Maximum Likelihood Quantum Error Mitigation for Algorithms with a Single Correct Output
CoRR(2024)
摘要
Quantum error mitigation is an important technique to reduce the impact of
noise in quantum computers. With more and more qubits being supported on
quantum computers, there are two emerging fundamental challenges. First, the
number of shots required for quantum algorithms with large numbers of qubits
needs to increase in order to obtain a meaningful distribution or expected
value of an observable. Second, although steady progress has been made in
improving the fidelity of each qubit, circuits with a large number of qubits
are likely to produce erroneous results. This low-shot, high-noise regime calls
for highly scalable error mitigation techniques. In this paper, we propose a
simple and effective mitigation scheme, qubit-wise majority vote, for quantum
algorithms with a single correct output. We show that our scheme produces the
maximum likelihood (ML) estimate under certain assumptions, and bound the
number of shots required. Our experimental results on real quantum devices
confirm that our proposed approach requires fewer shots than existing ones, and
can sometimes recover the correct answers even when they are not observed from
the measurement results.
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