# Extending comb-based spectral estimation to multiaxis quantum noise

## TL;DR

This paper extends spectral estimation techniques to characterize multiaxis quantum noise, enabling analysis of systems with both T1 and T2 processes, crucial for diverse quantum computing platforms.

## Contribution

It introduces a pulsed spectral estimation method based on sequence repetition and frequency-comb sampling applicable to multiaxis noise with large energy splittings.

## Key findings

- Applicable to systems with large qubit energy-splitting
- Effective for stationary Gaussian noise models
- Extends protocols to platforms with T1 and T2 processes

## Abstract

We show how to achieve full spectral characterization of general multiaxis additive noise. Our pulsed spectral estimation technique is based on sequence repetition and frequency-comb sampling and is applicable even to models where a large qubit energy-splitting is present (as is typically the case for spin qubits in semiconductors, for example), as long as the noise is stationary and a second-order (Gaussian) approximation to the controlled reduced dynamics is viable. Our new result is crucial to extending the applicability of these protocols, now standard in dephasing-dominated platforms such as silicon-based qubits, to experimental platforms where both $T_1$ and $T_2$ processes are significant, such as superconducting qubits.