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arxiv: 1803.09421 · v1 · pith:AME2WX5Gnew · submitted 2018-03-26 · 🪐 quant-ph

Adaptive weak-value amplification with adjustable postselection

classification 🪐 quant-ph
keywords schemeadaptivepostselectionamplificationextremelyinformationparametersmall
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Weak-value amplification (WVA) has recently become an important technique for parameter estimation, owing to its ability to enhance the signal-to-noise ratio by amplifying extremely small signals with proper postselection strategies. In this paper, we propose an adaptive WVA scheme to achieve the highest Fisher information when using an unbalanced pointer. Different from previous schemes, the adaptive WVA scheme is associated with a real-time update on the postselection states with the help of feedback information from the outcomes, and the "extremely small" condition set on the parameter of interest is relaxed. By applying this scheme to a time-delay measurement scenario, we show by numerical simulation that the precision achieved in our scheme is several times higher than the standard WVA scheme. Our result might open a path for improving the WVA technique in a more flexible and robust way.

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