CDI-Type II Beyond Kohn-Sham Density Functional Theory In Time-Dependent Dynamics

Kohn-Sham密度泛函理论（DFT）提供了一个关于凝聚态物质性质的通用理论。w·科恩（W. Kohn）因这一理论获得了1998年的诺贝尔奖，它彻底改变了实际计算。然而，这个理论是基于一个平均的、非相互作用的描述，最终在长时间尺度上是失败的。因此，现代理论物理学面临的挑战之一是发展超越这种平均图景的方法。一个实际的解决方案将是变革性的。我们的多学科项目通过利用实时方法解决了这一挑战。具体来说，我们将结合使用实时DFT和附加自由度的显式处理，如集体坐标和原子位置，这适用于材料科学和核物理学中的问题。这种动态方法自然地混合了配置，并为处理各种应用程序中的长期行为提供了一个通用框架。尽管上述扩展目前对计算的要求很高，但随着计算机能力的预期提高，以及CDI所带来的理论和算法的进步，它们很可能是可行的。一个成功的方法论的广泛影响具有相当大的理论和实践重要性。例如，超越Kohn-Sham DFT可能会带来新的发现，从核结构和反应到包括电子、光子学和催化在内的技术。此外，对计算技术的关注将把先进的计算机科学方法、计算机代码和高性能计算方法引入理论物理和材料科学，并将有助于培养新一代科学家。

Kohn-Sham density functional theory (DFT) provides a universal theory of the properties of condensed matter. This theory, for which W. Kohn received the 1998 Nobel Prize, has revolutionized practical calculations. Nevertheless, the theory is based on an average, non-interacting description, and ultimately fails at long time scales. Thus one of the challenges of modern theoretical physics is to develop methods that go beyond this average picture. A practical solution would be transformative. Our multi-disciplinary project addresses this challenge by exploiting real-time approaches. Specifically we will use a combination of real-time DFT and explicit treatments of additional degrees of freedom such as collective coordinates and atomic positions, which are appropriate for problems in materials science and nuclear physics. Such dynamic approaches naturally mix configurations, and provide a common framework for treating long-time behavior in various applications. Though the above extensions are currently computationally demanding, they are likely feasible with expected increases in computer power, together with theoretical and algorithmic advances made possible by the CDI. The broader impacts of a successful methodology are of considerable theoretical and practical importance. For example, going beyond Kohn-Sham DFT could likely enable new discoveries ranging from nuclear structure and reactions to technology including electronics, photonics, and catalysis. In addition, the focus on computational techniques will bring advanced computer science methods, computer codes, and high performance computational methods into theoretical physics and materials science, and will help train a new generation of scientists.