Title: Self-Organizing Constraint Systems for Quantum Computation

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum computation, a revolutionary field, demands highly precise and stable quantum circuits. Traditional constrained quantum circuits, while effective, often struggle with complex gate sequences and limited scalability, leading to significant error rates. This research proposes a novel self-organizing constraint system – Dynamic Entanglement Sculpting – designed to address these challenges. The system dynamically optimizes entanglement patterns, enabling the creation of complex quantum circuits with substantially reduced error rates. This work utilizes a machine learning-driven model to continuously adapt the entanglement structure, resulting in enhanced circuit fidelity and scalability. We demonstrate the effectiveness of this approach through simulation and preliminary experimental validation. The core claim is that this system facilitates the design of complex quantum circuits with significantly reduced error rates, offering a substantial improvement over existing constrained quantum circuit approaches.

DOI: 10.5281/zenodo.22190166

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