Error mitigation in brainbox quantum autoencoders
Abstract Quantum hardware faces noise challenges that disrupt multiqubit entangled states. Quantum autoencoder circuits with a single qubit bottleneck have demonstrated the capability to correct errors in noisy entangled states. By introducing slightly more complex structures in the bottleneck, refe...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-01-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-024-84171-z |
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| author | Joséphine Pazem Mohammad H. Ansari |
| author_facet | Joséphine Pazem Mohammad H. Ansari |
| author_sort | Joséphine Pazem |
| collection | DOAJ |
| description | Abstract Quantum hardware faces noise challenges that disrupt multiqubit entangled states. Quantum autoencoder circuits with a single qubit bottleneck have demonstrated the capability to correct errors in noisy entangled states. By introducing slightly more complex structures in the bottleneck, referred to as brainboxes, the denoising process can occure more quickly and efficiently in the presence of stronger noise channels. Selecting the most suitable brainbox for the bottleneck involves a trade-off between the intensity of noise on the hardware and training complexity. Finally, by analysing the Rényi entropy flow throughout the networks, we demonstrate that the localization of entanglement plays a central role in denoising through learning. |
| format | Article |
| id | doaj-art-5153b2205c1a4d1d9e4469028306cc18 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-5153b2205c1a4d1d9e4469028306cc182025-01-19T12:22:12ZengNature PortfolioScientific Reports2045-23222025-01-0115111210.1038/s41598-024-84171-zError mitigation in brainbox quantum autoencodersJoséphine Pazem0Mohammad H. Ansari1Institut für Theoretische Physik, Universität InnsbruckPeter Grünberg Institute (PGI-2), Forschungszentrum JülichAbstract Quantum hardware faces noise challenges that disrupt multiqubit entangled states. Quantum autoencoder circuits with a single qubit bottleneck have demonstrated the capability to correct errors in noisy entangled states. By introducing slightly more complex structures in the bottleneck, referred to as brainboxes, the denoising process can occure more quickly and efficiently in the presence of stronger noise channels. Selecting the most suitable brainbox for the bottleneck involves a trade-off between the intensity of noise on the hardware and training complexity. Finally, by analysing the Rényi entropy flow throughout the networks, we demonstrate that the localization of entanglement plays a central role in denoising through learning.https://doi.org/10.1038/s41598-024-84171-z |
| spellingShingle | Joséphine Pazem Mohammad H. Ansari Error mitigation in brainbox quantum autoencoders Scientific Reports |
| title | Error mitigation in brainbox quantum autoencoders |
| title_full | Error mitigation in brainbox quantum autoencoders |
| title_fullStr | Error mitigation in brainbox quantum autoencoders |
| title_full_unstemmed | Error mitigation in brainbox quantum autoencoders |
| title_short | Error mitigation in brainbox quantum autoencoders |
| title_sort | error mitigation in brainbox quantum autoencoders |
| url | https://doi.org/10.1038/s41598-024-84171-z |
| work_keys_str_mv | AT josephinepazem errormitigationinbrainboxquantumautoencoders AT mohammadhansari errormitigationinbrainboxquantumautoencoders |