Title: Geometric Modeling of Parallel Computing for Quantum Algorithms

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

This paper introduces a novel geometric framework for modeling and optimizing parallel computing architectures, with a particular focus on quantum algorithms. Traditional approaches often rely on abstract descriptions and lack the necessary geometric representation to effectively analyze and optimize parallel computations. We propose a new system utilizing geometric primitives to represent quantum processors, data flow, and quantum gates, allowing for a deeper understanding of their interactions and facilitating the design of more efficient parallel algorithms. We detail the development of a geometric language, tools, and a methodology for capturing the essence of quantum computing through geometric abstraction. The core mechanism centers around establishing a correspondence between quantum states, quantum operations, and geometric transformations, enabling automated optimization of parallel execution. This represents a significant step towards a more intuitive and effective approach to parallel computing, particularly in the context of quantum algorithms.

DOI: 10.5281/zenodo.22293620

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