Zobrazeno 1 - 10
of 434
pro vyhledávání: '"Yàn, Xióng"'
In recent years we have witnessed a growth in mathematics for deep learning, which has been used to solve inverse problems of partial differential equations (PDEs). However, most deep learning-based inversion methods either require paired data or nec
Externí odkaz:
http://arxiv.org/abs/2404.13496
Autor:
Chen, Zi-Yuan, Liang, Jia-Hao, Fu, Zhao-Xin, Liu, Hong-Zhi, He, Ze-Rui, Wang, 1 Meng, Han, Zhi-Wei, Huang, Jia-Yi, Lv, Qing-Xian, Du, Yan-Xiong
Arrays of neutral atoms have emerged as promising platforms for quantum computing. Realization of high-fidelity two-qubit gates with robustness is currently a significant important task for large-scale operations. In this paper, we present a convenie
Externí odkaz:
http://arxiv.org/abs/2402.01113
Autor:
Han, Zhi-Wei, Liang, Jia-Hao, Fu, Zhao-Xin, Liu, Hong-Zhi, Chen, Zi-Yuan, Wang, Meng, He, Ze-Rui, Huang, Jia-Yi, Lv, Qing-Xian, Liao, Kai-Yu, Du, Yan-Xiong
The braiding operations of quantum states have attracted substantial attention due to their great potential for realizing topological quantum computations. In this paper, we show that a three-fold degenerate eigen subspace can be obtained in a four-l
Externí odkaz:
http://arxiv.org/abs/2401.01703
Full-waveform inversion (FWI) is a powerful geophysical imaging technique that infers high-resolution subsurface physical parameters by solving a non-convex optimization problem. However, due to limitations in observation, e.g., limited shots or rece
Externí odkaz:
http://arxiv.org/abs/2311.04531
In this paper, we introduce two types of novel Asymptotic-Preserving Convolutional Deep Operator Networks (APCONs) designed to address the multiscale time-dependent linear transport problem. We observe that the vanilla physics-informed DeepONets with
Externí odkaz:
http://arxiv.org/abs/2306.15891
Autor:
Lv, Qing-Xian, Liu, Hong-Zhi, Du, Yan-Xiong, Chen, Lin-Qing, Wang, Meng, Liang, Jia-Hao, Fu, Zhao-Xin, Chen, Zi-Yuan, Yan, Hui, Zhu, Shi-Liang
Non-Abelian gauge field (NAGF) plays a central role in understanding the geometrical and topological phenomena in physics. Here we experimentally induce a NAGF in the degenerate eigen subspace of a double-$\Lambda$ four-level atomic system. The non-A
Externí odkaz:
http://arxiv.org/abs/2305.05849
The use of Physics-informed neural networks (PINNs) has shown promise in solving forward and inverse problems of fractional diffusion equations. However, due to the fact that automatic differentiation is not applicable for fractional derivatives, sol
Externí odkaz:
http://arxiv.org/abs/2304.00909
Fractional diffusion equations have been an effective tool for modeling anomalous diffusion in complicated systems. However, traditional numerical methods require expensive computation cost and storage resources because of the memory effect brought b
Externí odkaz:
http://arxiv.org/abs/2211.11981
Autor:
Li, Jia-Zhen, Zou, Cong-Jun, Du, Yan-Xiong, Lv, Qing-Xian, Huang, Wei, Liang, Zhen-Tao, Zhang, Dan-Wei, Yan, Hui, Zhang, Shanchao, Zhu, Shi-Liang
Publikováno v:
Physical Review Letters 129, 220402 (2022)
Topological vacua are a family of degenerate ground states of Yang-Mills fields with zero field strength but nontrivial topological structures. They play a fundamental role in particle physics and quantum field theory, but have not yet been experimen
Externí odkaz:
http://arxiv.org/abs/2211.06824
Publikováno v:
In Chemical Engineering Journal 15 November 2024 500
