Self-Adaptive Spin State Entanglement for Enhanced Quantum Computation

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum computation offers unprecedented computational power, but maintaining and manipulating entangled states remains a significant challenge. This paper investigates a novel approach to enhance quantum computation through the implementation of self-adaptive spin state entanglement. We propose a mechanism that dynamically adjusts the entanglement strength, optimizing the system for improved performance and efficiency. The core of this approach lies in the concept of self-calibration, enabling the system to maintain a desired entanglement level without requiring explicit control. This results in a more robust and adaptable entanglement, potentially unlocking new capabilities within quantum algorithms. The study involves a detailed analysis of the impact of this self-calibration on various quantum processing tasks, demonstrating significant efficiency gains. This work represents a fundamental shift in how we approach entanglement management, paving the way for more sophisticated and practical quantum systems.

DOI: 10.5281/zenodo.22201188

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