Open-System Quantum Many-Body Entangled Dynamics of Ultracold Molecules

量子力学是我们目前许多技术的基础，包括计算。然而，关于量子力学的许多问题仍然没有解决或开放，特别是在动力学和开放系统领域。探索量子力学的新体制使我们能够推动下一代计算和其他未来技术的发展。获得这种见解的关键实验背景是超冷分子，我们对量子问题的许多方面都有非常精确的控制。在这种情况下，该项目支持开发大规模开源代码，以推动此类实验向前发展。代码在高性能计算机上运行。在严格的数值技术和高性能并行计算方面对学生的训练是在社会许多领域取得成功的关键，从材料基因组计划到太空计划。这个项目将在一个多样化的研究环境中培养学生。随着更复杂的分子接近量子简并，描述它们的多体模型的数量和复杂性也将大幅增加。此外，寻找诸如量子相和鲁棒动力学现象等涌现现象需要探索巨大的参数空间，并使用许多不同的系统大小进行外推。为了应对这些挑战，研究人员寻求新的方法来设计和调度模拟以及收集和解释数据。要产生长期影响的开源工具必须灵活地适应不同的物理自由度、不同的哈密顿量和不同的动态过程；它们必须能够有效地管理大参数探索；它们必须包含从大型模拟中提取数据的强大工具。这里开发的矩阵积密度算子方法将支持超冷分子物理学的创新研究。

Quantum mechanics underlies much of our present technology, including computing. However, many questions about quantum mechanics remain unsolved or open, especially in the areas of dynamics and open systems. Exploring new regimes of quantum mechanics allows us to push towards next generation computing and other future technologies. A key experimental context to gain this insight is ultracold molecules, where we have an extraordinary degree of precise control over many aspects of the quantum problem. In this context, this project supports the development of a large scale open source code to push such experiments forward. The code is run on high performance computers. The training of students in rigorous numerical techniques and high-performance parallel computing is key to success in a number of arenas in society, from the materials genome initiative to the space program. This project will train students in a diverse research environment.As more complex molecules approach quantum degeneracy, the number and complexity of many-body models to describe them will also increase substantially. Additionally, searching for emergent phenomena such as quantum phases and robust dynamical phenomena requires exploration of vast parameter spaces and extrapolation using many different system sizes. In order to meet these challenges, researchers seek new ways to design and dispatch simulations and collect and interpret data. Open source tools which are to have long-term impact must be flexible to adapt to different physical degrees of freedom, different Hamiltonians, and different dynamical processes; they must be efficient to manage large parameter exploration; and they must contain powerful tools for extracting data from large simulations. The matrix product density operator approach to be developed here will support innovative research in ultracold molecular physics.