Trade-off between gradient measurement efficiency and expressivity in deep quantum neural networks
Abstract Quantum neural networks (QNNs) require an efficient training algorithm to achieve practical quantum advantages. A promising approach is gradient-based optimization, where gradients are estimated by quantum measurements. However, QNNs currently lack general quantum algorithms for efficiently...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-05-01
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| Series: | npj Quantum Information |
| Online Access: | https://doi.org/10.1038/s41534-025-01036-7 |
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