Hamiltonian learning for the estimation of magnetic fields with nanoscale quantum sensors

R. Santagati, A. A. Gentile, S. Knauer, S. Schmitt, S. Paesani, C. Granade, N. Wiebe, Christian Osterkamp, L. McGuinness, Jianwei Wang, M. Thompson, J. Rarity, F. Jelezko, A. Laing
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Abstract

Hamiltonian learning can be used to efficiently characterise quantum systems. Here we apply it to the estimation of magnetic fields with quantum sensors, achieving experimentally, room temperature sensing performance comparable to those of cryogenic set-ups.
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用纳米级量子传感器估计磁场的哈密顿学习
哈密顿学习可以用来有效地表征量子系统。在这里,我们将其应用于量子传感器的磁场估计,在实验中实现了与低温装置相当的室温传感性能。
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