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A Hybrid Quantum-Classical Physics-Informed Neural Network Architecture for Solving Quantum Optimal Control Problems

AuthID
P-017-YJW

Author(s)

Dehaghani, NB

Aguiar, AP

Wisniewski, R

Editor(es)

Culhane,C;Byrd,GT;Muller,H;Alexeev,Y;Alexeev,Y;Sheldon,S

Tipo de Documento

Proceedings Paper

Year published

2024

Publicado

in IEEE International Conference on Quantum Computing and Engineering, QCE 2024, Montreal, QC, Canada, September 15-20, 2024 in QCE

Volume: 1, Páginas: 1378-1386 (8)

Conference

5Th Ieee International Conference on Quantum Computing and Engineering, Qce 2024, Date: 15 September 2024 through 20 September 2024, Location: Montreal

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Dblp^®/pt/publications/view/1309276

Google Scholar^®

Metadata
Fontes

Publication Identifiers

DOI: 10.1109/qce60285.2024.00164

DBLP: conf/qce/DehaghaniAW24

SCOPUS: 2-s2.0-85217397664

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A Hybrid Quantum-Classical Physics-Informed Neural Network Architecture for Solving Quantum Optimal Control Problems

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A Hybrid Quantum-Classical Physics-Informed Neural Network Architecture for Solving Quantum Optimal Control Problems

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