Operational time-reversal symmetry for unital qubit channels

TL;DR

This paper characterizes when a Bayesian inverse, representing a form of time-reversal symmetry, exists for unital qubit channels, simplifying the problem to Pauli channels and revealing conditions for time-symmetric measurement correlations.

Contribution

It provides a complete characterization of Bayesian inverses for unital qubit channels, reducing the problem to Pauli channels and clarifying when time-reversal symmetry can be operationally achieved.

Findings

Bayesian inverses exist for certain unital qubit channels.

The problem reduces to finding Bayesian inverses of Pauli channels.

Operational time-reversal symmetry is characterized for unital noise.

Abstract

The Bayesian inverse of a quantum channel $\mathcal{E}$ is a channel $\mathcal{F}$ in the reverse direction of $\mathcal{E}$ that yields time-symmetric correlations for sequential measurements performed on open quantum systems. Such an operational form of time-reversal symmetry for open quantum systems is quite remarkable, as the dynamics of open quantum systems are inherently irreversible due to system-environment interactions. Similar to the Petz map, a Bayesian inverse $\mathcal{F}$ is defined with respect to a fiducial reference state $\rho$ for the channel $\mathcal{E}$. However, Bayesian inverses do not always exist, and it is often a non-trivial task to determine the set of states $\rho$ for which a Bayesian inverse of $\mathcal{E}$ exists. In this work, we solve the general problem of quantum Bayesian inversion for unital channels acting on a single qubit. Our analysis is streamlined by demonstrating that finding a Bayesian inverse for a unital qubit channel may be reduced to finding a Bayesian inverse of a Pauli channel, which is simply a mixture of unitary channels associated with the Pauli matrices. As such, we provide a complete description of when operational time-reversal symmetry is attainable for sequential measurements of a single qubit in the presence of unital noise.