Zobrazeno 1 - 10
of 5 714
pro vyhledávání: '"Du, Yi."'
Autor:
Wang, Can, Liu, Feng-Ming, Chen, He, Du, Yi-Fei, Ying, Chong, Wang, Jian-Wen, Huo, Yong-Heng, Peng, Cheng-Zhi, Zhu, Xiaobo, Chen, Ming-Cheng, Lu, Chao-Yang, Pan, Jian-Wei
Despite the significant progress in superconducting quantum computation over the past years, quantum state measurement still lags nearly an order of magnitude behind quantum gate operations in speed and fidelity. The main challenge is that the strong
Externí odkaz:
http://arxiv.org/abs/2412.13849
Autor:
Yang, Ming, Zhao, Wenxuan, Mu, Dan, Shi, Zhijian, Zhong, Jingyuan, Li, Yaqi, Liu, Yundan, Zhong, Jianxin, Cheng, Ningyan, Zhou, Wei, Wang, Jianfeng, Shi, Yan, Sun, Ying, Hao, Weichang, Yang, Lexian, Zhuang, Jincheng, Du, Yi
Publikováno v:
Physical Review Letters 133, 256601 (2024)
Massive Dirac fermions, which are essential for realizing novel topological phenomena, are expected to be generated from massless Dirac fermions by breaking the related symmetry, such as time-reversal symmetry (TRS) in topological insulators or cryst
Externí odkaz:
http://arxiv.org/abs/2412.13457
Autor:
Biguri, Ander, Sadakane, Tomoyuki, Lindroos, Reuben, Liu, Yi, Landman, Malena Sabaté, Du, Yi, Lohvithee, Manasavee, Kaser, Stefanie, Hatamikia, Sepideh, Bryll, Robert, Valat, Emilien, Wonglee, Sarinrat, Blumensath, Thomas, Schönlieb, Carola-Bibiane
Computed Tomography (CT) has been widely adopted in medicine and it is increasingly being used in scientific and industrial applications. Parallelly, research in different mathematical areas concerning discrete inverse problems has led to the develop
Externí odkaz:
http://arxiv.org/abs/2412.10129
We apply a Dense Neural Network (DNN) approach to reconstruct jet momentum within a quark-gluon plasma (QGP) background, using simulated data from PYTHIA and Linear Boltzmann Transport (LBT) Models for comparative analysis. We find that medium respon
Externí odkaz:
http://arxiv.org/abs/2412.06466
Derivative-free optimization (DFO) is vital in solving complex optimization problems where only noisy function evaluations are available through an oracle. Within this domain, DFO via finite difference (FD) approximation has emerged as a powerful met
Externí odkaz:
http://arxiv.org/abs/2411.00112
Quantum sensing utilize quantum effects, such as entanglement and coherence, to measure physical signals. The performance of a sensing process is characterized by error which requires comparison to a true value. However, in practice, such a true valu
Externí odkaz:
http://arxiv.org/abs/2410.20759
We introduce a novel deep learning framework based on Long Short-Term Memory (LSTM) networks to predict galactic cosmic-ray spectra on a one-day-ahead basis by leveraging historical solar activity data, overcoming limitations inherent in traditional
Externí odkaz:
http://arxiv.org/abs/2410.21046
We extract the leading Fock-state light front wave functions (LF-LFWFs) of heavy flavor-asymmetric pseudoscalar mesons $D$, $B$ and $B_c$ from their Bethe-Salpeter wave functions based on Dyson-Schwinger equations approach, and study their leading tw
Externí odkaz:
http://arxiv.org/abs/2409.05098
The construction of Ekman boundary layer solutions near the non-flat boundaries presents a complex challenge, with limited research on this issue. In Masmoudi's pioneering work [Comm. Pure Appl. Math. 53 (2000), 432--483], the Ekman boundary layer so
Externí odkaz:
http://arxiv.org/abs/2408.07582
Autor:
Wang, Chen, Ji, Kaiyi, Geng, Junyi, Ren, Zhongqiang, Fu, Taimeng, Yang, Fan, Guo, Yifan, He, Haonan, Chen, Xiangyu, Zhan, Zitong, Du, Qiwei, Su, Shaoshu, Li, Bowen, Qiu, Yuheng, Du, Yi, Li, Qihang, Yang, Yifan, Lin, Xiao, Zhao, Zhipeng
Data-driven methods such as reinforcement and imitation learning have achieved remarkable success in robot autonomy. However, their data-centric nature still hinders them from generalizing well to ever-changing environments. Moreover, collecting larg
Externí odkaz:
http://arxiv.org/abs/2406.16087