD signal. Our findings provide a systematic design framework for 3D chiral structures and a robust metric for assessing their chiroptical sensing performance, particularly in scenarios involving clusters of randomly oriented small molecules or a large chiral molecule.

physics.optics↗

arXiv2025

aiXiv: A Next-Generation Open Access Ecosystem for Scientific Discovery Generated by AI Scientists

Recent advances in large language models (LLMs) have enabled AI agents to autonomously generate scientific proposals, conduct experiments, author papers, and perform peer reviews. Yet this flood of AI-generated research content collides with a fragmented and largely closed publication ecosystem. Traditional journals and conferences rely on human peer review, making them difficult to scale and often reluctant to accept AI-generated research content; existing preprint servers (e.g. arXiv) lack rigorous quality-control mechanisms. Consequently, a significant amount of high-quality AI-generated research lacks appropriate venues for dissemination, hindering its potential to advance scientific progress. To address these challenges, we introduce aiXiv, a next-generation open-access platform for human and AI scientists. Its multi-agent architecture allows research proposals and papers to be submitted, reviewed, and iteratively refined by both human and AI scientists. It also provides API and MCP interfaces that enable seamless integration of heterogeneous human and AI scientists, creating a scalable and extensible ecosystem for autonomous scientific discovery. Through extensive experiments, we demonstrate that aiXiv is a reliable and robust platform that significantly enhances the quality of AI-generated research proposals and papers after iterative revising and reviewing on aiXiv. Our work lays the groundwork for a next-generation open-access ecosystem for AI scientists, accelerating the publication and dissemination of high-quality AI-generated research content. Code: https://github.com/aixiv-org aiXiv: https://aixiv.science

cs.AI↗

arXiv2025

Encoding orbital angular momentum of light in space with optical catastrophes

Light beams carrying orbital angular momentum (OAM) possess an unbounded set of orthogonal modes, offering significant potential for optical communication and security. However, exploiting OAM beams in space has been hindered by the lack of a versatile design toolkit. Here, we demonstrate a strategy to tailor OAM across multiple transverse planes by shaping optical caustics leveraging on catastrophe theory. With complex-amplitude metasurfaces fabricated using two-photon polymerization lithography, we construct these caustics to steer Poynting vectors and achieve arbitrary shapes of OAM beams. Interestingly, we use such an approach to realize hidden OAM along the propagation trajectory, where the intensity of the beam is spread out thus avoiding detection. The OAM of these beams can be intrinsic, which avoids OAM distortions arising from the mixing of intrinsic and extrinsic components. By exploiting this intrinsic nature of OAM, we demonstrate the detection of encoded information in optical encryption. Our approach provides a unique framework for dynamic control of OAM in space, with promising applications in optical trapping and sensing, high-capacity data storage, and optical information security.

physics.optics↗

arXiv2025

Packet Header Recognition Utilizing an All-Optical Reservoir Based on Reinforcement-Learning-Optimized Double-Ring Resonator

Optical packet header recognition is an important signal processing task of optical communication networks. In this work, we propose an all-optical reservoir, consisting of integrated double-ring resonators (DRRs) as nodes, for fast and accurate optical packet header recognition. As the delay-bandwidth product (DBP) of the node is a key figure-of-merit in the reservoir, we adopt a deep reinforcement learning algorithm to maximize the DBPs for various types of DRRs, which has the advantage of full parameter space optimization and fast convergence speed. Intriguingly, the optimized DBPs of the DRRs in cascaded, parallel, and embedded configurations reach the same maximum value, which is believed to be the global maximum. Finally, 3-bit and 6-bit packet header recognition tasks are performed with the all-optical reservoir consisting of the optimized cascaded rings, which have greatly reduced chip size and the desired "flat-top" delay spectra. Using this optical computing scheme, word-error rates as low as 5*10-4 and 9*10-4 are achieved for 3-bit and 6-bit packet header recognition tasks, respectively, which are one order of magnitude better than the previously reported values.

eess.SP↗

arXiv2025

An Analysis of Malicious Packages in Open-Source Software in the Wild

The open-source software (OSS) ecosystem suffers from security threats caused by malware.However, OSS malware research has three limitations: a lack of high-quality datasets, a lack of malware diversity, and a lack of attack campaign contexts. In this paper, we first build the largest dataset of 24,356 malicious packages from online sources, then propose a knowledge graph to represent the OSS malware corpus and conduct malware analysis in the wild.Our main findings include (1) it is essential to collect malicious packages from various online sources because their data overlapping degrees are small;(2) despite the sheer volume of malicious packages, many reuse similar code, leading to a low diversity of malware;(3) only 28 malicious packages were repeatedly hidden via dependency libraries of 1,354 malicious packages, and dependency-hidden malware has a shorter active time;(4) security reports are the only reliable source for disclosing the malware-based context. Index Terms: Malicious Packages, Software Analysis

cs.CR↗

arXiv2024

A new exceptional point condition for coupled microresonators with coupled mode theory in space

We derive new exceptional point (EP) conditions of the coupled microring resonators using coupled mode theory in space, a more accurate approach than the commonly used coupled mode theory in time. Transmission spectra around EPs obtained from the two models have been compared on two material platforms, revealing non-negligible deviations. Our analysis provides a guide for accurately determining parameter sets of coupled microrings at EPs and deepens our understanding on parity-time-symmetric coupled resonators at EPs.

physics.optics↗

arXiv2024

Tactics, Techniques, and Procedures (TTPs) in Interpreted Malware: A Zero-Shot Generation with Large Language Models

Nowadays, the open-source software (OSS) ecosystem suffers from security threats of software supply chain (SSC) attacks. Interpreted OSS malware plays a vital role in SSC attacks, as criminals have an arsenal of attack vectors to deceive users into installing malware and executing malicious activities. In this paper, we introduce tactics, techniques, and procedures (TTPs) proposed by MITRE ATT\&CK into the interpreted malware analysis to characterize different phases of an attack lifecycle. Specifically, we propose GENTTP, a zero-shot approach to extracting a TTP of an interpreted malware package. GENTTP leverages large language models (LLMs) to automatically generate a TTP, where the input is a malicious package, and the output is a deceptive tactic and an execution tactic of attack vectors. To validate the effectiveness of GENTTP, we collect two datasets for evaluation: a dataset with ground truth labels and a large dataset in the wild. Experimental results show that GENTTP can generate TTPs with high accuracy and efficiency. To demonstrate GENTTP's benefits, we build an LLM-based Chatbot from 3,700+ PyPI malware's TTPs. We further conduct a quantitative analysis of malware's TTPs at a large scale. Our main findings include: (1) many OSS malicious packages share a relatively stable TTP, even with the increasing emergence of malware and attack campaigns, (2) a TTP reflects characteristics of a malware-based attack, and (3) an attacker's intent behind the malware is linked to a TTP.

cs.CR↗

arXiv2024

A Large-scale Fine-grained Analysis of Packages in Open-Source Software Ecosystems

Package managers such as NPM, Maven, and PyPI play a pivotal role in open-source software (OSS) ecosystems, streamlining the distribution and management of various freely available packages. The fine-grained details within software packages can unveil potential risks within existing OSS ecosystems, offering valuable insights for detecting malicious packages. In this study, we undertake a large-scale empirical analysis focusing on fine-grained information (FGI): the metadata, static, and dynamic functions. Specifically, we investigate the FGI usage across a diverse set of 50,000+ legitimate and 1,000+ malicious packages. Based on this diverse data collection, we conducted a comparative analysis between legitimate and malicious packages. Our findings reveal that (1) malicious packages have less metadata content and utilize fewer static and dynamic functions than legitimate ones; (2) malicious packages demonstrate a higher tendency to invoke HTTP/URL functions as opposed to other application services, such as FTP or SMTP; (3) FGI serves as a distinguishable indicator between legitimate and malicious packages; and (4) one dimension in FGI has sufficient distinguishable capability to detect malicious packages, and combining all dimensions in FGI cannot significantly improve overall performance.

cs.SE↗

arXiv2024

I Did Not Notice: A Comparison of Immersive Analytics with Augmented and Virtual Reality

Immersive environments enable users to engage in embodied interaction, enhancing the sensemaking processes involved in completing tasks such as immersive analytics. Previous comparative studies on immersive analytics using augmented and virtual realities have revealed that users employ different strategies for data interpretation and text-based analytics depending on the environment. Our study seeks to investigate how augmented and virtual reality influences sensemaking processes in quantitative immersive analytics. Our results, derived from a diverse group of participants, indicate that users demonstrate comparable performance in both environments. However, it was observed that users exhibit a higher tolerance for cognitive load in VR and travel further in AR. Based on our findings, we recommend providing users with the option to switch between AR and VR, thereby enabling them to select an environment that aligns with their preferences and task requirements.

cs.HC↗

arXiv2024

An example of an infinite amenable group with the ISR property

Let $G$ be $S_{\mathbb{N}}$, the finitary permutation (i.e. permutations with finite support) group on positive integers $\mathbb{N}$. We prove that $G$ has the invariant von Neumann subalgebras rigidity (ISR, for short) property as introduced in Amrutam-Jiang's work. More precisely, every $G$-invariant von Neumann subalgebra $P\subseteq L(G)$ is of the form $L(H)$ for some normal sugbroup $H\lhd G$ and in this case, $H=\{e\}, A_{\mathbb{N}}$ or $G$, where $A_{\mathbb{N}}$ denotes the finitary alternating group on $\mathbb{N}$, i.e. the subgroup of all even permutations in $S_{\mathbb{N}}$. This gives the first known example of an infinite amenable group with the ISR property.

math.OA↗

arXiv2023

Effective connectivity signatures in major depressive disorder: fMRI study using a multi-site dataset

Diagnosis of major depressive disorder (MDD) primarily relies on the patient's self-reported symptoms and a clinical evaluation. Effective connectivity (EC) from resting-state functional magnetic resonance imaging (rs-fMRI) analysis can reflect the directionality of connections between brain regions, making it a candidate method to classify MDD. This study used Granger causality analysis to extract EC features from a large multi-site MDD dataset. The ComBat algorithm and multivariate linear regression were used to harmonize site difference and to remove age and sex covariates, respectively. Two-sample t-tests and model-based feature selection methods were used to screen for highly discriminative EC features for MDD, and LightGBM was used to classify MDD. In this large-scale multi-site rs-fMRI dataset, 97 EC features deemed highly discriminative for MDD were screened. In the nested five-fold cross-validation, the best classification model with the 97 EC features achieved accuracy, sensitivity, and specificity of 94.35%, 93.52%, and 95.25%, respectively. In another independent large dataset, which tested the generalization performance of the 97 EC features, the best classification models achieved 94.74%, 90.59%, and 96.75% for accuracy, sensitivity, and specificity, respectively. This work demonstrated that EC had a reasonable discriminative ability and supported the notion for using EC to potentially assist clinical diagnosis of MDD.

q-bio.NC↗

arXiv2023

Arbitrary Engineering of Spatial Caustics with 3D-printed Metasurfaces

Caustics occur in diverse physical systems, spanning the nano-scale in electron microscopy to astronomical-scale in gravitational lensing. As envelopes of rays, optical caustics result in sharp edges or extended networks. Caustics in structured light, characterized by complex-amplitude distributions, have innovated numerous applications including particle manipulation, high-resolution imaging techniques, and optical communication. However, these applications have encountered limitations due to a major challenge in engineering caustic fields with customizable propagation trajectories and in-plane intensity profiles. Here, we introduce the compensation phase via 3D-printed metasurfaces to shape caustic fields with curved trajectories in free space. The in-plane caustic patterns can be preserved or morphed from one structure to another during propagation. Large-scale fabrication of these metasurfaces is enabled by the fast-prototyping and cost-effective two-photon polymerization lithography. Our optical elements with the ultra-thin profile and sub-millimeter extension offer a compact solution to generating caustic structured light for beam shaping, high-resolution microscopy, and light-matter-interaction studies.

physics.optics↗

arXiv2023

Data-driven Storytelling in Hybrid Immersive Display Environments

Data-driven stories seek to inform and persuade audiences through the use of data visualisations and engaging narratives. These stories have now been highly optimised to be viewed on desktop and mobile computers. In contrast, while immersive virtual and augmented reality (VR/AR) technologies have been shown to be more persuasive, no clear standard has yet emerged for such immersive stories. With this in mind, we propose that a hybrid data-driven storytelling approach can leverage the familiarity of 2D display devices with the immersiveness and presence afforded by VR/AR headsets. In this position paper, we characterise hybrid data-driven stories by describing its design opportunities, considerations, and challenges. In particular, we describe how both 2D and 3D display environments can play either complementary or symbiotic roles with each other for the purposes of storytelling. We hope that this work inspires researchers to investigate how hybrid user interfaces may be used for storytelling.

cs.HC↗

arXiv2022

A Pilot Study on The Impact of Stereoscopic Display Type on User Interactions Within A Immersive Analytics Environment

Immersive Analytics (IA) and consumer adoption of augmented reality (AR) and virtual reality (VR) head-mounted displays (HMDs) are both rapidly growing. When used in conjunction, stereoscopic IA environments can offer improved user understanding and engagement; however, it is unclear how the choice of stereoscopic display impacts user interactions within an IA environment. This paper presents a pilot study that examines the impact of stereoscopic display type on object manipulation and environmental navigation using consumer-available AR and VR displays. This work finds that the display type can impact how users manipulate virtual content, how they navigate the environment, and how able they are to answer questions about the represented data.

cs.HC↗

arXiv2022

Eliciting Multimodal Gesture+Speech Interactions in a Multi-Object Augmented Reality Environment

As augmented reality technology and hardware become more mature and affordable, researchers have been exploring more intuitive and discoverable interaction techniques for immersive environments. In this paper, we investigate multimodal interaction for 3D object manipulation in a multi-object virtual environment. To identify the user-defined gestures, we conducted an elicitation study involving 24 participants for 22 referents with an augmented reality headset. It yielded 528 proposals and generated a winning gesture set with 25 gestures after binning and ranking all gesture proposals. We found that for the same task, the same gesture was preferred for both one and two object manipulation, although both hands were used in the two object scenario. We presented the gestures and speech results, and the differences compared to similar studies in a single object virtual environment. The study also explored the association between speech expressions and gesture stroke during object manipulation, which could improve the recognizer efficiency in augmented reality headsets.

cs.HC↗

arXiv2022

A Pure and indistinguishable single-photon source at telecommunication wavelength

On-demand single-photon sources emitting pure and indistinguishable photons at the telecommunication wavelength are a critical asset towards the deployment of fiber-based quantum networks. Indeed, single photons may serve as flying qubits, allowing communication of quantum information over long distances. Self-assembled InAs quantum dots embedded in GaAs constitute an excellent nearly deterministic source of high quality single photons, but the vast majority of sources operate in the 900-950 nm wavelength range, precluding their adoption in a quantum network. Here, we present a quantum frequency conversion scheme for converting single photons from quantum dots to the telecommunication C band, around 1550 nm, achieving 40.8% end-to-end efficiency, while maintaining both high purity and a high degree of indistinguishability during conversion with measured values of $g^{(2)}(0)=2.4\%$ and $V^{\text{corr}}=94.8\%$, respectively.

quant-ph↗

arXiv2021

In-plane resonant excitation of quantum dots in a dual-mode photonic-crystal waveguide with high $β$-factor

A high-quality quantum dot (QD) single-photon source is a key resource for quantum information processing. Exciting a QD emitter resonantly can greatly suppress decoherence processes and lead to highly indistinguishable single-photon generation. It has, however, remained a challenge to implement strict resonant excitation in a stable and scalable way, without compromising any of the key specs of the source (efficiency, purity, and indistinguishability). In this work, we propose a novel dual-mode photonic-crystal waveguide that realizes direct in-plane resonant excitation of the embedded QDs. The device relies on a two-mode waveguide design, which allows exploiting one mode for excitation of the QD and the other mode for collecting the emitted single photons with high efficiency. By proper engineering of the photonic bandstructure, we propose a design with single-photon collection efficiency of $β> 0.95$ together with a single-photon impurity of $ε< 5 \times 10^{-3}$ over a broad spectral and spatial range. The device has a compact footprint of $\sim 50$ $μ$m$^2$ and would enable stable and scalable excitation of multiple emitters for multi-photon quantum applications.

quant-ph↗