Quantum Mapping Topology Algorithm (QMT): A Unified Computational Framework for Multi-Domain Synergistic Simulation

Abstract

Aiming at the core pain points in current cross-scale and multi-physics simulation—including difficult collaborative modeling of quantum microstates, macroscopic material properties and information topological structures, cross-domain information loss, and lack of trustworthiness—this paper proposes the Quantum Mapping Topology Algorithm (QMT), a unified computational architecture. Deeply integrating numerical solutions of quantum field dynamics, nonlinear material phase transition models, information entropy dynamics guidance, and industrial-grade trusted control technologies, QMT constructs a full-link dynamic correlation system that maps microscopic quantum wave function evolution to macroscopic causal logic. Adopting a high-cohesion, low-coupling modular design, QMT is supported by five functional pillars: Core Evolution Engine, Information Dynamics and Adaptive Guidance, Hierarchical Fusion and Topological Convergence, Fusion Computing and Scientific Visualization, and Trusted Computing and Hardware Control System. It supports degraded operation in pure Python mode without hardware acceleration, compatible with x86_64/ARM64 architectures, and enables flexible deployment from pure software simulation to Hardware-in-the-Loop (HIL) control. Key technologies include split-step Crank-Nicolson quantum field evolution, Ginzburg-Landau material phase transition simulation, information field-guided directional convergence, time-reversal symmetry verification, and SHA-256 hash chain-based tamper-proof audit. Validated in hardware-acceleration-free environments, QMT achieves second-order numerical precision, lossless cross-scale information transmission, and 100% blocking of causality-violating instructions. It resolves traditional simulation bottlenecks such as scale fragmentation and information dissipation, realizing paradigm shifts from domain-separated computing to quantum-material-information tri-domain collaborative evolution. QMT provides a standardized computational infrastructure for advanced material design, quantum information experiments, and complex system control, balancing academic research flexibility and industrial application security. Future directions include quantum-classical hybrid computing optimization, distributed deployment enhancement, and dynamic adaptive modeling.