Dust Theory Vol. 8: Gradient Quantum Computing: A Native Quantum Paradigm and Hardware Architecture Based on Gradient-Relational Ontology (Gradient Cosmos Research Series)

All existing quantum computing paradigms take substantial qubits as basic units and realize state evolution through quantum gate operations. Essentially, they simulate quantum effects within the framework of classical architecture, and persistently face three core bottlenecks: extreme decoherence sensitivity, huge error correction overhead, and extremely high scaling difficulty. The root cause lies in the failure to grasp the relational essence of quantum phenomena at the ontological level. Based on the path-rule duality principle of Gradient-Relational Ontology and the path-state essence of quantum states, this paper proposes gradient quantum computing as a native quantum computing paradigm. The basic unit of computation is not binary qubits, but multi-dimensional parallel conductive gradient paths; the computing process is not the sequential operation of quantum gates, but the self-organized evolution of path superposition, interference and condensation; measurement is not a special operation triggering collapse, but the spontaneous condensation of paths into rule states. The study demonstrates that this paradigm possesses endogenous decoherence suppression and native error correction capabilities. It can maintain computational stability through structural steady states without external quantum error correction codes. Its parallelism grows exponentially with path scale, and the scaling bottleneck is far lower than that of traditional qubit architectures. This paper further presents a four-layer hardware system architecture for gradient quantum computers, clarifies the core technical path of physical implementation, and proves its natural computational advantages in combinatorial optimization, quantum simulation and other problems. This study extends relational ontology to the field of quantum computing, providing a brand-new ontological path and architectural scheme for breaking through the engineering bottlenecks of existing quantum computing and realizing large-scale general-purpose quantum computing.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-06-27
DOI
https://doi.org/10.5281/zenodo.20965011
Primary Topic
Quantum Computing Algorithms and Architecture
Type
preprint
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Dust Theory Vol. 8: Gradient Quantum Computing: A Native Quantum Paradigm and Hardware Architecture Based on Gradient-Relational Ontology (Gradient Cosmos Research Series)

Y Cao
Zenodo (CERN European Organization for Nuclear Research)
Quantum Computing Algorithms and Architecture
preprint

Dust Theory Vol. 8: Gradient Quantum Computing: A Native Quantum Paradigm and Hardware Architecture Based on Gradient-Relational Ontology (Gradient Cosmos Research Series)

Y Cao
preprint en

Abstract

All existing quantum computing paradigms take substantial qubits as basic units and realize state evolution through quantum gate operations. Essentially, they simulate quantum effects within the framework of classical architecture, and persistently face three core bottlenecks: extreme decoherence sensitivity, huge error correction overhead, and extremely high scaling difficulty. The root cause lies in the failure to grasp the relational essence of quantum phenomena at the ontological level. Based on the path-rule duality principle of Gradient-Relational Ontology and the path-state essence of quantum states, this paper proposes gradient quantum computing as a native quantum computing paradigm. The basic unit of computation is not binary qubits, but multi-dimensional parallel conductive gradient paths; the computing process is not the sequential operation of quantum gates, but the self-organized evolution of path superposition, interference and condensation; measurement is not a special operation triggering collapse, but the spontaneous condensation of paths into rule states. The study demonstrates that this paradigm possesses endogenous decoherence suppression and native error correction capabilities. It can maintain computational stability through structural steady states without external quantum error correction codes. Its parallelism grows exponentially with path scale, and the scaling bottleneck is far lower than that of traditional qubit architectures. This paper further presents a four-layer hardware system architecture for gradient quantum computers, clarifies the core technical path of physical implementation, and proves its natural computational advantages in combinatorial optimization, quantum simulation and other problems. This study extends relational ontology to the field of quantum computing, providing a brand-new ontological path and architectural scheme for breaking through the engineering bottlenecks of existing quantum computing and realizing large-scale general-purpose quantum computing.

Zenodo (CERN European Organization for Nuclear Research)
Quantum Computing Algorithms and Architecture
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Dust Theory Vol. 8: Gradient Quantum Computing: A Native Quantum Paradigm and Hardware Architecture Based on Gradient-Relational Ontology (Gradient Cosmos Research Series) — Y Cao · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS