System identification for passive linear quantum systems

TL;DR

This paper investigates the identifiability and parameter reconstruction of passive linear quantum systems, proposing methods to optimize estimation precision and achieve Heisenberg-limited sensitivity using non-classical states.

Contribution

It characterizes which passive linear quantum systems are identifiable and introduces a frequency domain design for optimal parameter estimation.

Findings

Minimal systems are identifiable up to a unitary transformation.

Infecting systems are fully identifiable.

Heisenberg-limited estimation achievable with non-classical states.

Abstract

System identification is a key enabling component for the implementation of quantum technologies, including quantum control. In this paper, we consider the class of passive linear input-output systems, and investigate several basic questions: (1) which parameters can be identified? (2) Given sufficient input-output data, how do we reconstruct the system parameters? (3) How can we optimize the estimation precision by preparing appropriate input states and performing measurements on the output? We show that minimal systems can be identified up to a unitary transformation on the modes, and systems satisfying a Hamiltonian connectivity condition called "infecting" are completely identifiable. We propose a frequency domain design based on a Fisher information criterion, for optimizing the estimation precision for coherent input state. As a consequence of the unitarity of the transfer function, we show that the Heisenberg limit with respect to the input energy can be achieved using non-classical input states.