We present an extension to the robust phase estimation protocol, which can identify incorrect results that would otherwise lie outside expected statistical range. Robust is increasingly a method of choice for applications such as estimating effective process parameters noisy hardware, but its robustness dependent on noise satisfying certain threshold assumptions. provide consistency checks indi...

Abstract We explore why many recently proposed robust estimation problems are efficiently solvable, even though the underlying optimization non-convex. study loss landscape of these problems, and identify existence ’generalized quasi-gradients’. Whenever quasi-gradients exist, a large family no-regret algorithms guaranteed to approximate global minimum; this includes commonly used filtering alg...