Physical Computing at the Data Processing Inequality Limit
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arXiv
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| Hauptverfasser: | , , , , , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| author | Zheng, Yuhang Zhao, Yang Zou, Xiuting Zhao, Chunyu Yu, Zhiyi Li, Zechen Wu, Jiaxing Xu, Shaofu Zou, Weiwen |
| author_facet | Zheng, Yuhang Zhao, Yang Zou, Xiuting Zhao, Chunyu Yu, Zhiyi Li, Zechen Wu, Jiaxing Xu, Shaofu Zou, Weiwen |
| contents | Wave-physics-based intelligent sensing has driven multidisciplinary applications from smart industries to decision-making systems. Traditional sensing paradigms transform physical waveforms into human-understandable intermediate representations through preprocessing. Such transformations inherently cause information loss owing to data processing inequality (DPI). Here, we established a theoretical framework for physical computing at the DPI upper limit. Physical computing avoids information loss during preprocessing by directly extracting information from physical waveforms, achieving the theoretical maximum of accessible information as determined by the DPI. Furthermore, physical computing comprehensively utilizes multiple dimensions of physical waveforms, thereby enhancing the upper limit of information capture capability. Electromagnetic sensing experiments have demonstrated that physical computing can achieve 100% sensing accuracy, substantially outperforming traditional sensing paradigms. The proposed theoretical framework of physical computing offers a promising path towards enhancing the information-capture capability of next-generation intelligent sensing systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_17233 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Physical Computing at the Data Processing Inequality Limit Zheng, Yuhang Zhao, Yang Zou, Xiuting Zhao, Chunyu Yu, Zhiyi Li, Zechen Wu, Jiaxing Xu, Shaofu Zou, Weiwen Applied Physics Wave-physics-based intelligent sensing has driven multidisciplinary applications from smart industries to decision-making systems. Traditional sensing paradigms transform physical waveforms into human-understandable intermediate representations through preprocessing. Such transformations inherently cause information loss owing to data processing inequality (DPI). Here, we established a theoretical framework for physical computing at the DPI upper limit. Physical computing avoids information loss during preprocessing by directly extracting information from physical waveforms, achieving the theoretical maximum of accessible information as determined by the DPI. Furthermore, physical computing comprehensively utilizes multiple dimensions of physical waveforms, thereby enhancing the upper limit of information capture capability. Electromagnetic sensing experiments have demonstrated that physical computing can achieve 100% sensing accuracy, substantially outperforming traditional sensing paradigms. The proposed theoretical framework of physical computing offers a promising path towards enhancing the information-capture capability of next-generation intelligent sensing systems. |
| title | Physical Computing at the Data Processing Inequality Limit |
| topic | Applied Physics |
| url | https://arxiv.org/abs/2512.17233 |