Then, the adaptive correction of the energy position is explored to improve algorithm performance. The core idea of our mechanism is to adaptively guide the candidate solutions toward convergence to the ground
In just a few hours, the team was able to run a simulation on a laptop that previously took several days on a supercomputer. The new algorithm saw a 1000-fold reduction in processor demand, and a million-fold reduction in memory demand. While this simulation was just a simple test, the ...
Our unique algorithm evolves particle states to find optimal pathways through the solution space. 3 Interference Patterns Constructive and destructive interference amplifies relevant patterns while suppressing noise. 4 Measurement & Interpretation Final states are measured and interpreted with our specialized a...
Quantum Computing, Bee Colony Optimizing, Bloch Sphere Rotating, Algorithm DesigningTo enhance the performance of the artificial bee colony optimization by integrating the quantum computing model into bee colony optimization, we present a quantum-inspired bee colony optimization algorithm. In our method, ...
Algorithm S3 in Supplementary information explains the details. Full size image In this work, we use the eigenvector centrality criterion that we can represent in the form (e.g.62) λpEp,i=∑j=1NAijEp,j, (28) where λp is the PE; Ep,i (i=1,…,N) is the correspondent eigen...
Quantum-inspired evolutionary algorithm for numerical optimization. In Proceedings of the IEEE congress on evolutionary computation. Vancouver, Canada.da Cruz A. V. A., Vellasco M. M. B. R., Pacheco M. A. C. Quantum-inspired evolutionary algorithm for numerical optimization. Proceedings of the...
The number of clusters has to be known in advance for the conventional k-means clustering algorithm and moreover the clustering result is sensitive to the selection of the initial cluster centroids. This sensitivity may make the algorithm converge to the local optima. This paper proposes a quantu...
In this paper, we present a proof-of-principle sublinear-time algorithm for solving SDPs with low-rank constraints; specifically, given an SDP with m constraint matrices, each of dimension n and rank r, our algorithm can compute any entry and efficient descriptions of the spectral decomposition ...
This paper proposes a new immune clonal algorithm, called a quantum-inspired immune clonal algorithm (QICA), which is based on the concept and principles of quantum computing, such as a quantum bit and superposition of states. Like other evolutionary algorithms, QICA is also characterized by the...
select article Quantum-inspired algorithm for direct multi-class classification Research articleAbstract only Quantum-inspired algorithm for direct multi-class classification Roberto Giuntini, Federico Holik, Daniel K. Park, Hector Freytes, ... Giuseppe Sergioli ...