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作为一种物质表征的重要技术手段, 固态核磁共振已经在物理学、材料科学、化学、生物学等多个学科领域得到广泛的应用. 近年来, 得益于固态核磁共振体系中丰富的多体相互作用和多样的脉冲控制手段, 该技术逐渐在前沿的量子科技中展现出重要的研究价值和应用潜力. 本文系统性地介绍了固态核磁共振体系的研究对象和理论基础, 包括该系统中重要的核自旋相互作用机理及其哈密顿量形式, 列举了动力学解耦、魔角旋转等典型的固态核自旋动力学调控手段. 此外, 我们重点展示了近年来在固态核磁共振量子控制方面取得的前沿进展, 包括核自旋极化增强技术、弗洛凯哈密顿量的调控技术等. 最后, 我们结合一些重要的研究工作阐述了固态核磁共振量子控制技术在量子模拟领域中的应用.Solid-state nuclear magnetic resonance (NMR) has emerged as an important technique for material characterization, finding extensive applications across a diverse range of disciplines including physics, materials science, chemistry, and biology. Its utility stems from the ability to probe the local atomic environments and molecular dynamics within solid materials, which provides information on the composition of the material. In recent years, the scope of solid-state NMR has expanded into the realm of quantum information science and technology, where its abundant many-body interactions pulse control methodologies make it have significant research value and application potential. This paper offers a comprehensive overview of the research objects and theoretical underpinnings of solid-state NMR, delving into the critical nuclear spin interaction mechanisms and their corresponding Hamiltonian forms. These interactions, which include dipolar coupling, chemical shift anisotropy, and quadrupolar interactions, are fundamental to the interpretation of NMR spectra and the understanding of material properties at the atomic level. Moreover, the paper introduces typical dynamical control methods employed in the manipulation of solid-state nuclear spins. Techniques such as dynamical decoupling, which mitigates the effects of spin-spin interactions to extend coherence times, and magic-angle spinning, which averages out anisotropic interactions to yield high-resolution spectra. These methods are essential for enhancing the sensitivity and resolution of NMR experiments, enabling the extraction of detailed structural and dynamic information from complex materials. Then we introduce some recent advancements in quantum control based on solid-state NMR, such as nuclear spin polarization enhancement techniques, which include dynamic nuclear polarization (DNP) and cross polarization (CP), significantly boost the sensitivity of NMR measurements. Additionally, the control techniques of Floquet average Hamiltonians are mentioned, showcasing their role in the precise manipulation of quantum states and the realization of quantum dynamics. Finally, the paper presents a series of seminal research works that illustrate the application of solid-state NMR quantum control technologies in the field of quantum simulation. These studies demonstrate how solid-state NMR can be leveraged to simulate and investigate quantum many-body systems, providing valuable insights into quantum phase transitions, entanglement dynamics, and other phenomena relevant to quantum information science. By bridging the gap between fundamental research and practical applications, solid-state NMR continues to play a crucial role in advancing our understanding of quantum materials and technologies.
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Keywords:
- solid-state nuclear magnetic resonance /
- quantum control /
- nuclear spin interactions /
- quantum simulation
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$ \hat{H}_{\rm tar} $ C 单位(π), $ n=1, 2, 3, 4 $ $ \displaystyle\sum_{i<j}J_{ij}[2\hat{I}^i_z\hat{I}^j_z-\hat{I}^i_x\hat{I}^j_x-\hat{I}^i_y\hat{I}^j_y] $ 1 $ \beta_{n}=1, \gamma_n= {(n-1)}/{2} $ –0.5 $ \beta_{n} = {1}/{2}, \gamma_n = {(n-1)}/{2} $ $ \displaystyle\sum_{i<j}J_{ij}[\hat{I}^i_x\hat{I}^j_x-\hat{I}^i_y\hat{I}^j_y] $ 1 $ \beta_{n}=0.304, \gamma_n= [{1+4(-1)^n}]/{4} $ –1 $ \beta_{n}=0.304, \gamma_n= [{3+4(-1)^n}]/{4} $ $ \displaystyle\sum_{i<j}J_{ij}[\hat{I}^i_z\hat{I}^j_x+\hat{I}^i_x\hat{I}^j_z] $ 1/3 $ \beta_{n}=0.304, \gamma_n= [{3(-1)^n}]/{4} $ –1/3 $ \beta_{n}=0.304, \gamma_n= {(-1)^n}/{4} $ $ \displaystyle\sum_{i<j}J_{ij}[\hat{I}^i_z\hat{I}^j_y+\hat{I}^i_y\hat{I}^j_z] $ 1/3 $ \beta_{n}=0.304, \gamma_n = [{2+(-1)^n}]/{4} $ –1/3 $ \beta_{n}=0.304, \gamma_n= [{2+(-1)^n}]/({-4}) $ $ \displaystyle\sum_{i<j}J_{ij}[\hat{I}^i_y\hat{I}^j_x+\hat{I}^i_x\hat{I}^j_y] $ 1 $ \beta_{n}=0.304, \gamma_n= [{1+(-1)^n}]/{2} $ –1 $ \beta_{n}=0.304, \gamma_n = [{2+(-1)^n}]/{2} $ 
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