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Your search keyword '"Lv, Wenkai"' showing total 21 results
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21 results on '"Lv, Wenkai"'

1. Negligible Normal Fluid in Superconducting State of Heavily Overdoped Bi$_2$Sr$_2$CaCu$_2$O$_{8+\delta}$ Detected by Ultra-Low Temperature Angle-Resolved Photoemission Spectroscopy

Author

Yin, Chaohui, Wang, Qinghong, Xie, Yuyang, Chen, Yiwen, Liu, Junhao, Yang, Jiangang, Jia, Junjie, Zhang, Xing, Lv, Wenkai, Yan, Hongtao, Rong, Hongtao, Zhang, Shenjin, Wang, Zhimin, Zong, Nan, Liu, Lijuan, Li, Rukang, Wang, Xiaoyang, Zhang, Fengfeng, Yang, Feng, Peng, Qinjun, Xu, Zuyan, Liu, Guodong, Mao, Hanqing, Zhao, Lin, Li, Xintong, and Zhou, Xingjiang

Subjects
Condensed Matter - Superconductivity
Abstract

In high temperature cuprate superconductors, it was found that in the overdoped region the superfluid density decreases with the increase of hole doping. One natural question is whether there exists normal fluid in the superconducting state in the overdoped region. In this paper, we have carried out high-resolution ultra-low temperature laser-based angle-resolved photoemission measurements on a heavily overdoped Bi2212 sample with a $T_{\mathrm{c}}$ of 48 K. We find that this heavily overdoped Bi2212 remains in the strong coupling regime with $2 \mathit{\Delta}_0 / k_{\mathrm{B}} T_{\mathrm{c}}=5.8$. The single-particle scattering rate is very small along the nodal direction ($\sim$5 meV) and increases as the momentum moves from the nodal to the antinodal regions. A hard superconducting gap opening is observed near the antinodal region with the spectral weight at the Fermi level fully suppressed to zero. The normal fluid is found to be negligibly small in the superconducting state of this heavily overdoped Bi2212. These results provide key information to understand the high $T_\mathrm{c}$ mechanism in the cuprate superconductors., Comment: 13 pages, 4 figures

Published
2024
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10. Research on Hybrid Recommendation Model for Personalized Recommendation Scenarios

Author

Lv, Wenkai Ni, Yanhui Du, Xingbang Ma, and Haibin

Subjects
RippleNet, preference propagation, hybrid recommendation, user portrait
Abstract

One of the five types of Internet information service recommendation technologies is the personalized recommendation algorithm, and knowledge graphs are frequently used in these algorithms. RippleNet is a personalized recommendation model based on knowledge graphs, but it is susceptible to localization issues in user portrait updating. In this study, we propose NRH (Node2vec-side and RippleNet Hybrid Model), a hybrid recommendation model based on RippleNet that uses Node2vec-side for item portrait modeling and explores potential association relationships of items; the user portrait is split into two parts, namely, a static history portrait and a dynamic preference portrait; the NRH model adopts a hybrid recommendation approach based on collaborative filtering and a knowledge graph to obtain the user’s preferences on three publicly accessible datasets; and comparison experiments with the mainstream model are lastly carried out. The AUC and ACC increased, respectively, by 0.9% to 29.5% and 1.6% to 31.4% in the MovieLens-1M dataset, by 1.5% to 17.1% and 4.4% to 18.7% in the Book-Crossing dataset, and by 0.8% to 27.9% and 2.9% to 24.1% in the Last.FM dataset. The RippleNet model was used for comparison experiments comparing suggestion diversity. According to the experimental findings, the NRH model performs better in accuracy and variety than the popular customized knowledge graph recommendation algorithms now in use.

Published
2023
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15. Energy-Efficient and QoS-Aware Computation Offloading in GEO/LEO Hybrid Satellite Networks.

Author

Lv, Wenkai, Yang, Pengfei, Ding, Yunqing, Wang, Zhenyi, Lin, Chengmin, and Wang, Quan

Subjects
*ENERGY conservation, *ENERGY consumption, *POLYNOMIAL time algorithms, *NONLINEAR programming, *QUALITY of service, *SPACE-based radar
Abstract

Benefiting from advanced satellite payload technologies, edge computing servers can be deployed on satellites to achieve orbital computing and reduce the mission processing delay. However, geostationary Earth orbit (GEO) satellites are hindered by long-distance communication, whereas low Earth orbit (LEO) satellites are restricted by time windows. Relying solely on GEO or LEO satellites cannot meet the strict quality of service (QoS) requirements of on-board missions while conserving energy consumption. In this paper, we propose a computation offloading strategy for GEO/LEO hybrid satellite networks that minimizes total energy consumption while guaranteeing the QoS requirements of multiple missions. We first innovatively transform the on-board partial computation offloading problem, which is a mixed-integer nonlinear programming (MINLP) problem, into a minimum cost maximum flow (MCMF) problem. Then, the successive shortest path-based computation offloading (SSPCO) method is introduced to obtain the offloading decision in polynomial time. To evaluate the effectiveness and performance of SSPCO, we conduct a series of numerical experiments and compare SSPCO with other offloading methods. The experimental results demonstrate that our proposed SSPCO outperforms the reference methods in terms of total energy consumption, QoS violation degree, and algorithm running time. [ABSTRACT FROM AUTHOR]

Published
2023
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