The atomic nucleus is a complex quantum many-body system whose rich and diverse behaviour continues to challenge our understanding. A central goal of nuclear structure physics is to understand how nuclear properties, probed using a wide range of reactions and techniques, evolve as a function of excitation energy, angular momentum and also by changing proton and neutron numbers across the nuclear chart. This talk will illustrate the symbiotic relationship between theoretical frameworks and experimental data.
We will explore how symmetry-based approaches reveal systematic patterns in experimental data and provide physical insight complementary to computationally intensive large-scale shell-model calculations. Long-lived excited states (isomers), which serve as sensitive probes of nuclear structure, will be used as illustrative examples to investigate phenomena such as emergent symmetries, seniority breaking, and the evolution of shapes and shells.
Finally, we will discuss emerging approaches that are transforming nuclear structure studies. These include i) Physics-informed machine-learning techniques that can uncover hidden correlations in nuclear data, enabling robust predictions and the underlying physics, ii) recent advances in quantum computing and its potential for addressing the challenges in nuclear structure.