Efficient correction of multiqubit measurement errors

Abstract

State preparation and measurement (SPAM) errors limit the performance of near-term quantum computers and their potential for practical application. SPAM errors are partly correctable after a calibration step that requires, for a complete implementation on a register of $n$ qubits, $2^n$ additional measurements. Here we introduce an approximate but efficient method for multiqubit SPAM error characterization and mitigation requiring the classical processing of $2^n\times 2^n$ matrices, but only $O(4^k{n}^2)$ measurements, where $k=O(1)$ is the number of qubits in a correlation volume. We demonstrate and validate the technique using an IBM Q processor on registers of 4 and 8 superconducting qubits.

References in corpus (3)

• Surface codes: Towards practical large-scale quantum computation
• Machine learning for discriminating quantum measurement trajectories and improving readout
• Rigorous measurement error correction

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