Learning and forecasting open quantum dynamics with correlated noise
Abstract The development of practical quantum processors relies on the ability to control and predict their functioning despite the presence of noise. This is particularly challenging for temporarily correlated noise. Here we propose a physics-inspired supervised machine learning approach to efficie...
محفوظ في:
| المؤلفون الرئيسيون: | , , , , , , , , , , , , , , |
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| التنسيق: | Artigo |
| اللغة: | Inglês |
| منشور في: |
Nature Portfolio
2025-01-01
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| سلاسل: | Communications Physics |
| الوصول للمادة أونلاين: | https://doi.org/10.1038/s42005-025-01944-2 |
| الوسوم: |
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