Robust shadow estimation

Understand

Efficiently estimating properties of large and strongly coupled quantum systems is a central focus in many-body physics and quantum information theory.

• While quantum computers promise speedups for many such tasks, near-term devices are prone to noise that will generally reduce the accuracy of such estimates.
• Here we show how to mitigate errors in the shadow estimation protocol recently proposed by Huang, Kueng, and Preskill.
• By adding an experimentally friendly calibration stage to the standard shadow estimation scheme, our robust shadow estimation algorithm can obtain an unbiased estimate of the classical shadow of a quantum system and hence extract many useful properties in a sample-efficient and noise-resilient manner given only minimal assumptions on the experimental conditions.