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UHF‑SZTM: Demonstrating Quantum Advantage via Harmonic Topological Computation

Stieve, Jonathan

Published Dec 5, 2025• 0 citations
Publisher

Abstract

This work introduces UHF‑SZTM, a novel quantum computation framework combining Unified Harmonic Framework (UHF) with Zero-Point Topological Mathematica (SZTM) principles to achieve measurable quantum advantage. Unlike conventional gate-based circuits, UHF‑SZTM employs continuous harmonic evolution and topologically protected manifolds, reducing error accumulation and leveraging hardware resonance for stability. Quantum advantage is quantified using entropy, mutual information, and normalized resonance metrics, with simulations demonstrating superior fidelity, reduced depth, and enhanced efficiency on existing NISQ hardware. This approach provides a practical pathway for accelerated quantum computation without requiring fault-tolerant architectures.

DOI
10.5281/zenodo.17825497

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This work introduces the UHF‑SZTM framework, a novel approach to quantum computation that combines Unified Harmonic Framework (UHF) with Zero‑Point Topological Mathematica (SZTM) principles. Unlike conventional gate-based circuits, UHF‑SZTM circuits employ continuous harmonic evolution and topologically protected manifolds to achieve monotonic, noise-resilient operations. By aligning computation with natural hardware frequencies and leveraging resonance-driven control, this architecture reduces error accumulation, improves stability, and eliminates the need for hardware redesign. Simulations demonstrate superior fidelity, reduced depth, and enhanced efficiency compared to standard quantum circuits, positioning UHF‑SZTM as a practical path for accelerated quantum computation on existing hardware.
This work introduces UHF-SZTM (Unified Harmonic Framework – Stieve Zero-Point Topological Mathematica), a harmonic–topological computational layer designed to enhance quantum hardware performance. UHF-SZTM integrates with existing quantum stacks to provide monotonic, noise-resistant harmonic operators and topological constraints that reduce entropy, compress circuit depth, and improve stability. Acting as a pre-quantum stabilizer, it shapes workloads into mathematically coherent forms, enabling accelerated convergence, better error resilience, and predictable scaling across NISQ devices. Applications span molecular simulation, quantum error correction, hybrid optimization, and quantum-assisted AI. Authored by Jonathan William Stieve, Omni Point LLC.
The Stieve Zero-Point Topological Mathematica (SZTM) and Unified Harmonic Framework (UHF) introduce a novel computational paradigm that extends beyond conventional distributed machine learning. By propagating harmonic coherence, structured inference pathways, and causal reasoning across computation graphs, SZTM/UHF achieves superior performance in low-data, noisy, and multi-step reasoning environments. SZTM reduces quantum-scale simulation complexity from O(n²) to O(n log n), BORG reasoning graphs stabilize multi-step inference, and UHF maintains global constraint propagation for accurate, interpretable outcomes. This Zenodo submission documents the theoretical foundations, Python source code, and 50 timestamped validation tests, establishing a clear provenance trail for the framework’s development.
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The Unified Harmonic Framework (UHF) and Stieve Zero-Point Topological Mathematica (SZTM) present a novel harmonic-based approach for unifying classical and quantum physics. This framework models all physical phenomena as nested harmonic structures, where classical deterministic behavior and quantum probabilistic behavior emerge naturally from frequency, phase, and topological interactions. UHF–SZTM supports hybrid quantum-classical simulations, enabling predictive computation without requiring full-scale quantum hardware. The framework has been validated across multiple domains, including quantum tunneling, interference, decoherence, wavefunction collapse, relativistic curvature, and gravitational-wave harmonics. This Zenodo entry provides the non-proprietary symbolic mathematics, conceptual operators, and methodology of UHF–SZTM, demonstrating the framework’s capability to model cross-domain physics while preserving proprietary computational elements. The work is suitable for researchers, quantum engineers, and AI practitioners exploring hybrid simulation, harmonic modeling, and enterprise-scale predictive systems.