Structure of nuclei far from stability

低能核物理学在对其研究对象的基本理解方面即将发生重大的范式转变。在轻核中，现在可以提供受强相互作用的量子色动力学（QCD）理论启发的核结构的从头计算预测，打破了数十年来从全球或局部拟合实验数据得出的唯象有效相互作用的统治。这些方法用于分析轻离子诱导反应，在统一的框架内考虑它们的结构;这打破了核反应和核结构理论之间的传统分离。在加拿大国家粒子和核物理实验室TRIUMF，加速器和复杂的伽马射线探测系统的持续发展使人们能够研究远离稳定的原子核，从而检验人们对稳定和近稳定原子核的理解。一个突出的例子是，由于中子或质子过剩而引起的核壳层有序性的改变，通常以意想不到的方式重新排列壳层结构，并打破了自旋/宇称、质量、结合和激发能等可观测量的趋势。组态相互作用方法使用二体和三体相互作用的启发QCD允许解决多体核问题的中等质量的核，包括那些远离稳定，而密度泛函理论提供了进一步的扩展，调查这些相互作用的有效性最重的核。目前的理论方法系统地跟踪近似值所施加的误差，预测趋势和不确定性。

Low-energy nuclear physics is on the verge of a significant paradigm shift in the basic understanding of its objects of study. In light nuclei it is now possible to provide ab-initio predictions of nuclear structure inspired by the Quantum Chromodynamics (QCD) theory of strong interactions, breaking a decades-long reign of phenomenological effective interactions derived from global or local fits to experimental data. These methods are used for analysis of light-ion induced reactions taking into account their structure within a unified framework; this defies the traditional separation between nuclear reaction and nuclear structure theories. At TRIUMF, Canada's National Laboratory for Particle and Nuclear Physics, sustained development in accelerators and sophisticated gamma-ray detection systems permits the study of nuclei very far from stability that tests understanding developed for stable and near-stable nuclei. A striking example is the change of nuclear shell ordering prompted by the neutron or proton excess that rearranges shell structure, often in unexpected ways, and breaks trends of observables such as spins/parities, masses, binding, and excitation energies established near stability. Configuration Interaction methods using two- and three-body interactions inspired by QCD allow the many-body nuclear problem to be solved for medium mass nuclei, including those far from stability, while density functional theories provide a further extension for investigating the validity of these interactions up to the heaviest nuclei. Current theoretical methods track errors imposed by approximations systematically, predicting trends together with uncertainties.