Quantum Entanglement Non-Linear Computation: Adaptive Noise Injection

Jincheng Zhang

Published Sep 2, 2026• 0 citations

Abstract

Quantum entanglement, a cornerstone of quantum mechanics, offers unprecedented computational capabilities. However, its delicate nature makes it susceptible to decoherence, leading to errors in computations. This paper investigates a novel approach to mitigate these vulnerabilities through the implementation of adaptive noise injection within a quantum computation framework. We propose a system where the rate and type of noise injected are dynamically adjusted based on the state of the entangled qubits, effectively enhancing the stability and accuracy of the resulting quantum state. The core mechanism centers around leveraging the inherent fragility of entanglement to guide its evolution. This research explores the potential of this self-adaptive strategy to significantly improve the performance of quantum computations.

DOI: 10.5281/zenodo.22246600

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