Geometric Quantum Computation Framework

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

This paper introduces a novel geometric quantum computation framework designed to simulate and predict complex geometric shapes. Traditional computational methods often struggle with the inherent complexity of geometric data, requiring significant computational resources and time. This framework leverages quantum computation's unique capabilities – superposition, entanglement, and interference – to efficiently represent and manipulate geometric data, enabling novel modeling and analysis. We propose a layered architecture comprising a quantum state encoder, a geometric evolution simulator, and a readout mechanism, all underpinned by a sophisticated quantum algorithm for iterative refinement. The core mechanism centers around mapping geometric primitives into quantum states, facilitating rapid exploration of the space of possible shapes and their evolutions. The framework's design addresses challenges associated with geometric data representation and computation, offering the potential for significant advancements in areas like geometric modeling, simulations, and analysis.

DOI: 10.5281/zenodo.22503369

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