Compressed qubit noise spectroscopy: Piecewise-linear modeling and Rademacher measurements

Published

September 24, 2026

Author(s)

Kaixin Huang, Demitry Farfurnik, Dror Baron, Yi-Kai Liu

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: expanding its applicability to a larger class of noise spectra, and simplifying its implementation. First, we extend the random pulse sequences method to reconstruct 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 introduce a simplified variant using Rademacher measurements, optimized for sparse spectra, that greatly reduces experimental complexity without compromising reconstruction accuracy. Together, these developments broaden the reach of random pulse sequences noise spectroscopy and enhance its practicality for high-resolution, resource-efficient noise characterization in realistic quantum systems.

Citation

Arxiv

Volume

26

Issue

3

Pub Weblink

https://arxiv.org/

Pub Type

Websites

Download Paper

https://doi.org/10.1103/r813-2yvm

Local Download

Keywords

Qubit noise spectroscopy, compressed sensing, linear programming, quantum dots

Citation

Huang, K. , Farfurnik, D. , Baron, D. and Liu, Y. (2026), Compressed qubit noise spectroscopy: Piecewise-linear modeling and Rademacher measurements, Arxiv, [online], https://doi.org/10.1103/r813-2yvm, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=961161, https://arxiv.org/ (Accessed September 30, 2026)

Additional citation formats