Optimizing a polynomial function on a quantum processor
Abstract The gradient descent method is central to numerical optimization and is the key ingredient in many machine learning algorithms. It promises to find a local minimum of a function by iteratively moving along the direction of the steepest descent. Since for high-dimensional problems the requir...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Publishing Group
2021-01-01
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| Series: | npj Quantum Information |
| Online Access: | https://doi.org/10.1038/s41534-020-00351-5 |