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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2408.12271 |
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| _version_ | 1866914920761655296 |
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| author | Kalita, Sampreet Sarma, Amarendra K. |
| author_facet | Kalita, Sampreet Sarma, Amarendra K. |
| contents | The exploration of deep neural networks for optimal control has gathered a considerable amount of interest in recent years. Here, we utilize deep reinforcement learning to control individual evolutions of coupled harmonic oscillators in an oscillator network. Our work showcases a numerical approach to actively cool internal oscillators to their thermal ground states through modulated forces imparted to the external oscillators in the network. We present our results for thermal cooling of all oscillators in multiple network configurations and introduce the utility of our scheme in the quantum regime. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_12271 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Domino-cooling Oscillator Networks with Deep Reinforcement Learning Kalita, Sampreet Sarma, Amarendra K. Quantum Physics Data Analysis, Statistics and Probability The exploration of deep neural networks for optimal control has gathered a considerable amount of interest in recent years. Here, we utilize deep reinforcement learning to control individual evolutions of coupled harmonic oscillators in an oscillator network. Our work showcases a numerical approach to actively cool internal oscillators to their thermal ground states through modulated forces imparted to the external oscillators in the network. We present our results for thermal cooling of all oscillators in multiple network configurations and introduce the utility of our scheme in the quantum regime. |
| title | Domino-cooling Oscillator Networks with Deep Reinforcement Learning |
| topic | Quantum Physics Data Analysis, Statistics and Probability |
| url | https://arxiv.org/abs/2408.12271 |