Control-centric quantum noise spectroscopy of time-ordered polyspectra

TL;DR

This paper introduces a control-centric approach to quantum noise spectroscopy that focuses on time-ordered polyspectra, enabling more effective noise characterization under realistic control constraints.

Contribution

It recasts noise spectroscopy in terms of time-ordered polyspectra, allowing generalization to arbitrary control scenarios without losing estimation accuracy.

Findings

Successfully reconstructs time-ordered polyspectra in simulations.

Generalizes frequency-comb QNS protocols to various control scenarios.

Improves estimation in challenging, pathological cases.

Abstract

Precise environmental-noise characterisation in open quantum systems is a key step toward high-fidelity quantum control and targeted decoherence suppression in computing and sensing applications. Non-parametric quantum noise spectroscopy (QNS) provides a general-purpose, model-agnostic framework for estimating the spectral properties of an environment. The ability to perform such protocols under realistic constraints is key to their practical applicability. Notably, it is important to account for control constraints and understand how they limit the ability to learn about noise correlations as experiment-agnostic objects. We show how adopting a control-centric point of view allows one to recast the noise spectroscopy problem in such a way that (i) the central objects are now the time-ordered polyspectra, (ii) control filter functions are no longer encumbered by time-ordering. In particular, we show that this approach enables the seamless generalisation of frequency-comb QNS protocols to arbitrary control scenarios without introducing additional control symmetries that effectively remove time-ordering from filter functions, improving estimation in typically pathological scenarios. We demonstrate the targeted reconstruction of the time-ordered polyspectra across classical Gaussian and quantum non-Gaussian environments via simulations.