Theory of Compression Channels for Postselected Quantum Metrology
Jing Yang
TL;DR
This work develops a unified theory of lossless postselected quantum metrology by introducing a prior structure for compression channels that preserve quantum Fisher information (QFI) while discarding information-bearing outcomes. It shows that lossless compression channels (LCCs) must decompose the postselection POVMs as $E_{\omega}=q_{\omega}\rho_x^{\perp}+\Lambda_{\omega}$ and saturate generalized optimal measurement conditions, enabling substantial reduction in measurement costs without sacrificing precision. The authors provide explicit constructions for regular and null POVMs, prove a general LCC structure, analyze the sensitivity of postselected states, and connect these results to weak-value amplification. They further demonstrate two classes of near-lossless, subsystem-only compression for bipartite entangled states under non-interacting Hamiltonians, illustrating practical pathways to distribute quantum measurements in scalable sensing tasks. These insights offer a comprehensive framework to design compression channels that dramatically lower final-detection costs in quantum metrology, with implications for optical phase estimation, interferometry, and distributed quantum sensing.
Abstract
Postselected quantum metrological scheme is especially advantageous when the final measurements are either very noisy or expensive in practical experiments. In this work, we put forward a general theory on the compression channels in postselected quantum metrology. We define the basic notions characterizing the compression quality and illuminate the underlying structure of lossless compression channels. Previous experiments on Postselected optical phase estimation and weak-value amplification are shown to be particular cases of this general theory. Furthermore, for two categories of bipartite systems, we show that the compression loss can be made arbitrarily small even when the compression channel acts only on one subsystem. These findings can be employed to distribute quantum measurements so that the measurement noise and cost are dramatically reduced.
