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Quantum Neural Networks and Topological Quantum Field Theories
Antonino Marcianò1, Deen Chen2, Filippo Fabrocini3
1Center for Field Theory and Particle Physics & Department of Physics, Fudan University, Jingwan campus, Jingsan Rd, 200433 Shanghai, China; Laboratori Nazionali di Frascati INFN, Via Enrico Fermi, 54, 00044, Frascati (Rome), Italy.
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.
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