A Hybrid Quantum-Classical Approach for Melt Pool Prediction in Laser Powder Bed Fusion
Laser powder bed fusion (LPBF) is a promising additive manufacturing technique that suffers from quality assurance concerns. Predicting melt pools from process parameters is crucial for assessing quality prior to manufacturing but remains a difficult problem because of the complex physical processes underlying LPBF. Quantum computers present a new computing paradigm, providing a new approach to information processing using quantum entanglement and superposition. This paper presents a practical demonstration of a hybrid quantum-classical model that leverages quantum computing to improve process parameter feature extraction with a quantum feature encoder. To make the quantum approach comput...
| Authors | Matthew M. Sato, Kincho H. Law |
|---|---|
| Primary category | quant-ph |
| Published | 17 June 2026 |
| Last updated at source | 17 June 2026 |
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