Noise-Aware Quantum Amplitude Estimation

TL;DR

This paper introduces a Gaussian noise model for quantum amplitude estimation, validated on real quantum computers, and demonstrates how to incorporate it into algorithms for improved error mitigation.

Contribution

It presents a new Gaussian noise model for quantum amplitude estimation and a method to embed this model into algorithms for noise-aware quantum estimation.

Findings

The Gaussian noise model fits experimental data well.

Embedding the noise model improves quantum error mitigation.

Experimental results show enhanced accuracy with noise-aware estimation.

Abstract

In this article, based on some simple and reasonable assumptions, we derive a Gaussian noise model for quantum amplitude estimation. We provide results from quantum amplitude estimation run on various IBM superconducting quantum computers and on Quantinuum's H1 trapped-ion quantum computer to show that the proposed model is a good fit for real-world experimental data. We also show that the proposed Gaussian noise model can be easily composed with other noise models in order to capture effects that are not well described by Gaussian noise. We give a generalized procedure for how to embed this noise model into any quantum-phase-estimation-free quantum amplitude estimation algorithm, such that the amplitude estimation is "noise aware." We then provide experimental results from running an implementation of noise-aware quantum amplitude estimation using data from an IBM superconducting quantum computer, demonstrating that the addition of "noise awareness" serves as an effective means of quantum error mitigation.