Mitigating errors in state preparation and measurement with noncomputational states

Error mitigation has enabled quantum computing applications with more than a hundred qubits and deep circuits. Many error mitigation methods are noise-aware, relying on a faithful characterization of the noise channels of the hardware. However, fundamental limitations lead to unlearnable degrees of freedom of the underlying noise models when considering qubits. Here, we show how to leverage noncomputational states as an additional resource to learn state-preparation errors in superconducting qubits. This allows one to fully constrain the noise models. We can thus independently and accurately mitigate state-preparation errors, gate errors, and measurement errors. Our proposed method is also applicable to dynamic circuits with midcircuit measurements. This work opens the door to improved error mitigation for measurements, both at the end of the circuit and midcircuit.

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Publication Details

Journal
Physical Review Applied
Published
2025-12-08
DOI
https://doi.org/10.1103/jv9h-spzw
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
0.00
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article

Mitigating errors in state preparation and measurement with noncomputational states

Karl J. Friston
Physical Review Applied
Quantum Computing Algorithms and Architecture
article

Mitigating errors in state preparation and measurement with noncomputational states

Karl J. Friston
article en

Abstract

Error mitigation has enabled quantum computing applications with more than a hundred qubits and deep circuits. Many error mitigation methods are noise-aware, relying on a faithful characterization of the noise channels of the hardware. However, fundamental limitations lead to unlearnable degrees of freedom of the underlying noise models when considering qubits. Here, we show how to leverage noncomputational states as an additional resource to learn state-preparation errors in superconducting qubits. This allows one to fully constrain the noise models. We can thus independently and accurately mitigate state-preparation errors, gate errors, and measurement errors. Our proposed method is also applicable to dynamic circuits with midcircuit measurements. This work opens the door to improved error mitigation for measurements, both at the end of the circuit and midcircuit.

Physical Review AppliedVol. 25(2)
IBM Research - Zurich (CH), École Polytechnique Fédérale de Lausanne (CH)
Openalex Percentile: Top 79%
Quantum Computing Algorithms and Architecture
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