Towards Training Robustness Against Dynamic Errors in Quantum Machine Learning

Quantum machine learning, crucial in the noisy intermediate-scale quantum (NISQ) era, confronts challenges in error mitigation. Current noise-aware training (NAT) methods often assume static error rates in quantum neural networks (QNNs), overlooking the dynamic nature of quantum noise. Our work high...

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Bibliographic Details

Published in:	2025 62nd ACM/IEEE Design Automation Conference (DAC) pp. 1 - 7
Main Authors:	Duan, Shijin, Liu, Gaowen, Fleming, Charles, Kompella, Ramana, Xu, Xiaolin, Ren, Shaolei
Format:	Conference Proceeding
Language:	English
Published:	IEEE 22.06.2025
Subjects:	Error analysis Machine learning Noise Optimization Prevention and mitigation Qubit Robustness Search methods Training
Online Access:	Get full text
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