Efficient separate quantification of state preparation errors and measurement errors on quantum computers and their mitigation
ORAL
Abstract
Current noisy quantum computers have multiple types of errors, which can occur in the state preparation, measurement/readout, and gate operation, as well as intrinsic decoherence and relaxation. Partly motivated by the booming of intermediate-scale quantum processors, measurement and gate errors have been recently extensively studied, and several methods of mitigating them have been proposed and formulated in software packages (e.g., in IBM Qiskit). Despite this, the state preparation error and the procedure to quantify it have not yet been standardized, as state preparation and measurement errors are usually considered not directly separable. Inspired by a recent work of Laflamme, Lin and Mor [Phys. Rev. A 106, 012439 (2022)], we propose a simple and resource-efficient approach to quantify separately the state preparation and readout error rates. With these two errors separately quantified, we also propose methods to mitigate them separately, especially mitigating state preparation errors with linear (with the number of qubits) complexity. As a result of the separate mitigation, we show that the fidelity of the outcome can be improved by an order compared to the standard measurement error mitigation scheme, and such mitigation scheme can be immediately applied to current noisy quantum computers. To demonstrate the quantification and mitigation schemes, we present results from cloud experiments on IBM's superconducting quantum computers. The results indicate that the state preparation error rate is also an important metric for qubit metrology.
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Presenters
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Hongye Yu
Stony Brook University (SUNY)
Authors
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Hongye Yu
Stony Brook University (SUNY)
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Tzu-Chieh Wei
Stony Brook University (SUNY)