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1,195 results on '"Guan, Dong"'

1. Topological flat bands in hyperbolic lattices

Author

Guan, Dong-Hao, Qi, Lu, Zhou, Yuan, He, Ai-Lei, and Wang, Yi-Fei

Subjects
Condensed Matter - Strongly Correlated Electrons
Abstract

Topological flat bands (TFBs) provide a promising platform to investigate intriguing fractionalization phenomena, such as the fractional Chern insulators (FCIs). Most of TFB models are established in two-dimensional Euclidean lattices with zero curvature. In this work, we systematically explore TFBs in a class of two-dimensional non-Euclidean lattices with constant negative curvature, {\emph i.e.,} the hyperbolic analogs of the kagome lattice. Based on the Abelian hyperbolic band theory, TFBs have been respectively found in the heptagon-kagome, the octagon-kagome, the nonagon-kagome and the decagon-kagome lattices by introducing staggered magnetic fluxes and the next nearest-neighbor hoppings. The flatness ratios of all hyperbolic TFB models are more than 15, which suggests that the hyperbolic FCIs can be realized in these TFB models. We further demonstrate the existence of a $\nu=1/2$ FCI state with open boundary conditions when hard-core bosons fill into these hyperbolic TFB models., Comment: 7 pages, 5 figures, comments are welcome

Published
2024

2. Dissipationless topological quantum computation for Majorana objects in sparse-dense mixed encoding process

Author

Zhan, Ye-Min, Mao, Guan-Dong, Chen, Yu-Ge, Yu, Yue, and Luo, Xi

Subjects
Quantum Physics, Condensed Matter - Strongly Correlated Electrons
Abstract

Topological quantum computation based on Majorana objects is subject to a significant challenge because at least some of the two-qubit quantum gates rely on the fermion (either charge or spin) parity of the qubits. This dependency renders the quantum operations involving these gates probabilistic when attempting to advance quantum processes within the quantum circuit model. Such an approach leads to significant information loss whenever measurements yield the undesired fermion parity. To resolve the problem of wasting information, we devise topological operations that allow for the non-dissipative correction of information from undesired fermion parity to the desired one. We will use the sparse-dense mixed encoding process for the controlled-NOT gate as an example to explain how corrections can be implemented without affecting the quantum information carried by the computational qubits. This correction process can be applied {to} either the undesired input qubits or the fermion parity-dependent quantum gates, and it works for both Majorana-zero-mode-based and Majorana-edge-mode-based topological quantum computation., Comment: 9 pages, 5 figures, accepted by PRA

Published
2024
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14. Long ⁃ term outcome of intracranial ⁃ intracranial side ⁃ to ⁃ side bypass for complex intracranial aneurysms

Author

LIU Yuan, TONG Zhi-yong, YU Guan-dong, ZHAO Xu-dong, and CHU Jin-gang

Subjects
intracranial aneurysm, anterior cerebral artery, middle cerebral artery, cerebral revascularization, intracranial-intracranial (not in mesh), side-to-side anastomosis (not in mesh), Neurology. Diseases of the nervous system, RC346-429
Abstract

Objective To explore the long-term outcome of intracranial-intracranial side-to-side bypass for complex intracranial aneurysms. Methods Five patients with complex intracranial aneurysms underwent intracranial-intracranial side-to-side bypass performed by the same surgeon at The First Hospital of China Medical University from January 2015 to December 2023 were included. Two cases involved the A2 segment of anterior cerebral artery (ACA) and 3 cases involved the M2 segment of middle cerebral artery (MCA). Indocyanine green angiography (ICGA) was used intraoperatively, and CTA or DSA was used postoperatively to evaluate aneurysm occlusion and blood flow reconstruction. The modified Rankin Scale (mRS) was used to evaluate the neurological prognosis at one week, 3 months and the last follow-up. CT/ MRI examination was completed on the first day, one week and 3 months after operation to evaluate whether hemorrhagic or ischemic complications occurred. Results Five cases of complex intracranial aneurysms were all occluded accurately. Two cases underwent A3-A3 side-to-side anastomosis, and 3 cases underwent M2-M2 side-to-side anastomosis, among which one case added M1-radial artery (RA)-M2 intracranialintracranial bypass with RA as graft on the basis of M2-M2 side-to-side anastomosis. During the operation, ICGA confirmed that the side-to-side anastomosis and M1-RA-M2 bypass were unobstructed in 5 cases. The postoperative follow - up time was 23 (14, 71) months. No aneurysm was found in cerebrovascular imaging examination one week and 3 months after operation in 5 patients, and 9 to 12 months after operation in 3 patients. Five side - to - side anastomosis stomas and one M1 - RA - M2 graft were all unobstructed. At one week after operation, the mRS increased by 0-3 score compared with that before operation (4 score maintained unchanged before and after operation in one case, 2 score increased in one case, and 3 score increased in one case). In 2 unruptured cases, the mRS score was 1 score at one week after operation, and there was no change from that before operation. At 3 months after operation, the mRS scores of 5 cases were decreased (2 cases with 0 score, one case with 2 score, and 2 cases with 3 score); one case was lost at the last follow-up, and the mRS scores of other 4 cases decreased further (2 cases with 0 score, one case with 1 score, and one case with 2 score). No cerebral hemorrhage or cerebral ischemia occurred in the follow-up. Conclusions Intracranial-intracranial side-to-side bypass has good short-term and long-term patency and stable long-term clinical effect. It is a reliable technique for surgical treatment of complex intracranial aneurysms.

Published
2024
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15. Structural Stability Analysis of a High Power PEMFC Stack

Author

Chen, Ting, Pan, Jie, Zhang, Xiao, Guan, Dong, Chen, Zhen, Chaari, Fakher, Series Editor, Gherardini, Francesco, Series Editor, Ivanov, Vitalii, Series Editor, Haddar, Mohamed, Series Editor, Cavas-Martínez, Francisco, Editorial Board Member, di Mare, Francesca, Editorial Board Member, Kwon, Young W., Editorial Board Member, Tolio, Tullio A. M., Editorial Board Member, Trojanowska, Justyna, Editorial Board Member, Schmitt, Robert, Editorial Board Member, Xu, Jinyang, Editorial Board Member, Halgamuge, Saman K., editor, Zhang, Hao, editor, Zhao, Dingxuan, editor, and Bian, Yongming, editor

Published
2024
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16. Uniform Load Assembly Method of PEMFC Under Vibration Based on the Wave Spring Suspension Support

Author

Pan, Biyu, Guan, Dong, Wang, Rui, Chen, Zhen, Chen, Ting, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Jing, Xingjian, editor, Ding, Hu, editor, Ji, Jinchen, editor, and Yurchenko, Daniil, editor

Published
2024
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21. Continual Transfer Learning for Cross-Domain Click-Through Rate Prediction at Taobao

Author

Liu, Lixin, Wang, Yanling, Wang, Tianming, Guan, Dong, Wu, Jiawei, Chen, Jingxu, Xiao, Rong, Zhu, Wenxiang, and Fang, Fei

Subjects
Computer Science - Information Retrieval
Abstract

As one of the largest e-commerce platforms in the world, Taobao's recommendation systems (RSs) serve the demands of shopping for hundreds of millions of customers. Click-Through Rate (CTR) prediction is a core component of the RS. One of the biggest characteristics in CTR prediction at Taobao is that there exist multiple recommendation domains where the scales of different domains vary significantly. Therefore, it is crucial to perform cross-domain CTR prediction to transfer knowledge from large domains to small domains to alleviate the data sparsity issue. However, existing cross-domain CTR prediction methods are proposed for static knowledge transfer, ignoring that all domains in real-world RSs are continually time-evolving. In light of this, we present a necessary but novel task named Continual Transfer Learning (CTL), which transfers knowledge from a time-evolving source domain to a time-evolving target domain. In this work, we propose a simple and effective CTL model called CTNet to solve the problem of continual cross-domain CTR prediction at Taobao, and CTNet can be trained efficiently. Particularly, CTNet considers an important characteristic in the industry that models has been continually well-trained for a very long time. So CTNet aims to fully utilize all the well-trained model parameters in both source domain and target domain to avoid losing historically acquired knowledge, and only needs incremental target domain data for training to guarantee efficiency. Extensive offline experiments and online A/B testing at Taobao demonstrate the efficiency and effectiveness of CTNet. CTNet is now deployed online in the recommender systems of Taobao, serving the main traffic of hundreds of millions of active users., Comment: Accepted by WWW 2023 industry track

Published
2022

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