南方科技大学知识苑(SUSTech KC): Quantum Neural Networks and Topological Quantum Field Theories

题名	Quantum Neural Networks and Topological Quantum Field Theories
作者	Marcianò，Antonino 1,2; Chen，Deen 3; Fabrocini，Filippo 3,4; Fields，Chris 5; Greco，Enrico 6; Gresnigt，Niels 7; Jinklub，Krid 3; Lulli，Matteo8 ; Terzidis，Kostas 3; Zappala，Emanuele 9
通讯作者	Fabrocini，Filippo
发表日期	2022-09-01
DOI	10.1016/j.neunet.2022.05.028
发表期刊	NEURAL NETWORKS 影响因子和分区
ISSN	0893-6080
EISSN	1879-2782
卷号	153页码:164-178
摘要	Our work intends to show that: (1) Quantum Neural Networks (QNNs) can be mapped onto spin-networks, with the consequence that the level of analysis of their operation can be carried out on the side of Topological Quantum Field Theory (TQFT); (2) A number of Machine Learning (ML) key-concepts can be rephrased by using the terminology of TQFT. Our framework provides as well a working hypothesis for understanding the generalization behavior of DNNs, relating it to the topological features of the graph structures involved.
关键词	Graph neural networks Quantum amplitude classifiers Quantum perceptron Topological quantum field theory Topological quantum neural networks
相关链接	[Scopus记录]
收录类别	SCI ; EI
语种	英语
学校署名	其他
资助项目	National Natural Science Foundation of China[11875113];National Natural Science Foundation of China[12050410244];Fudan University[JJH1512105];Eesti Teadusagentuur[MOBJD679];Xi’an Jiaotong-Liverpool University[REF-18-02-03];
WOS研究方向	Computer Science ; Neurosciences & Neurology
WOS类目	Computer Science, Artificial Intelligence ; Neurosciences
WOS记录号	WOS:000822992800008
出版者	PERGAMON-ELSEVIER SCIENCE LTD
EI入藏号	20222612295187
EI主题词	Quantum theory ; Topology
EI分类号	Artificial Intelligence:723.4 ; Combinatorial Mathematics, Includes Graph Theory, Set Theory:921.4 ; Quantum Theory; Quantum Mechanics:931.4
ESI学科分类	COMPUTER SCIENCE
Scopus记录号	2-s2.0-85132938862
来源库	Scopus
引用统计	被引频次[WOS]：12
成果类型	期刊论文
条目标识符	http://sustech.caswiz.com/handle/2SGJ60CL/352466
专题	工学院_力学与航空航天工程系
作者单位	1.Center for Field Theory and Particle Physics & Department of Physics,Fudan University,Shanghai,Jingwan campus, Jingsan Rd,200433,China 2.Laboratori Nazionali di Frascati INFN,Frascati (Rome),Via Enrico Fermi, 54,00044,Italy 3.College of Design and Innovation,Tongji University,Shanghai,281 Fuxin Rd,200092,China 4.Institute for Computing Applications ”Mario Picone”,Italy National Research Council,Rome,Via dei Taurini, 19,00185,Italy 5.Allen Discovery Center,Tufts University,Medford,200 College Avenue,02155,United States 6.Department of Chemical and Pharmaceutical Sciences,University of Trieste,Trieste,Via Giorgieri, 1,34127,Italy 7.Department of Physics,Xi'an Jiaotong-Liverpool University,Suzhou,111 Ren'ai Rd,215123,China 8.Department of Mechanics and Aerospace Engineering,Southern University of Science and Technology,Shenzhen,1088 Xueyuan Avenue,518055,China 9.Yale School of Medicine,Yale University,New HavenCT,06510,United States
推荐引用方式 GB/T 7714	Marcianò，Antonino,Chen，Deen,Fabrocini，Filippo,et al. Quantum Neural Networks and Topological Quantum Field Theories[J]. NEURAL NETWORKS,2022,153:164-178.
APA	Marcianò，Antonino.,Chen，Deen.,Fabrocini，Filippo.,Fields，Chris.,Greco，Enrico.,...&Zappala，Emanuele.(2022).Quantum Neural Networks and Topological Quantum Field Theories.NEURAL NETWORKS,153,164-178.
MLA	Marcianò，Antonino,et al."Quantum Neural Networks and Topological Quantum Field Theories".NEURAL NETWORKS 153(2022):164-178.