Dynamic Probability Field Based on Topological Computation

Jincheng Zhang

Published Sep 2, 2026• 0 citations

Abstract

The study of dynamic probability fields explores how systems evolve through complex interactions, offering a powerful framework for modeling phenomena in diverse fields, from finance to biology. This paper investigates a novel dynamic probability field model based on topological computation, leveraging quantum entanglement and topology to dynamically adjust probability fields and generate diverse future states. The core mechanism centers around a "quantum topological jump" – a mechanism that accelerates and expands quantum operations through instantaneous entanglement, and uses topological structure to predict future states. This approach contrasts with traditional chaos theory, offering a mechanism for adaptive decision-making through real-time response to environmental changes. The model's design emphasizes the potential for self-adaptive strategies, generating multiple possible future outcomes based on the interplay of entangled quantum states. This research introduces a framework that can dynamically adjust probability fields, offering a pathway for advanced decision-making.

DOI: 10.5281/zenodo.22248544

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