Optimal Probe State for Phase Estimation Under Covariant Measurement
Abstract
We study the optimization of input states for phase estimation under covariant measurements. Building on Holevo's framework, which provides the optimal covariant measurement for a fixed input state, we further optimize over the input state itself. For a general even $2π$-periodic cost function with non-negative Fourier coefficients, we derive a necessary and sufficient condition for the optimal input state: Its Fock coefficients are determined, up to arbitrary phases, by the eigenvector correspo...
Description / Details
We study the optimization of input states for phase estimation under covariant measurements. Building on Holevo's framework, which provides the optimal covariant measurement for a fixed input state, we further optimize over the input state itself. For a general even -periodic cost function with non-negative Fourier coefficients, we derive a necessary and sufficient condition for the optimal input state: Its Fock coefficients are determined, up to arbitrary phases, by the eigenvector corresponding to the largest eigenvalue of a Toeplitz matrix defined by the cost function. This characterization yields an explicit expression for the attainable lower bound of the average cost under optimal covariant measurements and shows that this bound asymptotically approaches zero in the infinite-energy limit. For the specific cost function , we obtain the optimal input state and the corresponding minimum average cost in closed form, demonstrating Heisenberg scaling with respect to the mean photon number.
Source: arXiv:2606.18169v1 - http://arxiv.org/abs/2606.18169v1 PDF: https://arxiv.org/pdf/2606.18169v1 Original Link: http://arxiv.org/abs/2606.18169v1
Please sign in to join the discussion.
No comments yet. Be the first to share your thoughts!
Jun 17, 2026
Quantum Computing
Quantum Physics
0