Character Phase Estimation
Presented by Kevin Young (Sandia National Laboratories)
The computational utility of modern quantum computers is limited not by speed or size, but by errors. These errors can arise from environmental couplings, unknown qubit interactions, crosstalk from active gates, or miscalibrations of the control parameters. Quantitative understanding of these errors is critical for improving a device’s performance, as well as for informing design of the next generation of quantum processors. However, tomographic error reconstruction can be costly in both quantum computer runtime and classical post-processing overhead. In this talk, I will discuss a new class of error reconstruction methods we call “character phase estimation.” Our method leverages tools from representation theory to learn the rates of target errors, eliminate bias from extraneous errors, and dramatically simplify the data analysis. I’ll discuss how character phase estimation can be used to interpolate between randomized benchmarking and gate set tomography to produce a new family of scalable and robust tomography routines.
3:30 pm, Thursday, September 28, 2023
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