Accurate and efficient preparation of quantum state is a core issue in building a quantum computer. In this paper, we investigate how to prepare a certain single- or two-qubit target state from arbitrary initial states in semiconductor double quantum dots with only a few discrete control pulses by leveraging the deep reinforcement learning. Our method is based on the training of the network over numerous preparing tasks. The results show that once the network is well trained, it works for any initial states in the continuous Hilbert space. Thus repeated training for new preparation tasks is avoided. Our scheme outperforms the traditional optimization approaches based on gradient with both the higher efficiency and the preparation quality in discrete control space. Moreover, we find that the control trajectories designed by our scheme are robust against stochastic fluctuations within certain thresholds, such as the charge and nuclear noises.

We investigate the feasibility of using an effective pulse control method to realize an almost exact state transmission through a uniform chain where the communication channel is immersed in a quantum environment. This pulse control is treated in a nonperturbative fashion, allowing for a more precise view. Using the non-Markovian quantum state diffusion equation, we calculate the dynamics of the transmission fidelity. The results show that the memory effects of the environment can support an effective transmission control that can be boosted under a non-Markovian environment. Our scheme provides another way to realize almost exact state transmission in a spin chain system.

Adiabatic quantum computation requires keeping a system in a particular eigenstate. However, unwanted transitions can occur due to the interaction of the system with a noisy environment. The adiabatic evolution of the system will then be ruined. To reduce the effect of the environment, quantum control methods can be used. This allows one to speed up the adiabatic process. Here we present an effective control scheme to allow for a speedup of the adiabatic process by using a sequence of pulses on the system. Using the hierarchical functional derivative (HFD) approach, we calculate the fidelity evolution, which is a measure of the adiabaticity in an open system. By carefully choosing the pulse intensity and duration, an accelerated adiabatic path can be obtained for both a weak-coupling and a strong non-Markovian environment.

Transmission of a quantum state is essential for performing quantum information processing tasks. The communication channel will be inevitably immersed in its surrounding environment under realistic conditions. In this paper, we investigate the influence of environment noise on the transmission fidelity when transferring a quantum state through a spin chain. The non-Markovian open system dynamics is systematically analyzed by using the quantum state diffusion equation method. With each spin immersed in its own finite temperature and non-Markovian heat bath, we consider three types of system–bath interaction: dephasing, dissipation and spin-boson. The transmission fidelity is found to decrease with the increasing bath temperature and system–bath coupling strength. Interestingly, we find that the bath non-Markovianity can help enhancing the transmission fidelity.

Adiabatic quantum computation requires that the system remains in its ground state. However, an adiabatic process often loses partly or entirely its quantumness, such as entanglement in its long runtime, due to the system-environment interactions. Here we put forward an effective quantum control technique to realize the adiabatic quantum search algorithm in a nonadiabatic regime and in the presence of environment. Using the non-Markovian quantum state diffusion equation approach, we numerically study the system dynamics characterized by the success probability. The results show that the probability increases with decreasing coupling strength and temperature. In particular, non-Markovianity from the environment can help to enhance the success probability. By choosing a suitable pulse intensity and period, a high success probability can be obtained in a short runtime for weak system-bath coupling, low temperature, and strong non-Markovian heat baths.