Zobrazeno 1 - 10
of 6 616
pro vyhledávání: '"gao, Qi"'
This study develops an effective theoretical framework that couples two vector fields: the velocity field $\mathbf{u}$ and an auxiliary vorticity field $\boldsymbol{\xi}$. Together, these fields form a larger conserved dynamical system. Within this f
Externí odkaz:
http://arxiv.org/abs/2410.18667
Current automatic deep learning (i.e., AutoDL) frameworks rely on training feedback from actual runs, which often hinder their ability to provide quick and clear performance predictions for selecting suitable DL systems. To address this issue, we pro
Externí odkaz:
http://arxiv.org/abs/2410.14743
Verifiable formal languages like Lean have profoundly impacted mathematical reasoning, particularly through the use of large language models (LLMs) for automated reasoning. A significant challenge in training LLMs for these formal languages is the la
Externí odkaz:
http://arxiv.org/abs/2410.10878
Autor:
Kanno, Shu, Sugisaki, Kenji, Nakamura, Hajime, Yamauchi, Hiroshi, Sakuma, Rei, Kobayashi, Takao, Gao, Qi, Yamamoto, Naoki
We develop an energy calculation algorithm leveraging quantum phase difference estimation (QPDE) scheme and a tensor-network-based unitary compression method in the preparation of superposition states and time-evolution gates. Alongside its efficient
Externí odkaz:
http://arxiv.org/abs/2408.04946
Feature extraction is a critical technology to realize the automatic transmission of feature information throughout product life cycles. As CAD models primarily capture the 3D geometry of products, feature extraction heavily relies on geometric infor
Externí odkaz:
http://arxiv.org/abs/2406.18543
We analyze the static response to kinetic perturbations of nonequilibrium steady states that can be modeled as diffusions. We demonstrate that kinetic response is purely a nonequilibirum effect, measuring the degree to which the Fluctuation-Dissipati
Externí odkaz:
http://arxiv.org/abs/2404.09860
Autor:
Ding, Ming-Yi, Shi, Jian-Rong, Yan, Hong-liang, Li, Chun-Qian, Gao, Qi, Chen, Tian-Yi, Zhang, Jing-Hua, Liu, Shuai, Xie, Xiao-Jin, Tang, Yao-Jia, Zhou, Ze-Ming, Wang, Jiang-Tao
Lithium is a fragile but crucial chemical element in the universe, exhibits interesting and complex behaviors. Thanks to the massive spectroscopic data from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) medium-resolution surv
Externí odkaz:
http://arxiv.org/abs/2403.01815
Autor:
Hu, Pei-Jin, Chen, Qi-Ling, Chen, Tian-Lu, Kang, Ming-Ming, Guo, Yi-Qing, Luo-Bu, Dan-Zeng, Feng, You-Liang, Gao, Qi, Gou, Quan-Bu, Hu, Hong-Bo, Li, Hai-Jin, Liu, Cheng, Liu, Mao-Yuan, Liu, Wei, Qian, Xiang-Li, Qiao, Bing-Qiang, Su, Jing-Jing, Sun, Hui-Ying, Wang, Xu, Wang, Zhen, Xin, Guang-Guang, Yang, Chao-Wen, Yao, Yu-Hua, Yuan, Qiang, Zhang, Yi
The detection of GW170817/GRB170817A implied the strong association between short gamma-ray bursts (SGRBs) and binary neutron star (BNS) mergers which produce gravitational waves (GWs). More evidence is needed to confirm the association and reveal th
Externí odkaz:
http://arxiv.org/abs/2401.11399
Autor:
Yasuda, Toshiki, Suzuki, Yudai, Kubota, Tomoyuki, Nakajima, Kohei, Gao, Qi, Zhang, Wenlong, Shimono, Satoshi, Nurdin, Hendra I., Yamamoto, Naoki
Reservoir computing is a machine learning framework that uses artificial or physical dissipative dynamics to predict time-series data using nonlinearity and memory properties of dynamical systems. Quantum systems are considered as promising reservoir
Externí odkaz:
http://arxiv.org/abs/2310.06706
Autor:
Huang, Hanzi, Chen, Haoshuo, Gao, Qi, Huang, Yetian, Fontaine, Nicolas K., Mazur, Mikael, Dallachiesa, Lauren, Ryf, Roland, Li, Zhengxuan, Song, Yingxiong
We experimentally investigate transmitting high-order quadrature amplitude modulation (QAM) signals with carrierless and intensity-only measurements with phase retrieval (PR) receiving techniques. The intensity errors during measurement, including no
Externí odkaz:
http://arxiv.org/abs/2310.05314