Zobrazeno 1 - 10
of 319
pro vyhledávání: '"Li, Zimu"'
We consider quantum circuit models where the gates are drawn from arbitrary gate ensembles given by probabilistic distributions over certain gate sets and circuit architectures, which we call stochastic quantum circuits. Of main interest in this work
Externí odkaz:
http://arxiv.org/abs/2411.04898
The efficiency of locally generating unitary designs, which capture statistical notions of quantum pseudorandomness, lies at the heart of wide-ranging areas in physics and quantum information technologies. While there are extensive potent methods and
Externí odkaz:
http://arxiv.org/abs/2411.04893
Technical Report: The Graph Spectral Token -- Enhancing Graph Transformers with Spectral Information
Autor:
Pengmei, Zihan, Li, Zimu
Graph Transformers have emerged as a powerful alternative to Message-Passing Graph Neural Networks (MP-GNNs) to address limitations such as over-squashing of information exchange. However, incorporating graph inductive bias into transformer architect
Externí odkaz:
http://arxiv.org/abs/2404.05604
Autor:
Jing, Xinxin, Wang, Haozhi, Huang, Jianxiang, Liu, Yingying, Li, Zimu, Chen, Jielin, Xu, Yiqun, Li, Lingyun, Lin, Yunxiao, Buratto, Damiano, Xia, Qinglin, Pan, Muchen, Wang, Yue, Li, Mingqiang, Zhou, Ruhong, Liu, Xiaoguo, Mann, Stephen, Fan, Chunhai
The organizational complexity of biominerals has long fascinated scientists seeking to understand biological programming and implement new developments in biomimetic materials chemistry. Nonclassical crystallization pathways have been observed and an
Externí odkaz:
http://arxiv.org/abs/2311.02674
Transformers, adapted from natural language processing, are emerging as a leading approach for graph representation learning. Contemporary graph transformers often treat nodes or edges as separate tokens. This approach leads to computational challeng
Externí odkaz:
http://arxiv.org/abs/2310.01704
Quantum information processing in the presence of continuous symmetry is of wide importance and exhibits many novel physical and mathematical phenomena. SU(d) is a continuous symmetry group of particular interest since it represents a fundamental typ
Externí odkaz:
http://arxiv.org/abs/2309.16556
The generation of $k$-designs (pseudorandom distributions that emulate the Haar measure up to $k$ moments) with local quantum circuit ensembles is a problem of fundamental importance in quantum information and physics. Despite the extensive understan
Externí odkaz:
http://arxiv.org/abs/2309.08155
Autor:
Kan, Xuan, Li, Zimu, Cui, Hejie, Yu, Yue, Xu, Ran, Yu, Shaojun, Zhang, Zilong, Guo, Ying, Yang, Carl
Biological networks are commonly used in biomedical and healthcare domains to effectively model the structure of complex biological systems with interactions linking biological entities. However, due to their characteristics of high dimensionality an
Externí odkaz:
http://arxiv.org/abs/2306.02532
Publikováno v:
Mach. Learn.: Sci. Technol. 5 025044, 2024
Many learning tasks, including learning potential energy surfaces from ab initio calculations, involve global spatial symmetries and permutational symmetry between atoms or general particles. Equivariant graph neural networks are a standard approach
Externí odkaz:
http://arxiv.org/abs/2211.07482
We introduce a framework of the equivariant convolutional algorithms which is tailored for a number of machine-learning tasks on physical systems with arbitrary SU($d$) symmetries. It allows us to enhance a natural model of quantum computation--permu
Externí odkaz:
http://arxiv.org/abs/2207.07250