中文版 | English
Title

Quantum Neural Networks and Topological Quantum Field Theories

Author
Corresponding AuthorFabrocini,Filippo
Publication Years
2022-09-01
DOI
Source Title
ISSN
0893-6080
EISSN
1879-2782
Volume153Pages:164-178
Abstract
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.
Keywords
URL[Source Record]
Indexed By
SCI ; EI
Language
English
SUSTech Authorship
Others
Funding Project
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 Research Area
Computer Science ; Neurosciences & Neurology
WOS Subject
Computer Science, Artificial Intelligence ; Neurosciences
WOS Accession No
WOS:000822992800008
Publisher
EI Accession Number
20222612295187
EI Keywords
Quantum theory ; Topology
ESI Classification Code
Artificial Intelligence:723.4 ; Combinatorial Mathematics, Includes Graph Theory, Set Theory:921.4 ; Quantum Theory; Quantum Mechanics:931.4
ESI Research Field
COMPUTER SCIENCE
Scopus EID
2-s2.0-85132938862
Data Source
Scopus
Citation statistics
Cited Times [WOS]:2
Document TypeJournal Article
Identifierhttp://kc.sustech.edu.cn/handle/2SGJ60CL/352466
DepartmentDepartment of Mechanics and Aerospace Engineering
Affiliation
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
Recommended Citation
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.
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