Usefulness of an enhanced Kitaev phase-estimation algorithm in quantum metrology and computation

TL;DR

This paper investigates a generalized Kitaev phase estimation algorithm, demonstrating its potential to achieve Heisenberg-limited precision, but also highlighting its limitations under losses and alternative resource measures.

Contribution

It introduces a generalized Kitaev algorithm with improved error scaling and analyzes its performance relative to fundamental bounds and practical constraints.

Findings

Generalized algorithm achieves Heisenberg 1/N^2 error scaling.

Optimality breaks down with losses, performing worse than entanglement-based strategies.

Standard Kitaev's method is optimal under alternative resource quantification.

Abstract

We analyze the performance of a generalized Kitaev's phase estimation algorithm where N phase gates, acting on $M$ qubits prepared in a product state, may be distributed in an arbitrary way. Unlike the standard algorithm, where the mean square error scales as 1/N, the optimal generalizations offer the Heisenberg $1/N^2$ error scaling and we show that they are in fact very close to the fundamental Bayesian estimation bound. We also demonstrate that the optimality of the algorithm breaks down when losses are taken into account, in which case the performance is inferior to the optimal entanglement-based estimation strategies. Finally, we show that when an alternative resource quantification is adopted, which describes the phase estimation in Shor's algorithm more accurately, the standard Kitaev's procedure is indeed optimal and there is no need to consider its generalized version.