Using random walks for iterative phase estimation

Abstract

The disclosed technology concerns example embodiments for estimating eigenvalues of quantum operations using a quantum computer. Such estimations are useful in performing Shor's algorithm for factoring, quantum simulation, quantum machine learning, and other various quantum computing applications. Existing approaches to phase estimation are sub-optimal, difficult to program, require prohibitive classical computing, and/or require too much classical or quantum memory to be run on existing devices. Embodiments of the disclosed approach address one or more (e.g., all) of these drawbacks. Certain examples work by using a random walk for the estimate of the eigenvalue that (e.g., only) keeps track of the current estimate and the measurement record that it observed to reach that point.