Noise Reversal by Entropy Quantum Computing

TL;DR

This paper introduces an entropy quantum computing method that observes and reproduces quantum noise properties to effectively reverse noise in optical data, improving signal clarity in high-sensitivity measurements.

Contribution

It presents a novel hardware-based noise removal technique using entropy quantum computing to emulate and reverse quantum noise in optical systems.

Findings

Successfully recovers 1D and 2D images with high noise levels

Demonstrates noise reversal by reproducing quantum statistical properties

Enhances signal-to-noise ratio in optical data

Abstract

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.