Quantum Energetic Advantage before Computational Advantage in Boson Sampling
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arXiv
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| Autori principali: | , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866911373936558080 |
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| author | Soret, Ariane Dridi, Nessim Wein, Stephen C. Giesz, Valérian Mansfield, Shane Emeriau, Pierre-Emmanuel |
| author_facet | Soret, Ariane Dridi, Nessim Wein, Stephen C. Giesz, Valérian Mansfield, Shane Emeriau, Pierre-Emmanuel |
| contents | Understanding the energetic efficiency of quantum computers is essential for assessing their scalability and for determining whether quantum technologies can outperform classical computation beyond runtime alone. In this work, we analyze the energy required to solve the Boson Sampling problem, a paradigmatic task for quantum advantage, using a realistic photonic quantum computing architecture. Using the Metric-Noise-Resource methodology, we establish a quantitative connection between experimental control parameters, dominant noise processes, and energetic resources through a performance metric tailored to Boson Sampling. We estimate the energy cost per sample and identify operating regimes that optimize energetic efficiency. By comparing the energy consumption of quantum and state-of-the-art classical implementations, we demonstrate the existence of a quantum energetic advantage -- defined as a lower energy cost per sample compared to the best-known classical implementation -- that emerges before the onset of computational advantage, even in regimes where classical algorithms remain faster. Finally, we propose an experimentally feasible Boson Sampling architecture, including a complete noise and loss budget, that enables a near-term observation of quantum energetic advantage. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_08068 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Quantum Energetic Advantage before Computational Advantage in Boson Sampling Soret, Ariane Dridi, Nessim Wein, Stephen C. Giesz, Valérian Mansfield, Shane Emeriau, Pierre-Emmanuel Quantum Physics Understanding the energetic efficiency of quantum computers is essential for assessing their scalability and for determining whether quantum technologies can outperform classical computation beyond runtime alone. In this work, we analyze the energy required to solve the Boson Sampling problem, a paradigmatic task for quantum advantage, using a realistic photonic quantum computing architecture. Using the Metric-Noise-Resource methodology, we establish a quantitative connection between experimental control parameters, dominant noise processes, and energetic resources through a performance metric tailored to Boson Sampling. We estimate the energy cost per sample and identify operating regimes that optimize energetic efficiency. By comparing the energy consumption of quantum and state-of-the-art classical implementations, we demonstrate the existence of a quantum energetic advantage -- defined as a lower energy cost per sample compared to the best-known classical implementation -- that emerges before the onset of computational advantage, even in regimes where classical algorithms remain faster. Finally, we propose an experimentally feasible Boson Sampling architecture, including a complete noise and loss budget, that enables a near-term observation of quantum energetic advantage. |
| title | Quantum Energetic Advantage before Computational Advantage in Boson Sampling |
| topic | Quantum Physics |
| url | https://arxiv.org/abs/2601.08068 |