Noise-agnostic quantum error mitigation with data augmented neural models
Abstract Quantum error mitigation, a data processing technique for recovering the statistics of target processes from their noisy version, is a crucial task for near-term quantum technologies. Most existing methods require prior knowledge of the noise model or the noise parameters. Deep neural netwo...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-01-01
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| Series: | npj Quantum Information |
| Online Access: | https://doi.org/10.1038/s41534-025-00960-y |
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