Zobrazeno 1 - 10
of 33 210
pro vyhledávání: '"Yang BO"'
Autor:
Yang, Bo
We present here a complete microscopic theory of a family of neutral excitations in the fractional quantum Hall fluids, related to the geometric fluctuations of the quantum Hall ground states. Many of the physical properties of such geometric modes c
Externí odkaz:
http://arxiv.org/abs/2411.05076
The gravitational deflection of light signals restricted in the polar-axis plane of a moving Kerr-Newman (KN) black hole with a constant velocity along the polar axis is studied within the second post-Minkowskian (PM) approximation. For this purpose,
Externí odkaz:
http://arxiv.org/abs/2411.03808
Autor:
Liang, Ruihuai, Yang, Bo, Chen, Pengyu, Li, Xianjin, Xue, Yifan, Yu, Zhiwen, Cao, Xuelin, Zhang, Yan, Debbah, Mérouane, Poor, H. Vincent, Yuen, Chau
Network optimization is a fundamental challenge in the Internet of Things (IoT) network, often characterized by complex features that make it difficult to solve these problems. Recently, generative diffusion models (GDMs) have emerged as a promising
Externí odkaz:
http://arxiv.org/abs/2411.00453
Defense hardening can effectively enhance the resilience of distribution networks against extreme weather disasters. Currently, most existing hardening strategies focus on reducing load shedding. However, for electricity-hydrogen distribution network
Externí odkaz:
http://arxiv.org/abs/2410.20475
Autor:
Yang, Bo-Shun, Hoffmann, Susanne M
Publikováno v:
Res. Astron. Astrophys, 11 (2024)
In recent astronomical discussions, attempts have been made to link the known dwarf nova Z Cam to historical celestial events, particularly the "guest star" phenomenon reported in China in 77 BCE. Despite other suggestions and the problems with regar
Externí odkaz:
http://arxiv.org/abs/2410.19010
Enhancing SNN-based Spatio-Temporal Learning: A Benchmark Dataset and Cross-Modality Attention Model
Spiking Neural Networks (SNNs), renowned for their low power consumption, brain-inspired architecture, and spatio-temporal representation capabilities, have garnered considerable attention in recent years. Similar to Artificial Neural Networks (ANNs)
Externí odkaz:
http://arxiv.org/abs/2410.15689
Autor:
Wang, Zhichao, Chen, Xinhai, Gong, Chunye, Yang, Bo, Deng, Liang, Sun, Yufei, Pang, Yufei, Liu, Jie
Mesh smoothing methods can enhance mesh quality by eliminating distorted elements, leading to improved convergence in simulations. To balance the efficiency and robustness of traditional mesh smoothing process, previous approaches have employed super
Externí odkaz:
http://arxiv.org/abs/2410.19834
Graph Neural Networks (GNNs) have become the de facto standard for analyzing graph-structured data, leveraging message-passing techniques to capture both structural and node feature information. However, recent studies have raised concerns about the
Externí odkaz:
http://arxiv.org/abs/2410.15241
Graph classification in medical imaging and drug discovery requires accuracy and robust uncertainty quantification. To address this need, we introduce Conditional Prediction ROC (CP-ROC) bands, offering uncertainty quantification for ROC curves and r
Externí odkaz:
http://arxiv.org/abs/2410.15239
High renewable energy penetration into power distribution systems causes a substantial risk of exceeding voltage security limits, which needs to be accurately assessed and properly managed. However, the existing methods usually rely on the joint prob
Externí odkaz:
http://arxiv.org/abs/2410.12438