Topics in Nuclear Structure Theory

了解原子核所表现出的各种特性，以及这些特性是如何随着中子和质子的数量而演变的，是核物理学的关键挑战之一。本提案的中心主题是开发一种新的方法，以获得核景观中可靠的核微观描述。这种方法被称为密度矩阵重整化群，在处理许多其他复杂的多体量子系统方面已被证明是非常成功的，并且似乎也非常适合于应用于原子核。本提案的目标是将密度矩阵重整化群建立为原子核微观描述的实用方法，并在整个元素周期表中系统地应用它。成功地实现这个项目的目标应产生广泛的影响，远远超出核领域。对原子核的详细结构有了可靠的描述，就有可能解决核天体物理学中的基本问题，包括宇宙中的元素是如何合成的，以及与自然的基本对称性有关的问题。正在开发的方法计算量非常大，需要开发新的计算算法，这些算法也应该在各个领域有广泛的应用。最后，建议的科学研究将涉及几名博士生的积极参与，帮助他们在前沿科学研究和前沿计算方法方面进行培训。

Understanding the variety of properties exhibited by atomic nuclei from the underlying forces between their constituent nucleons, and understanding how these features evolve with the number of neutrons and protons, represents one of the key challenges of nuclear physics. The central theme of this proposal is to develop a new method for obtaining a reliable microscopic description of nuclei across the nuclear landscape. This method, which is called the Density Matrix Renormalization Group, has proven very successful in the treatment of many other complex many-body quantum systems, and seems very well suited for application to atomic nuclei as well. The goal of the proposal is to build the Density Matrix Renormalization Group into a practical approach for the microscopic description of atomic nuclei and to apply it systematically across the periodic table.Success in achieving the goals of this project should have broad impact extending well beyond the nuclear domain. Having a reliable description of the detailed structure of atomic nuclei makes it possible to address fundamental issues in nuclear astrophysics, including how the elements in the universe are synthesized, as well as issues related to fundamental symmetries of nature. The method being developed is computationally very intensive, requiring the development of new computational algorithms that should also have broad application across felds. Finally, the scientific research that is proposed will involve the active participation of several Ph.D. students, helping to train them in forefront scientific research and in cutting edge computational methodologies.