Optimized Experiment Design and Analysis for Fully Randomized Benchmarking

Explore the advantages of fully randomized benchmarking (RB) in assessing quantum gate quality during a 59-minute talk by Alexander Kwiatkowski at QuICS. Discover how full randomization improves upon current RB implementations by offering smaller confidence intervals, enabling maximum likelihood analysis without heuristics, and allowing for straightforward sequence length optimization. Learn about the technique's ability to model and measure behaviors beyond the basic RB model, such as gate-position-dependent and time-dependent errors. Examine concrete protocols for minimizing uncertainty in parameter estimation within time constraints, and understand the flexible maximum likelihood analysis approach. Review potential improvements in past experiments and observe real-world benefits demonstrated in ion trap experiments at NIST, where optimized fully randomized benchmarking significantly reduced step error uncertainty compared to traditional methods.

Alexander Kwiatkowski: Optimized experiment design and analysis for fully randomized benchmarking