Quantum Utility-Scale Error Mitigation for Quantum Quench Dynamics in Heisenberg Spin Chains
Seokwon Choi, Talal Ahmed Chowdhury, Kwangmin Yu

TL;DR
This paper introduces a self-mitigation quantum error correction method that enhances the accuracy of quantum quench dynamics simulations on large, noisy quantum computers, surpassing classical simulation capabilities.
Contribution
The paper presents a novel self-mitigation error mitigation technique and demonstrates its effectiveness for large-scale quantum simulations up to 104 qubits.
Findings
Self-mitigation maintains accuracy on 104-qubit systems with over 3,000 CNOT gates.
Combining error mitigation with entanglement entropy measurements aligns well with theoretical predictions.
The method enables studying many-body quantum dynamics on near-term quantum hardware.
Abstract
We propose a quantum error mitigation method termed self-mitigation, which is comparable with zero-noise extrapolation, to achieve quantum utility on near-term, noisy quantum computers. We investigate the effectiveness of several quantum error mitigation strategies, including self-mitigation, by simulating quantum quench dynamics for Heisenberg spin chains with system sizes up to 104 qubits using IBM quantum processors. In particular, we discuss the limitations of zero-noise extrapolation and the advantages offered by self-mitigation at a large scale. The self-mitigation method shows stable accuracy with the large systems of 104 qubits with more than 3,000 CNOT gates. Also, we combine the discussed quantum error mitigation methods with practical entanglement entropy measuring methods, and it shows a good agreement with the theoretical estimation. Our study illustrates the usefulness of…
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Taxonomy
TopicsQuantum many-body systems · Quantum Computing Algorithms and Architecture · Neural Networks and Reservoir Computing
