Efficient Simulation of Open Quantum Systems on NISQ Trapped-Ion Hardware

TL;DR

This paper introduces an efficient Kraus operator-based framework for simulating open quantum systems on NISQ hardware, avoiding Trotterization and employing error mitigation to improve accuracy, demonstrated on trapped-ion quantum computers.

Contribution

It presents a novel, resource-efficient method for simulating open quantum systems on NISQ devices using Kraus operators and Lindblad equations, with hardware-agnostic error mitigation techniques.

Findings

Accurate simulation of quantum channels on trapped-ion hardware

Error mitigation techniques significantly improve fidelity

Kraus-based approach outperforms traditional Trotterization methods

Abstract

Simulating open quantum systems, which interact with external environments, presents significant challenges on noisy intermediate-scale quantum (NISQ) devices due to limited qubit resources and noise. In this paper, we propose an efficient framework for simulating open quantum systems on NISQ hardware by leveraging a time-perturbative Kraus operator representation of the system's dynamics. Our approach avoids the computationally expensive Trotterization method and exploits the Lindblad master equation to represent time evolution in a compact form, particularly for systems satisfying specific commutation relations. We demonstrate the efficiency of our method by simulating quantum channels, such as the continuous-time Pauli channel and damped harmonic oscillators, on NISQ trapped-ion hardware, including IonQ Harmony and Quantinuum H1-1. Additionally, we introduce hardware-agnostic error mitigation techniques, including Pauli channel fitting and quantum depolarizing channel inversion, to enhance the fidelity of quantum simulations. Our results show strong agreement between the simulations on real quantum hardware and exact solutions, highlighting the potential of Kraus-based methods for scalable and accurate simulation of open quantum systems on NISQ devices. This framework opens pathways for simulating more complex systems under realistic conditions in the near term.