Energy-dependent barren plateau in bosonic variational quantum circuits
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arXiv
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| Hauptverfasser: | , |
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| Format: | Preprint |
| Veröffentlicht: |
2023
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| _version_ | 1866908090853490688 |
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| author | Zhang, Bingzhi Zhuang, Quntao |
| author_facet | Zhang, Bingzhi Zhuang, Quntao |
| contents | Bosonic continuous-variable Variational quantum circuits (VQCs) are crucial for information processing in cavity quantum electrodynamics and optical systems, widely applicable in quantum communication, sensing and error correction. The trainability of such VQCs is less understood, hindered by the lack of theoretical tools such as $t$-design due to the infinite dimension of the physical systems involved. We overcome this difficulty to reveal an energy-dependent barren plateau in such VQCs. The variance of the gradient decays as $1/E^{Mν}$, exponential in the number of modes $M$ but polynomial in the (per-mode) circuit energy $E$. The exponent $ν=1$ for shallow circuits and $ν=2$ for deep circuits. We prove these results for state preparation of general Gaussian states and number states. We also provide numerical evidence that the results extend to general state preparation tasks. As circuit energy is a controllable parameter, we provide a strategy to mitigate the barren plateau in continuous-variable VQCs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2305_01799 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Energy-dependent barren plateau in bosonic variational quantum circuits Zhang, Bingzhi Zhuang, Quntao Quantum Physics Machine Learning Bosonic continuous-variable Variational quantum circuits (VQCs) are crucial for information processing in cavity quantum electrodynamics and optical systems, widely applicable in quantum communication, sensing and error correction. The trainability of such VQCs is less understood, hindered by the lack of theoretical tools such as $t$-design due to the infinite dimension of the physical systems involved. We overcome this difficulty to reveal an energy-dependent barren plateau in such VQCs. The variance of the gradient decays as $1/E^{Mν}$, exponential in the number of modes $M$ but polynomial in the (per-mode) circuit energy $E$. The exponent $ν=1$ for shallow circuits and $ν=2$ for deep circuits. We prove these results for state preparation of general Gaussian states and number states. We also provide numerical evidence that the results extend to general state preparation tasks. As circuit energy is a controllable parameter, we provide a strategy to mitigate the barren plateau in continuous-variable VQCs. |
| title | Energy-dependent barren plateau in bosonic variational quantum circuits |
| topic | Quantum Physics Machine Learning |
| url | https://arxiv.org/abs/2305.01799 |