Edwin Pednault

Jul 28, 2023 | link.aps.org | Arkopal Dutt |Edwin Pednault |IBM Quantum |Yorktown Heights

Abstract Hamiltonian learning is an important procedure in quantum system identification, calibration, and successful operation of quantum computers. Through queries to the quantum system, this procedure seeks to obtain the parameters of a given Hamiltonian model and description of noise sources. Standard techniques for Hamiltonian learning require careful design of queries and O(ε−2) queries in achieving learning error ε due to the standard quantum limit.