Efficiently Computable Strategies and Limits for Bosonic Channel Discrimination

TL;DR

This paper develops new bounds and computational tools for discriminating bosonic quantum channels under energy constraints, advancing quantum sensing and communication capabilities.

Contribution

It introduces an energy-constrained chain rule for the Belavkin-Staszewski divergence and SDP-based bounds for channel discrimination error exponents.

Findings

SDP formulations for relative entropy measures under energy constraints

Optimal probes are Fock-diagonal states

Practical benchmarks for quantum-limited sensing

Abstract

Discriminating between noisy quantum processes is a central primitive for quantum communication, metrology, and computing. While discrimination limits for finite-dimensional channels are well understood, the continuous-variable setting, particularly under experimentally relevant energy constraints, remains significantly less developed. In this work, we establish an energy-constrained chain rule for the Belavkin-Staszewski channel divergence, which yields a fundamental upper bound on the error exponents achievable by fully adaptive, energy-constrained quantum channel discrimination protocols. We then derive efficiently computable bounds on asymmetric error exponents for energy-constrained discrimination of bosonic dephasing and loss-dephasing channels. Specifically, we show that three operationally relevant quantities -- the measured relative entropy, the Umegaki relative entropy, and the geometric Renyi divergence -- admit semidefinite program (SDP) formulations when the input energy is bounded and the Hilbert space is suitably truncated. Applying these tools, we demonstrate that optimal probes for these channels under energy constraints are Fock-diagonal, and we also enable numerically precise evaluation of bounds on achievable error exponents across discrimination strategies ranging from separable to fully adaptive. The resulting SDPs provide practical benchmarks for quantum-limited sensing in low-energy bosonic platforms.