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Quantum System中的自适应概率模型调整

Jincheng Zhang

Published Sep 6, 2026• 0 citations
Publisher

Abstract

Quantum system中的自适应概率模型调整旨在提高量子系统的可靠性。本研究提出了一种基于机器学习的自适应概率模型调整方法,通过对量子系统状态的动态分析,自动调整概率模型参数,从而实现自适应校正。我们的研究结果表明,该方法可以有效提高量子系统的量子精度和稳定性,并为量子计算领域提供了一种新的模型校正策略。

DOI
10.5281/zenodo.22467786

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Quantum拓扑,一种量子力学概念,描述了空间中的几何结构,具有非平凡性,并且在某些条件下可以表现出自适应性。本研究探讨了利用量子拓扑作为自适应几何变换的潜在应用,旨在解决复杂形状分析和表示方面的挑战。我们提出了一种基于量子拓扑的动态几何变换技术,该技术通过量子拓扑的自适应特性,能够实现对复杂形状的动态调整和改进,从而提供更强大的形状分析和表示能力。
Quantum measurement is a class of quantum channels that sends quantum states to classical states. We set up resource theories of quantum coherence and quantum entanglement for quantum measurements and find relations between them. For this, we conceive a relative entropy-type quantity to account for the quantum resources of quantum measurements. The quantum coherence of a quantum measurement can be converted into the entanglement in a bipartite quantum measurement through coherence nongenerating transformations. Conversely, a quantum entanglement monotone of quantum measurements induces a quantum coherence monotone of quantum measurements. Our results confirm that the understanding on the link between quantum coherence and quantum entanglement is valid even for quantum measurements which do not generate any quantum resource.
It’s obvious to ask what to do if we are given a quantum computer. Here, we present a number of quantum tasks which have been performed on a quantum computer. Some practical applications like quantum cheque, quantum locker and quantum OTP have been experimentally realized using IBM’s 5 qubit quantum computer. The above applications can together act as a quantum banking system. Simulating quantum physics is another area of great interest. Quantum tunneling has been simulated on the quantum computer to show it’s quantum nature and potential applications. Quantum devices such as quantum repeater, and quantum router play key roles in a quantum network for long distance communication. These devices have been designed using IBM’s quantum computer. Recent trends like quantum machine learning and quantum artificial intelligence have significant applications e.g., classification of big data, recognizing hand written pattern, quantum image processing etc. All the above tasks can be efficiently simulated in a quantum computer, provided we have a basic background of quantum circuits and quantum gates.
Quantum拓扑,一种量子力学中存在的奇特结构,为量子计算提供了独特的优势。本研究提出了一种基于量子拓扑的自适应量子计算量子路径优化方法,旨在利用拓扑结构优化量子路径,从而提高计算效率。该方法借鉴了量子拓扑的特性,通过构建拓扑结构来指导量子路径的优化,从而实现更高效的量子计算。该方法具有自动学习能力,并能够针对不同问题优化量子路径,为量子计算的发展提供新的思路。
This paper proposes a novel work to design reversible quantum circuits. The function of this circuit is to investigate quantum transmission integrity in the quantum communication networks. This work is to verify quantum transmission sequence of a quantum frame by using reversible quantum model. This model designs control module to derive the correlation between two quantum strings: quantum input sequence and quantum output sequence. If a quantum frame reserves the correlation, then we can obtain quantum transmission sequence. So, quantum transmission integrity of a quantum frame can be verified.