Optimization of CV-QKD Under Practical Constraints
Fuente:
arXiv
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| Autores principales: | , , , , |
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| Formato: | Preprint |
| Publicado: |
2026
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866918479803711488 |
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| author | Matsenko, Svitlana Ghazisaeidi, Amirhossein Jarzyna, Marcin Banaszek, Konrad Zibar, Darko |
| author_facet | Matsenko, Svitlana Ghazisaeidi, Amirhossein Jarzyna, Marcin Banaszek, Konrad Zibar, Darko |
| contents | Using reinforcement learning, we optimize for practical hardware constraints, including limited FIR filter taps at the transmitter and receiver, mean photon number and finite DAC/ADC resolution. Under these realistic conditions, the proposed approach achieves significant performance improvements. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_02045 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Optimization of CV-QKD Under Practical Constraints Matsenko, Svitlana Ghazisaeidi, Amirhossein Jarzyna, Marcin Banaszek, Konrad Zibar, Darko Information Theory Artificial Intelligence Quantum Physics Using reinforcement learning, we optimize for practical hardware constraints, including limited FIR filter taps at the transmitter and receiver, mean photon number and finite DAC/ADC resolution. Under these realistic conditions, the proposed approach achieves significant performance improvements. |
| title | Optimization of CV-QKD Under Practical Constraints |
| topic | Information Theory Artificial Intelligence Quantum Physics |
| url | https://arxiv.org/abs/2605.02045 |