Perturbative readout error mitigation for near term quantum computers
Evan Peters, Andy C. Y. Li, Gabriel N. Perdue

TL;DR
This paper introduces perturbative methods to efficiently mitigate readout errors in near-term quantum computers, significantly reducing resource requirements while maintaining accuracy under low-error conditions.
Contribution
It develops two perturbative approximation techniques for readout error mitigation that scale more favorably than traditional methods, enabling faster and resource-efficient error correction.
Findings
Achieves polynomial speedup in error mitigation process
Recovers specific output probabilities with bounded error
Provides a generalized approach for full distribution recovery
Abstract
Readout errors on near-term quantum computers can introduce significant error to the empirical probability distribution sampled from the output of a quantum circuit. These errors can be mitigated by classical postprocessing given the access of an experimental \emph{response matrix} that describes the error associated with measurement of each computational basis state. However, the resources required to characterize a complete response matrix and to compute the corrected probability distribution scale exponentially in the number of qubits . In this work, we modify standard matrix inversion techniques using two perturbative approximations with significantly reduced complexity and bounded error when the likelihood of high order bitflip events is strongly suppressed. Given a characteristic error rate , our first method recovers the probability of the all-zeros bitstring by…
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