Quantum Computing Device for Detecting Interconnected Network Nodes
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Solution Overview
Problem
Existing methods for detecting groups of interconnected nodes in complex networks, such as 5G telecommunications networks, face scalability issues due to high time and space complexity, making it difficult to analyze and optimally configure large and complex networks effectively.
Innovation Solution
A quantum computing device is used to detect groups of interconnected nodes by determining initial groups of adjacent nodes based on maximizing modularity, with a hybrid system of quantum and classical computing iterating through combinations until no further improvement in modularity is achieved, employing a quantum circuit and oracles to efficiently find initial groups and merge them based on modularity increases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If classical algorithms (fast unfolding algorithm or quantum walk) are used to detect communities in large networks, then community detection accuracy is improved, but time complexity and space complexity increase significantly making the method intractable for large networks
Solution Approach 1:
The patent replaces classical computational mechanics with quantum computational mechanics. Quantum algorithms leverage quantum parallelism and interference to evaluate multiple community configurations simultaneously, achieving exponential speedup in finding optimal community partitions while maintaining detection accuracy. The quantum system evolves according to quantum mechanical principles rather than classical iterative optimization.
Solution Approach 2:
The patent changes the fundamental parameters of the computational system from classical bits to quantum bits (qubits), enabling the system to represent and process community configurations in a high-dimensional Hilbert space. This parameter change allows the system to explore the solution space more efficiently by utilizing quantum superposition and entanglement, reducing both time and space complexity for large network analysis.
2Measurement precision
If classical algorithms (fast unfolding algorithm or quantum walk) are used to detect communities in large networks, then community detection accuracy is improved, but space complexity increases making the method intractable for large networks
Solution Approach 1:
The patent replaces classical memory and storage requirements with quantum memory resources. Quantum algorithms can store and manipulate community configuration information in quantum registers with exponentially smaller physical footprint compared to classical systems, due to the dense coding capability and quantum parallelism inherent in quantum mechanical systems.
Solution Approach 2:
The patent transitions from classical three-dimensional space (physical memory storage) to quantum state space (Hilbert space) for representing community configurations. By encoding community information in quantum superposition states, the system achieves efficient storage and manipulation of large network data with reduced physical space requirements, leveraging the high-dimensional nature of quantum state space.
Data Source
AI summary
Embodiments described herein relate to a quantum computing device, methods and apparatus for determining a group of interconnected nodes in a network parameter. In an embodiment, a method includes using a quantum computing device to determine initial groups of adjacent nodes based on maximising modularity, and detecting a group of interconnected nodes by grouping the initial groups of adjacent nodes based on maximising modularity.