A Lyapunov-based control scheme is presented to drive closed quantum systems into any target eigenstate with as high population as possible by the quantum-behaved particle swarm optimization (pso) algorithm. Based on ...
详细信息
ISBN:
(纸本)9789881563804
A Lyapunov-based control scheme is presented to drive closed quantum systems into any target eigenstate with as high population as possible by the quantum-behaved particle swarm optimization (pso) algorithm. Based on a Lyapunov function with a Hermitian operator to be constructed, a control law with the unknown parameters contained in the Hermitian operator is designed. To achieve high-population state transfer to the target state, we first initialize those unknown parameters by choosing a path to the target state in its energy-level connectivity graph and setting their values along the path. Then, a set of optimal parameters is found by the quantum-behaved pso algorithm. Finally, numerical simulation experiments are performed on a five-level quantum system and a four-qubit system to demonstrate the effectiveness of the control scheme in this paper.
On the optimal design of CMOS operational amplifier, it is very difficult to improve the circuit's performance by manual design. So a quantum-behaved particle swarm optimization algorithm (Qpso) based on the swarm...
详细信息
ISBN:
(纸本)9781424422388
On the optimal design of CMOS operational amplifier, it is very difficult to improve the circuit's performance by manual design. So a quantum-behaved particle swarm optimization algorithm (Qpso) based on the swarm intelligent technology is presented to get the global optimal solution. This algorithm is mainly to optimize the position of the particle instead of solve the circuit performance analytic equation. First of all, initialize the position and velocity of particles, then renew iteratively, until to search the global optimum. The example result proves it can improve the circuit's performance of the CMOS operational amplifier, and the quantum-behaved pso algorithm is superior to genetic algorithm and psoalgorithm in precision, velocity of convergence.
A Lyapunov-based control scheme is presented to drive closed quantum systems into any target eigenstate with as high population as possible by the quantum-behaved particle swarm optimization(pso) algorithm. Based on...
详细信息
A Lyapunov-based control scheme is presented to drive closed quantum systems into any target eigenstate with as high population as possible by the quantum-behaved particle swarm optimization(pso) algorithm. Based on a Lyapunov function with a Hermitian operator to be constructed, a control law with the unknown parameters contained in the Hermitian operator is designed. To achieve high-population state transfer to the target state, we first initialize those unknown parameters by choosing a path to the target state in its energy-level connectivity graph and setting their values along the path. Then, a set of optimal parameters is found by the quantum-behaved pso algorithm. Finally, numerical simulation experiments are performed on a five-level quantum system and a four-qubit system to demonstrate the effectiveness of the control scheme in this paper.
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