
TL;DR
The paper introduces a novel global optimization algorithm inspired by social group leader influence, demonstrating improved scalability and application to quantum circuit design problems.
Contribution
It presents a new social-inspired optimization method with enhanced scalability and practical applications in quantum computing.
Findings
Scales as N^2.5 for Lennard-Jones clusters
Effective in quantum circuit design, including Grover search
Outperforms previous optimization methods
Abstract
We present a new global optimization algorithm in which the influence of the leaders in social groups is used as an inspiration for the evolutionary technique which is designed into a group architecture. To demonstrate the efficiency of the method, a standard suite of single and multidimensional optimization functions along with the energies and the geometric structures of Lennard-Jones clusters are given as well as the application of the algorithm on quantum circuit design problems. We show that as an improvement over previous methods, the algorithm scales as N^2.5 for the Lennard-Jones clusters of N-particles. In addition, an efficient circuit design is shown for two qubit Grover search algorithm which is a quantum algorithm providing quadratic speed-up over the classical counterpart.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
