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Quantum Machine Learning
RuleSet Generation Framework for Application Layer Integration in Quantum Internet
arXiv
Authors: Rei Kawano, Shin Nishio, Hideaki Kawaguchi, Shota Nagayama, Takahiko Satoh
Year
2025
Paper ID
16030
Status
Preprint
Abstract Read
~2 min
Abstract Words
160
Citations
N/A
Abstract
Layered architectures for the Quantum Internet have been proposed, inspired by that of the classical Internet, which has demonstrated high maintainability even in large-scale systems. While lower layers in the Quantum Internet, such as entanglement generation and distribution, have been extensively studied, the application layer - responsible for translating user requests into executable quantum-network operations - remains largely unexplored. A significant challenge is translating application-level requests into the concrete instructions executable at lower layers. In this work, we introduce a RuleSet-based framework that explicitly incorporates the application layer into the layered architecture of the Quantum Internet. Our framework builds on a RuleSet-based protocol, clarifying communication procedures, organizing application request information, and introducing new Rules for application execution by embedding application specifications into RuleSets. To evaluate feasibility, we constructed state machines from the generated RuleSets. This approach enables a transparent integration from the application layer down to the physical layer, thereby lowering barriers to deploying new applications on the Quantum Internet.
Why This Paper Matters
- This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
- It adds a 2025 reference point for readers tracking recent quantum research.
- Layered architectures for the Quantum Internet have been proposed, inspired by that of the classical Internet, which has demonstrated high maintainability even in large-scale...
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