Compressed Qubit Noise Spectroscopy: Piecewise-Linear Modeling and Rademacher Measurements

TL;DR

This paper introduces an improved qubit noise spectroscopy method that uses total generalized variation regularization for better spectral resolution and Rademacher measurements for simplified experimental implementation, enabling more accurate noise characterization.

Contribution

The authors develop a novel regularization technique for piecewise-linear noise spectra and introduce Rademacher measurements to simplify experimental procedures in quantum noise spectroscopy.

Findings

Enhanced spectral resolution with TGV regularization.

Reduced experimental complexity using Rademacher measurements.

Maintained accuracy with significant speedup.

Abstract

Random pulse sequences are a powerful method for qubit noise spectroscopy, enabling efficient reconstruction of sparse noise spectra. Here, we advance this method in two complementary directions. First, we extend the method using a regularizer based on the total generalized variation (TGV) norm, in order to reconstruct a larger class of noise spectra, namely piecewise-linear noise spectra, which more realistically model many physical systems. We show through numerical simulations that the new method resolves finer spectral features, while maintaining an order-of-magnitude speedup over conventional approaches to noise spectroscopy. Second, we simplify the experimental implementation of the method, by introducing Rademacher measurements for reconstructing sparse noise spectra. These measurements use pseudorandom pulse sequences that can be generated in real time from a short random seed, reducing experimental complexity without compromising reconstruction accuracy. Together, these developments broaden the reach of random pulse sequences for accurate and efficient noise characterization in realistic quantum systems.