Based on Adaptive Topology for Quantum Probability Computation

Jincheng Zhang

Published Sep 7, 2026• 0 citations

Abstract

Quantum probability computation (QPC) is a rapidly developing field with significant potential for breakthroughs in quantum information processing. Traditional QPC approaches often rely on computationally intensive classical algorithms, limiting their scalability and applicability. This paper introduces a novel QPC algorithm, termed Adaptive Topology-Based Quantum Probability Computation (QPC), that leverages the inherent properties of self-adjoint structures to optimize quantum probability calculations. The core mechanism of this algorithm hinges on dynamically adjusting the topology of the quantum system to enhance the fidelity and speed of the computation. The proposed method offers a fundamentally different approach compared to existing QPC techniques, promising substantial improvements in computational efficiency and scalability. This paper provides a comprehensive theoretical analysis and practical implementation of the QPC algorithm, demonstrating its effectiveness through rigorous numerical simulations and preliminary experimental results.

DOI: 10.5281/zenodo.22601137

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