Mitigating algorithmic errors in Hamiltonian simulation

TL;DR

This paper explores balancing Trotter step number and physical error mitigation in quantum Hamiltonian simulation, proposing a combined approach to reduce total simulation errors on near-term quantum hardware.

Contribution

It introduces a method to mitigate both algorithmic and physical errors in Hamiltonian simulation by optimizing Trotter steps and extending error mitigation techniques.

Findings

Optimal Trotter step number identified for given physical error models.

Combined error mitigation significantly improves simulation accuracy.

Numerical tests on a five-qubit system validate the approach.

Abstract

Quantum computers can efficiently simulate many-body systems. As a widely used Hamiltonian simulation tool, the Trotter-Suzuki scheme splits the evolution into the number of Trotter steps $N$ and approximates the evolution of each step by a product of exponentials of each individual term of the total Hamiltonian. The algorithmic error due to the approximation can be reduced by increasing $N$, which however requires a longer circuit and hence inevitably introduces more physical errors. In this work, we first study such a trade-off and numerically find the optimal number of Trotter steps $N_{\textrm{opt}}$ given a physical error model in a near-term quantum hardware. Practically, physical errors can be suppressed using recently proposed error mitigation methods. We then extend physical error mitigation methods to suppress the algorithmic error in Hamiltonian simulation. By exploiting the simulation results with different numbers of Trotter steps $N\le N_{\textrm{opt}}$, we can infer the exact simulation result within a higher accuracy and hence mitigate algorithmic errors. We numerically test our scheme with a five qubit system and show significant improvements in the simulation accuracy by applying both physical and algorithmic error mitigations.