Variational optimization for quantum problems using deep generative networks
Abstract Optimization drives advances in quantum science and machine learning, yet most generative models aim to mimic data rather than to discover optimal answers to challenging problems. Here we present a variational generative optimization network that learns to map simple random inputs into high...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-08-01
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| Series: | Communications Physics |
| Online Access: | https://doi.org/10.1038/s42005-025-02261-4 |
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