Abstract:Superconducting circuits extensively rely on the Josephson junction as a nonlinear electronic element for manipulating quantum information and mediating photon interactions. Despite continuing efforts in designing anharmonic Josephson circuits with improved coherence times, the best photon lifetimes have been demonstrated in microwave cavities. Nevertheless, architectures based on quantum memories need a qubit element for addressing these harmonic modules at the cost of introducing additional loss channels and… Show more
“…It should be noted that our method is sufficient for the evolution of quantum state in spin 1/2 system. Other difficult quantum control problems include quantum error correction based on bosonic codes (Michael et al 2016) and quantum state preparation in the singlephoton manifold (Vrajitoarea et al 2020). And it is a valuable work to conduct a study on providing solu-tions by using learning theories (Li et al 2018;Zhang and Wang 2020) and neural network (Xu et al 2019;Hu et al 2020), which is also one of our next research.…”
The design of quantum system control is a key task to a powerful quantum information technology. In practical, traditional quantum system control methods often face different constraints, and are easy to cause both leakage and stochastic control errors under the condition of limited resources. Reinforcement learning has been proved as an efficient way to complete the quantum system control task. So a quantum system control method based on enhanced reinforcement learning (QSC-ERL) is proposed. A satisfactory control strategy is obtained through enhanced reinforcement learning so that the quantum system can be evolved accurately from the initial state to the target state. According to the number of candidate unitary operations, the three-switch control is used for simulation experiments. Compared with other methods, the QSC-ERL can achieve high fidelity learning control of quantum systems and improve the efficiency of quantum system control.
“…It should be noted that our method is sufficient for the evolution of quantum state in spin 1/2 system. Other difficult quantum control problems include quantum error correction based on bosonic codes (Michael et al 2016) and quantum state preparation in the singlephoton manifold (Vrajitoarea et al 2020). And it is a valuable work to conduct a study on providing solu-tions by using learning theories (Li et al 2018;Zhang and Wang 2020) and neural network (Xu et al 2019;Hu et al 2020), which is also one of our next research.…”
The design of quantum system control is a key task to a powerful quantum information technology. In practical, traditional quantum system control methods often face different constraints, and are easy to cause both leakage and stochastic control errors under the condition of limited resources. Reinforcement learning has been proved as an efficient way to complete the quantum system control task. So a quantum system control method based on enhanced reinforcement learning (QSC-ERL) is proposed. A satisfactory control strategy is obtained through enhanced reinforcement learning so that the quantum system can be evolved accurately from the initial state to the target state. According to the number of candidate unitary operations, the three-switch control is used for simulation experiments. Compared with other methods, the QSC-ERL can achieve high fidelity learning control of quantum systems and improve the efficiency of quantum system control.
“…Nonlinearity and nonlinear interactions are weak and difficult to be detected in some systems, but they can also become sufficiently strong to be the dominant factor in some other systems. The cross-Kerr effect is one of the subtle nonlinear interactions between fields and waves that can exist in natural ions [13], atoms [14][15][16], and artificial mesoscopic architectures, such as superconducting circuits [17][18][19]. The cross-Kerr effect is a nonlinear shift in the frequency of a resonator as a function of the number of excitations in another mode that interacts with the resonator.…”
When there is a certain amount of field inhomogeneity, the biased ferrimagnetic crystal will exhibit the higher-order magnetostatic (HMS) mode in addition to the uniform-precession Kittel mode. In cavity magnonics, we show both experimentally and theoretically the cross-Kerr-type interaction between the Kittel mode and HMS mode. When the Kittel mode is driven to generate a certain number of excitations, the HMS mode displays a corresponding frequency shift, and vice versa. The cross-Kerr effect is caused by an exchange interaction between these two spin-wave modes. Utilizing the cross-Kerr effect, we realize and integrate a multi-mode cavity magnonic system with only one yttrium iron garnet (YIG) sphere. Our results will bring new methods to magnetization dynamics studies and pave a way for novel cavity magnonic devices by including the magnetostatic mode-mode interaction as an operational degree of freedom.
“…However, the achievement of both high Q 0 and high E acc in the same cavity has remained elusive. Beyond SRF accelerator technology, high Q 0 SRF quality Nb is beginning to find application in quantum computing devices 3 , 4 , with the possibility that high Q at very low microwave power at a single photon level may provide a viable approach to increase qubit lifetime 5 , 6 . Hence, understanding the factors that determine Q 0 in SRF Nb is of great interest.…”
Elemental type-II superconducting niobium is the material of choice for superconducting radiofrequency cavities used in modern particle accelerators, light sources, detectors, sensors, and quantum computing architecture. An essential challenge to increasing energy efficiency in rf applications is the power dissipation due to residual magnetic field that is trapped during the cool down process due to incomplete magnetic field expulsion. New SRF cavity processing recipes that use surface doping techniques have significantly increased their cryogenic efficiency. However, the performance of SRF Nb accelerators still shows vulnerability to a trapped magnetic field. In this manuscript, we report the observation of a direct link between flux trapping and incomplete flux expulsion with spatial variations in microstructure within the niobium. Fine-grain recrystallized microstructure with an average grain size of 10â50 ”m leads to flux trapping even with a lack of dislocation structures in grain interiors. Larger grain sizes beyond 100â400 ”m do not lead to preferential flux trapping, as observed directly by magneto-optical imaging. While local magnetic flux variations imaged by magneto-optics provide clarity on a microstructure level, bulk variations are also indicated by variations in pinning force curves with sequential heat treatment studies. The key results indicate that complete control of the niobium microstructure will help produce higher performance superconducting resonators with reduced rf losses1 related to the magnetic flux trapping.
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