Noiseless linear amplification-based quantum Ziv-Zakai bound for phase estimation and its Heisenberg error limits in noisy scenarios

• URL: http://arxiv.org/abs/2404.14173v1
• Date: Mon, 22 Apr 2024 13:41:38 GMT
• Title: Noiseless linear amplification-based quantum Ziv-Zakai bound for phase estimation and its Heisenberg error limits in noisy scenarios
• Authors: Wei Ye, Peng Xiao, Xiaofan Xu, Xiang Zhu, Yunbin Yan, Lu Wang, Jie Ren, Yuxuan Zhu, Ying Xia, Xuan Rao, Shoukang Chang,
• Abstract summary: We study whether the phase estimation performance is improved significantly in noisy scenarios, involving the photon-loss and phase-diffusion cases. Our results show that in cases of photon loss and phase diffusion, the phase estimation performance of the QZZB can be improved remarkably by increasing the NLA gain factor. Our findings will provide an useful guidance for accomplishing more complex quantum information processing tasks.
• Score: 10.543863589371552
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In this work, we address the central problem about how to effectively find the available precision limit of unknown parameters. In the framework of the quantum Ziv-Zakai bound (QZZB), we employ noiseless linear amplification (NLA)techniques to an initial coherent state (CS) as the probe state, and focus on whether the phase estimation performance is improved significantly in noisy scenarios, involving the photon-loss and phase-diffusion cases. More importantly, we also obtain two kinds of Heisenberg error limits of the QZZB with the NLA-based CS in these noisy scenarios, making comparisons with both the Margolus-Levitin (ML) type bound and the Mandelstam-Tamm (MT) type bound. Our analytical results show that in cases of photon loss and phase diffusion, the phase estimation performance of the QZZB can be improved remarkably by increasing the NLA gain factor. Particularly, the improvement is more pronounced with severe photon losses. Furthermore in minimal photon losses, our Heisenberg error limit shows better compactness than the cases of the ML-type and MT-type bounds. Our findings will provide an useful guidance for accomplishing more complex quantum information processing tasks.

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