Related Experiment Video
Updated: Feb 13, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
Published on: September 8, 2023
A parallel adaptive quantum genetic algorithm for the controllability of arbitrary networks
Yuhong Li1, Guanghong Gong1, Ni Li1,2
1School of Automation Science and Electrical Engineering, Beihang University, Beijing, China.
Abstract:
In this paper, we propose a novel algorithm-parallel adaptive quantum genetic algorithm-which can rapidly determine the minimum control nodes of arbitrary networks with both control nodes and state nodes. The corresponding network can be fully controlled with the obtained control scheme. We transformed the network controllability issue into a combinational optimization problem based on the Popov-Belevitch-Hautus rank condition. A set of canonical networks and a list of real-world networks were experimented. Comparison results demonstrated that the algorithm was more ideal to optimize the controllability of networks, especially those larger-size networks. We demonstrated subsequently that there were links between the optimal control nodes and some network statistical characteristics. The proposed algorithm provides an effective approach to improve the controllability optimization of large networks or even extra-large networks with hundreds of thousands nodes.
Related Concept Videos
Quantum Numbers
The Quantum-Mechanical Model of an Atom
Protein Networks
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
Moment of Inertia about an Arbitrary Axis
In this scenario, the perpendicular distance between the chosen arbitrary axis...
Angular Momentum about an Arbitrary Axis
The velocity of a mass element comprises its translational velocity and the relative velocity instigated by the body's rotation. Substituting the velocity equation into...
Parallel Processing

