Weak antilocalization and electron-electron interaction in coupled multiple-channel transport in a Bi2_2Se3_3 thin film

Electron transport properties of a topological insulator Bi$_2$Se$_3$ thin film are studied in Hall-bar geometry. The film with a thickness of 10 nm is grown by van der Waals epitaxy on fluorophlogopite mica and Hall-bar devices are fabricated from the as-grown film directly on the mica substrate. Weak antilocalization and electron-electron interaction effects are observed and analyzed at low temperatures. The phase-coherence length extracted from the measured weak antilocalization characteristics shows a strong power-law increase with decreasing temperature and the transport in the film is shown to occur via coupled multiple (topological surface and bulk states) channels. The conductivity of the film shows a logarithmically decrease with decreasing temperature and thus the electron-electron interaction plays a dominant role in quantum corrections to the conductivity of the film at low temperatures.Comment: 12 pages, 5 figure

Adversarial Camouflage for Node Injection Attack on Graphs

Node injection attacks against Graph Neural Networks (GNNs) have received emerging attention as a practical attack scenario, where the attacker injects malicious nodes instead of modifying node features or edges to degrade the performance of GNNs. Despite the initial success of node injection attacks, we find that the injected nodes by existing methods are easy to be distinguished from the original normal nodes by defense methods and limiting their attack performance in practice. To solve the above issues, we devote to camouflage node injection attack, i.e., camouflaging injected malicious nodes (structure/attributes) as the normal ones that appear legitimate/imperceptible to defense methods. The non-Euclidean nature of graph data and the lack of human prior brings great challenges to the formalization, implementation, and evaluation of camouflage on graphs. In this paper, we first propose and formulate the camouflage of injected nodes from both the fidelity and diversity of the ego networks centered around injected nodes. Then, we design an adversarial CAmouflage framework for Node injection Attack, namely CANA, to improve the camouflage while ensuring the attack performance. Several novel indicators for graph camouflage are further designed for a comprehensive evaluation. Experimental results demonstrate that when equipping existing node injection attack methods with our proposed CANA framework, the attack performance against defense methods as well as node camouflage is significantly improved

Robust Recommender System: A Survey and Future Directions

With the rapid growth of information, recommender systems have become integral for providing personalized suggestions and overcoming information overload. However, their practical deployment often encounters "dirty" data, where noise or malicious information can lead to abnormal recommendations. Research on improving recommender systems' robustness against such dirty data has thus gained significant attention. This survey provides a comprehensive review of recent work on recommender systems' robustness. We first present a taxonomy to organize current techniques for withstanding malicious attacks and natural noise. We then explore state-of-the-art methods in each category, including fraudster detection, adversarial training, certifiable robust training against malicious attacks, and regularization, purification, self-supervised learning against natural noise. Additionally, we summarize evaluation metrics and common datasets used to assess robustness. We discuss robustness across varying recommendation scenarios and its interplay with other properties like accuracy, interpretability, privacy, and fairness. Finally, we delve into open issues and future research directions in this emerging field. Our goal is to equip readers with a holistic understanding of robust recommender systems and spotlight pathways for future research and development

Retrieval of cavity-generated atomic spin squeezing after free-space release

We demonstrate that releasing atoms into free space from an optical lattice does not deteriorate cavity-generated spin squeezing for metrological purposes. In this work, an ensemble of 500000 spin-squeezed atoms in a high-finesse optical cavity with near-uniform atom-cavity coupling is prepared, released into free space, recaptured in the cavity, and probed. Up to ∼10 dB of metrologically relevant squeezing is retrieved for 700μs free-fall times, and decaying levels of squeezing are realized for up to 3 ms free-fall times. The degradation of squeezing results from loss of atom-cavity coupling homogeneity between the initial squeezed state generation and final collective state readout. A theoretical model is developed to quantify this degradation and this model is experimentally validated

Abnormal Topology of the Structural Connectome in the Limbic Cortico-Basal-Ganglia Circuit and Default-Mode Network Among Primary Insomnia Patients

Purpose: Primary insomnia (PI) is the second most common mental disorder. However, the topologic alterations in structural brain connectome in patients with PI remain largely unknown.Methods: A total of 44 PI patients and 46 age-, gender-, and education level matched healthy control (HC) participants were recruited in this study. Diffusion tensor imaging (DTI) and resting state MRI were used to construct structural connectome for each participant, and the network parameters were employed by non-parametric permutations to evaluate the significant differences between the two groups. Relationships between abnormal network metrics and clinical characteristics, including the disease duration, the Pittsburgh Sleep Quality Index (PSQI), the Insomnia Severity Index (ISI), the Self-Rating Anxiety Scale (SAS), and the Self-Rating Depression Scale (SDS), were investigated with Spearman’s correlation analysis in PI patients.Results: PI patients demonstrated small-world architecture with lower global (P = 0.005) and local (P = 0.035) efficiencies compared with the HC group. The unique hub nodal properties in PI patients were mainly in the right limbic cortico-basal-ganglia circuit. Five disrupted subnetworks in PI patients were observed in the limbic cortico-basal-ganglia circuit and left default-mode networks (DMN) (P < 0.05, NBS corrected). Moreover, most unique hub nodal properties in the right limbic cortico-basal-ganglia circuit were significantly correlated with disease duration, and clinical characteristics (SAS, SDS, ISI scores) in PI processing.Conclusion: These findings suggested the abnormal anatomical network architecture may be closely linked to clinical characteristics in PI. The study provided novel insights into the neural substrates underlying symptoms and neurophysiologic mechanisms of PI