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Proceedings in Technology Transfer

Quantum Neural Networks in the NISQ Era: Architectures, Challenges, and Applications

Kanishka W. Palihakkara, Mahesh N. Jayakody

Published Jan 1, 2026• 0 citations
Publisher
DOI
10.1007/978-981-92-0423-6_19

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This study explores the application of quantum neural networks (QNN) and variational quantum regression (VQR) in seismic inversion, leveraging quantum computing’s advantages in superposition, entanglement, and interference. Implemented using variational quantum circuits (VQC) and tested on the Qiskit simulator, QNN captures complex seismic data relationships, while VQR focuses on regression tasks. Results demonstrate their potential in geophysical applications but highlight challenges in model generalization and scalability. As quantum computing advances beyond the NISQ era, quantum intelligence is expected to provide new insights for efficient seismic inversion.