Parameterized Hamiltonian simulation using quantum optimal control

TL;DR

This paper presents a new method combining digital decomposition and optimal control to enhance analog quantum Hamiltonian simulation, demonstrated on a superconducting transmon device for simulating an extended Bose-Hubbard model.

Contribution

It introduces a paradigm that integrates digital and optimal control techniques for more accurate and robust analog quantum simulation on hardware-specific devices.

Findings

Optimal controls improve simulation accuracy

Control time and pulse complexity affect robustness

Method applicable to near-term quantum devices

Abstract

Analog quantum simulation offers a hardware-specific approach to studying quantum dynamics, but mapping a model Hamiltonian onto the available device parameters requires matching the hardware dynamics. We introduce a paradigm for quantum Hamiltonian simulation that leverages digital decomposition techniques and optimal control to perform analog simulation. We validate this approach by constructing the optimal analog controls for a superconducting transmon device to emulate the dynamics of an extended Bose-Hubbard model. We demonstrate the role of control time, digital error, and pulse complexity, and we explore the accuracy and robustness of these controls. We conclude by discussing the opportunity for implementing this paradigm in near-term quantum devices.