| Autor: |
Garcia, Roy J., Bu, Kaifeng, Jaffe, Arthur |
| Rok vydání: |
2021 |
| Předmět: |
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| Druh dokumentu: |
Working Paper |
| DOI: |
10.1007/JHEP03(2022)027 |
| Popis: |
We characterize a quantum neural network's error in terms of the network's scrambling properties via the out-of-time-ordered correlator. A network can be trained by optimizing either a loss function or a cost function. We show that, with some probability, both functions can be bounded by out-of-time-ordered correlators. The gradients of these functions can be bounded by the gradient of the out-of-time-ordered correlator, demonstrating that the network's scrambling ability governs its trainability. Our results pave the way for the exploration of quantum chaos in quantum neural networks. |
| Databáze: |
arXiv |
| Externí odkaz: |
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