Abstract

The condition of a quantum Lyapunov-based control which can be well used in a closed quantum system is that the method can make the system convergent but not just stable. In the convergence study of the quantum Lyapunov control, two situations are classified: nondegenerate cases and degenerate cases. For these two situations, respectively, in this paper the target state is divided into four categories: the eigenstate, the mixed state which commutes with the internal Hamiltonian, the superposition state, and the mixed state which does not commute with the internal Hamiltonian. For these four categories, the quantum Lyapunov control methods for the closed quantum systems are summarized and analyzed. Particularly, the convergence of the control system to the different target states is reviewed, and how to make the convergence conditions be satisfied is summarized and analyzed a Survey of Quantum Lyapunov Control maximum common substructure-based support vector machine algorithm for the Fragment based drug discovery of drug like optimized Alpha-Helical Cationic Anticancer Peptide-mimetic annotated Pharmacophore.

Keywords

Survey;Quantum Lyapunov Control; Methods; maximum common; substructure-based; support vector; machine algorithm; Fragment based drug discovery; drug like; optimized Alpha-Helical; Cationic Anticancer; Peptide-mimetic; annotated Pharmacophore;