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。 探索量子力学的新机制使我们能够推动下一代计算和其他未来技术。 获得这种洞察力的一个关键实验背景是超冷分子，在那里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的开源代码，以推动此类实验的发展。 代码在高性能计算机上运行。 严格的数值技术和高性能并行计算的学生的培训是在社会上的一些领域取得成功的关键，从材料基因组计划到太空计划。本项目将在多样化的研究环境中培养学生。随着越来越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，寻找涌现现象，如量子相位和鲁棒动力学现象，需要探索巨大的参数空间和外推使用许多不同的系统尺寸。 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。 开源工具要具有长期的影响力，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力学过程;它们必须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。 矩阵产品密度算子的方法将在这里开发支持创新的研究在超冷分子物理。

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.