Noise Reversal by Entropy Quantum Computing
Fuente:
arXiv
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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866929712096346112 |
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| author | Huang, Yu-Ping Hu, Yongxiang |
| author_facet | Huang, Yu-Ping Hu, Yongxiang |
| contents | Signal to noise ratio is key to any measurement. Recent progress in semi/super-conductor technology have pushed the signal detection sensitivity to the ultimate quantum level, but the noise issue remains largely untouched and, in many cases, becomes even more severe because of the high sensitivity. In this paper, we explore a hardware-based approach to noise removal using entropy quantum computing. Distinct to any existing de-noising approach, it observes and reproduces the quantum statistical properties of noise in an optical system to emulate and thereby reverse the noise from data. We show how it can recover 1D and 2D image data mixed with much stronger noise. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_08591 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Noise Reversal by Entropy Quantum Computing Huang, Yu-Ping Hu, Yongxiang Quantum Physics Signal to noise ratio is key to any measurement. Recent progress in semi/super-conductor technology have pushed the signal detection sensitivity to the ultimate quantum level, but the noise issue remains largely untouched and, in many cases, becomes even more severe because of the high sensitivity. In this paper, we explore a hardware-based approach to noise removal using entropy quantum computing. Distinct to any existing de-noising approach, it observes and reproduces the quantum statistical properties of noise in an optical system to emulate and thereby reverse the noise from data. We show how it can recover 1D and 2D image data mixed with much stronger noise. |
| title | Noise Reversal by Entropy Quantum Computing |
| topic | Quantum Physics |
| url | https://arxiv.org/abs/2502.08591 |