Denoising Gradient Descent in Variational Quantum Algorithms
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arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866909129687171072 |
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| author | Simon, Lars Eble, Holger Kowalski, Hagen-Henrik Radons, Manuel |
| author_facet | Simon, Lars Eble, Holger Kowalski, Hagen-Henrik Radons, Manuel |
| contents | In this article we introduce an algorithm for mitigating the adverse effects of noise on gradient descent in variational quantum algorithms. This is accomplished by computing a {\emph{regularized}} local classical approximation to the objective function at every gradient descent step. The computational overhead of our algorithm is entirely classical, i.e., the number of circuit evaluations is exactly the same as when carrying out gradient descent using the parameter-shift rules. We empirically demonstrate the advantages offered by our algorithm on randomized parametrized quantum circuits. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_03826 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Denoising Gradient Descent in Variational Quantum Algorithms Simon, Lars Eble, Holger Kowalski, Hagen-Henrik Radons, Manuel Quantum Physics Numerical Analysis 68T99 In this article we introduce an algorithm for mitigating the adverse effects of noise on gradient descent in variational quantum algorithms. This is accomplished by computing a {\emph{regularized}} local classical approximation to the objective function at every gradient descent step. The computational overhead of our algorithm is entirely classical, i.e., the number of circuit evaluations is exactly the same as when carrying out gradient descent using the parameter-shift rules. We empirically demonstrate the advantages offered by our algorithm on randomized parametrized quantum circuits. |
| title | Denoising Gradient Descent in Variational Quantum Algorithms |
| topic | Quantum Physics Numerical Analysis 68T99 |
| url | https://arxiv.org/abs/2403.03826 |