Noise Reversal by Entropy Quantum Computing

Fuente: arXiv
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Main Authors: Huang, Yu-Ping, Hu, Yongxiang
Format: Preprint
Published: 2025
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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