Femtojoule-per-operation photonic computer for the subset sum problem
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arXiv
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| Main Authors: | , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866915460557045760 |
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| author | Zhang, Tian-Yu Xu, Xiao-Yun Zhou, Wen-Hao Wang, Xiao-Wei Wang, Chu-Han Chang, Yi-Jun Yang, Ying-Yue Ma, Jie Zhu, Ka-Di Jin, Xian-Min |
| author_facet | Zhang, Tian-Yu Xu, Xiao-Yun Zhou, Wen-Hao Wang, Xiao-Wei Wang, Chu-Han Chang, Yi-Jun Yang, Ying-Yue Ma, Jie Zhu, Ka-Di Jin, Xian-Min |
| contents | Energy-efficient computing is becoming increasingly important in the information era. However, electronic computers with von Neumann architecture can hardly meet the challenge due to the inevitable energy-intensive data movement, especially when tackling computationally hard problems or complicated tasks. Here, we experimentally demonstrate an energy-efficient photonic computer that solves intractable subset sum problem (SSP) by making use of the extremely low energy level of photons (~10^(-19) J) and a time-of-flight storage technique. We show that the energy consumption of the photonic computer maintains no larger than 10^(-15) J per operation at a reasonably large problem size N=33, and it consumes 10^(8) times less energy than the most energy-efficient supercomputer for a medium-scale problem. In addition, when the photonic computer is applied to deal with real-life problems that involves iterative computation of the SSP, the photonic advantage in energy consumption is further enhanced and massive energy can be saved. Our results indicate the superior competitiveness of the photonic computer in the energy costs of complex computation, opening a possible path to green computing. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_17274 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Femtojoule-per-operation photonic computer for the subset sum problem Zhang, Tian-Yu Xu, Xiao-Yun Zhou, Wen-Hao Wang, Xiao-Wei Wang, Chu-Han Chang, Yi-Jun Yang, Ying-Yue Ma, Jie Zhu, Ka-Di Jin, Xian-Min Optics Quantum Physics Energy-efficient computing is becoming increasingly important in the information era. However, electronic computers with von Neumann architecture can hardly meet the challenge due to the inevitable energy-intensive data movement, especially when tackling computationally hard problems or complicated tasks. Here, we experimentally demonstrate an energy-efficient photonic computer that solves intractable subset sum problem (SSP) by making use of the extremely low energy level of photons (~10^(-19) J) and a time-of-flight storage technique. We show that the energy consumption of the photonic computer maintains no larger than 10^(-15) J per operation at a reasonably large problem size N=33, and it consumes 10^(8) times less energy than the most energy-efficient supercomputer for a medium-scale problem. In addition, when the photonic computer is applied to deal with real-life problems that involves iterative computation of the SSP, the photonic advantage in energy consumption is further enhanced and massive energy can be saved. Our results indicate the superior competitiveness of the photonic computer in the energy costs of complex computation, opening a possible path to green computing. |
| title | Femtojoule-per-operation photonic computer for the subset sum problem |
| topic | Optics Quantum Physics |
| url | https://arxiv.org/abs/2508.17274 |