Quantum Magnetism in Low-Dimensional Materials

该理论研究将研究材料的磁性，并为拉曼散射、中子散射和核磁共振（NMR）等实验表征工具提供基于模型的计算支持。 大部分的研究依赖于两种类型的计算方法适用于多体模型哈密顿量。第一种是级数展开法，这是基于发展高阶微扰理论或幂级数展开的热力学性质在一个合适的变量，如反温度或耦合常数的比例。当这些展开参数很小时，级数收敛，直接求和提供了所需的答案。 Pade近似和相关的外推方法被用来获得热力学量时，膨胀参数变得很大。 已知这些方法工作良好，只要开发足够长的系列并且不跨越任何相边界。 与相变相关的奇异性可以通过特殊的外推方法得到。第二种方法是基于随机级数展开技术的量子Monte Carlo模拟。 这是一种随机方法，用于对配分函数的高温展开式中的所有项进行求和。 使用最近开发的“运营商循环”的更新，这种方法允许研究相当大的有限尺寸的系统到低温。这些理论计算将用于研究新的和现有的磁性材料的性能。 这些包括铜酸盐家族的高温超导材料和其他几种有机和无机材料。 我们确定了一些最近合成的正方形平面反铁磁材料和空间各向异性材料表现出不寻常的行为，其属性将得到解决。 为了对真实的材料的理解产生更大的影响，我们计划继续与电子结构理论家和实验小组合作。本研究的第二个目标是开发、建立或确认强相互作用多粒子系统中的新想法和概念。 例如，波动主导的一维物理是否可以延续到更高维的系统的问题将得到解决。 另一个感兴趣的问题是是否存在二维自旋模型，奇异相位和可能的分数自旋激发。 第三个目标是进一步发展和扩展计算方法本身，使它们能够用于更广泛的模型和更大的实验性质。 我们将集中在有限温度下的磁系统的动力学性质，这将是最重要的定量理解中子散射和核磁共振结果。这些计算研究为学生和博士后提供了极好的培训。%该理论研究将研究材料的磁性，并为拉曼散射、中子散射和核磁共振（NMR）等实验表征工具提供基于模型的计算支持。 大部分的研究依赖于两种类型的计算方法应用于多体模型哈密顿。 这些是级数展开技术和量子蒙特卡罗方法。 这些研究为学生提供了很好的培训。*

This theoretical research will study magnetic properties of materials and provide model-based computational support for experimental characterization tools such as Raman scattering, neutron scattering and nuclear magnetic resonance (NMR). The bulk of the study relies on two types of computational methods applied to many-body model Hamiltonians.The first is the series expansion method, which is based on developing high order perturbation theory or power-series expansions for thermodynamic properties in a suitable variable such as inverse temperature or ratio of coupling constants. When these expansion parameters are small and the series are convergent, a direct summation provides the desired answer. Pade approximants and related extrapolation methods are used to obtain thermodynamic quantities when the expansion parameters become large. These methods are known to work well provided one develops a long enough series and does not cross any phase boundaries. The singular properties associated with the phase transitions can be obtained as a limiting behavior from specially developed extrapolation schemes.The second method is quantum Monte Carlo simulations based on the stochastic series expansion technique. This is a stochastic method to sum up all the terms in a high temperature expansion of the partition function. Using recently developed "operator loop" updates, this method allows one to study fairly large finite-size systems down to low temperatures. These theoretical calculations will be used to study properties of novel and existing magnetic materials. These include the cuprate family of high temperature superconducting materials and several other organic and inorganic materials. We identify a number of recently synthesized square-planar antiferromagnetic materials and spatially anisotropic materials exhibiting unusual behavior, whose properties will be addressed. In order to have a greater impact on the understanding of real materials, we plan to continue our collaborations with electronic structure theorists and experimental groups.A second objective of this research is to develop, establish or confirm new ideas and concepts in strongly interacting many-particle systems. For example, the question of whether fluctuation dominated one-dimensional physics can carry over to higher dimensional systems will be addressed. Another question of interest is whether there exist two-dimensional spin models, with exotic phases and possibly fractional spin excitations. Specific models, whose properties will be calculated, are discussed.A third objective is to further develop and extend the computational methods themselves so that they can be used for a wider class of models and for a larger class of experimental properties. We will focus on dynamical properties of magnetic systems at finite temperatures, which would be most important in quantitatively understanding neutron scattering and NMR results. These computational studies provide excellent training for students and postdoctoral associates.%%%This theoretical research will study magnetic properties of materials and provide model-based computational support for experimental characterization tools such as Raman scattering, neutron scattering and nuclear magnetic resonance (NMR). The bulk of the study relies on two types of computational methods applied to many-body model Hamiltonians. These are series-expansion techniques and quantum Monte Carlo methods. These studies provide excellent training for students.***