Super-Exponential Advantage of Squeezed Light in Phase Estimation under Discrete Phase Randomisation

Abstract

A paradigmatic task in quantum metrology is that of phase estimation. For this task it is commonly believed, under reasonable assumptions about prior information, that a quadratic advantage in sensitivity is the maximum possible advantage offered by the use of quantum resources. In this work, we consider a channel that implements a phase shift by an angle $2\pi k/M$, where $k$ is a uniformly random unknown integer, in addition to a small unknown phase shift of interest. We show that, subject to a constraint on the mean photon number per channel use, there is a super-exponential separation between the quantum Fisher information (QFI) attainable using a squeezed vacuum state and that attainable using coherent states. This advantage holds over any state obtained from a coherent state via phase covariant channels. Specifically, when the mean photon number per channel use is 1, the ratio of their QFI grows as $\Omega [(M/\sqrt{2}e{)}^M]$. For a mean photon number per channel use of $M/\log (M)$, the squeezed vacuum QFI is $\Omega (M^{3/2}/\sqrt{\log (M)})$, whereas for a coherent state it is at most $\exp [-M\log \log (M)+O(M)]$. We complement this QFI analysis with non-asymptotic estimation results. For a mean photon number per channel use of $M/\log M$, an explicit squeezed-vacuum protocol estimates the phase to accuracy $O(1/M)$ using $O(\sqrt{M\log M})$ channel uses, whereas every coherent state protocol requires at least $\exp [M\log \log M-O(M)]$ channel uses. We consider the effects of noise and show that the ratio of their QFIs can still grow super-exponentially in $M$. Finally, under fixed optical loss and thermal noise, choosing $\bar{n}=M^2/(\log M{)}^{3/2}$ allows squeezed vacuum with heterodyne detection to achieve accuracy $O(1/M)$ using sub-polynomially many channel uses, whereas every protocol in the specified classical family requires super-polynomially many.

10 page main text, comments very welcome