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Theoretical and Computational Physics

The Theoretical and Computational Physics Group utilizes high performance and quantum computing to address problems in nuclear and particle physics.  We focus on understanding how nuclear structure evolves across the nuclear chart, and how stars live, die and create the elements of which we and our surroundings are made. 


Nuclear structure seeks to understand the ways that neutrons and protons assemble into atomic nuclei. The nuclear structure effort of the TCP group studies the structure of nuclei, focusing on radioactive isotopes of interest to the Facility for Rare Isotope Beams.  We use coupled-cluster theory for nuclear structure to compute nuclear properties, for example, to uncover the limits of nuclear formation. We also employ effective field theory (EFT) calculations for few-body nuclear systems (e.g. Halo EFT).  We have recently begun exploring the use of quantum computing for nuclear structure, computing the deuteron binding energy and investigating neutron superfluidity in nuclear matter.

Nuclear astrophysics is the study of the mechanisms by which stars and stellar events create atomic nuclei and the effects that this elemental creation has on these stars and stellar remnants.  The nuclear astrophysics effort of the TCP group performs simulations of explosive astronomical events like supernovae, novae and gamma-ray bursts, in order to understand these events and their observable signatures in neutrino and gravitational wave detectors.  We focus on the contributions of these astronomical explosions to the production of chemical elements in the Galaxy, seeking to explain that step in our cosmic origins.  We also investigate the knowledge of the structure of neutron stars and the properties of nuclear matter that can be discerned from astronomical observations.

Quantum computing is an emerging field with great potential for the computation of the properties of quantum many-body systems, common in nuclear and high energy physics.  However, the path to effectively harnessing this potential is highly uncertain.  We are therefore actively engaged in algorithm development for quantum computing, tailored for problems in nuclear and particle physics.  Further, we are investigating the uses of quantum computing and machine learning for the analysis of experimental physics data.