To better understand the states and evolution of quantum systems, HOLO employed a quantum trajectory simulation method. Quantum trajectories are a powerful tool for describing the evolution of quantum systems, helping researchers gain deeper insights into the behavior of quantum systems under various conditions. By simulating random measurement records, a large amount of data can be obtained, providing a solid foundation for analyzing the characteristics of quantum systems. At the same time, the conditional evolution of quantum system states is clearly presented through quantum trajectories, enabling researchers to accurately grasp the changing patterns of quantum systems in different environments.
Specifically, the quantum trajectory simulation process used by HOLO is as follows: First, the initial state of the quantum system and the parameters of the detection field are determined. Then, based on the principles of quantum mechanics, the interaction process between the quantum system and the detection field is calculated. In this process, various possible quantum states and interaction methods are considered to ensure the accuracy of the simulation. Next, a large amount of quantum system state data is obtained through random measurement records. After processing and analyzing this data, the characteristics and evolution patterns of the quantum system can be determined. Finally, based on the analysis results, further research and optimization of the quantum system are conducted.
HOLO’s analytical method has broad applicability. It is suitable for different measurement strategies and arbitrary input quantum states of the detection field pulses. This means that regardless of the measurement method used or the quantum state of the detection field, HOLO’s method can be applied for analysis. This versatility provides great convenience for quantum system research, allowing different research teams to choose appropriate measurement strategies and detection field states based on their specific needs.
In terms of metrological advantages, HOLO has verified the superiority of its method in measurement accuracy by deterministically calculating the theoretical lower bound of the average discrimination error. Specifically, the average discrimination error is an important metric for assessing the measurement precision of quantum systems. Through precise theoretical calculations, HOLO determined the theoretical lower bound of the average discrimination error and compared it with the average inference error. The results show that, in all cases, the theoretical lower bound of the average discrimination error is lower than the average inference error. This indicates that HOLO’s method has a clear advantage in measurement accuracy, providing more precise data and more reliable results for quantum system research.
In this quantum system study, HOLO achieved in-depth exploration and accurate measurement of quantum systems through the perfect integration of the detection field and quantum trajectories. Its innovative research methods and advanced technical approaches have laid a solid foundation for the development and application of quantum systems. It is believed that in the future, HOLO will continue to play an important role in the quantum field, making even greater contributions to the advancement of science and technology.
About MicroCloud Hologram Inc.
MicroCloud is committed to providing leading holographic technology services to its customers worldwide. MicroCloud’s holographic technology services include high-precision holographic light detection and ranging (“LiDAR”) solutions, based on holographic technology, exclusive holographic LiDAR point cloud algorithms architecture design, breakthrough technical holographic imaging solutions, holographic LiDAR sensor chip design and holographic vehicle intelligent vision technology to service customers that provide reliable holographic advanced driver assistance systems (“ADAS”). MicroCloud also provides holographic digital twin technology services for customers and has built a proprietary holographic digital twin technology resource library. MicroCloud’s holographic digital twin technology resource library captures shapes and objects in 3D holographic form by utilizing a combination of MicroCloud’s holographic digital twin software, digital content, spatial data-driven data science, holographic digital cloud algorithm, and holographic 3D capture technology. For more information, please visit http://ir.mcholo.com/
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