Quantum neural network
M.V.Altaisky
TL;DR
This paper proposes a design for a quantum neural network (QNN) utilizing quantum information principles, where optical modes, beam splitters, and phase shifters implement the network's components.
Contribution
It introduces a novel implementation method for QNNs using optical components, bridging quantum information processing with neural network architecture.
Findings
QNN can be realized with optical modes and components
Optical beam splitters and phase shifters serve as weights
Potential for quantum-enhanced neural network processing
Abstract
It is suggested that a quantum neural network (QNN), a type of artificial neural network, can be built using the principles of quantum information processing. The input and output qubits in the QNN can be implemented by optical modes with different polarization, the weights of the QNN can be implemented by optical beam splitters and phase shifters
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Quantum Information and Cryptography · Quantum Mechanics and Applications