Heisenberg-limited Bayesian phase estimation with low-depth digital quantum circuits
Su Direkci, Ran Finkelstein, Manuel Endres, Tuvia Gefen

TL;DR
This paper presents a low-depth digital quantum circuit scheme for Bayesian phase estimation that achieves near-Heisenberg limit precision with scalable resources, outperforming existing methods.
Contribution
It introduces a practical, scalable quantum phase estimation protocol using simple circuits and adaptive measurements, achieving Heisenberg scaling with minimal depth.
Findings
Achieves near-Heisenberg limit precision with logarithmic circuit depth.
Optimal initial states can be approximated with GHZ product states.
Outperforms existing schemes in precision and resource efficiency.
Abstract
Optimal phase estimation protocols require complex state preparation and readout schemes, generally unavailable or unscalable in many quantum platforms. We develop and analyze a scheme that achieves near-optimal precision up to a constant overhead for Bayesian phase estimation, using simple digital quantum circuits with depths scaling logarithmically with the number of qubits. We find that for Gaussian prior phase distributions with arbitrary widths, the optimal initial state can be approximated with products of Greenberger-Horne-Zeilinger states with varying number of qubits. Using local, adaptive measurements optimized for the prior distribution and the initial state, we show that Heisenberg scaling is achievable and that the proposed scheme outperforms known schemes in the literature that utilize a similar set of initial states. For an example prior width, we present a detailed…
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