Evidence of the side jump mechanism in the anomalous Hall effect in paramagnets

Persistent confusion has existed between the intrinsic (Berry curvature) and the side jump mechanisms of anomalous Hall effect (AHE) in ferromagnets. We provide unambiguous identification of the side jump mechanism, in addition to the skew scattering contribution in epitaxial paramagnetic Ni$_{34}$Cu$_{66}$ thin films, in which the intrinsic contribution is by definition excluded. Furthermore, the temperature dependence of the AHE further reveals that the side jump mechanism is dominated by the elastic scattering

Proper Scaling of the Anomalous Hall Effect

Working with epitaxial films of Fe, we succeeded in independent control of different scattering processes in the anomalous Hall effect. The result appropriately accounted for the role of phonons, thereby clearly exposing the fundamental flaws of the standard plot of the anomalous Hall resistivity versus longitudinal resistivity. A new scaling has been thus established that allows an unambiguous identification of the intrinsic Berry curvature mechanism as well as the extrinsic skew scattering and side-jump mechanisms of the anomalous Hall effect.Comment: 5 pages, 4 figure

Sequential Recommendation Based on Objective and Subjective Features

Nowadays, sequential recommender systems are widely used in E-commerce fields to capture consumers’ dynamic preferences in short terms. Existing transformer-based recommendation models mainly consider consumer preference for the products and some related features, such as price. However, besides such objective features, some subjective features, such as consumers’ preference for product quality, also affect consumers’ purchase decisions. In this paper, we design a Sequential Recommender system based on Objective and Subjective features (SROS). We construct subjective features by using natural language processing to analyze online consumer reviews. Then we design a feature-level multi-head self-attention to explore the interactions between objective features and subjective features and capture consumers’ dynamic preferences for them among different purchases. Experimental results on real-world datasets demonstrate the effectiveness of the proposed model