Computational developments for ab initio many-body theory
Lietz, Justin Gage
author
Hjorth-Jensen, Morten
thesis advisor
Bogner, Scott
degree committee member
O'Shea, Brian
degree committee member
Gade, Alex
degree committee member
Bazavov, Alexei
degree committee member
text
Text
Theses
No place, unknown, or undetermined
2019
2019
eng
English
application/pdf
xiii, 194 pages
Quantum many-body physics is the body of knowledge which studies systems of many interacting particles and the mathematical framework for calculating properties of these systems. Methods in many-body physics which use a first principles approach to solving the many-body Schrodinger equation are referred to as ab initio methods, and provide approximate solutions which are systematically improvable. Coupled cluster theory is an ab initio quantum many-body method which has been shown to provide accurate calculations of ground state energies for a wide range of systems in quantum chemistry and nuclear physics. Calculations of physical properties using ab initio many-body methods can be computationally expensive, requiring the development of efficient data structures, algorithms and techniques in high-performance computing to achieve numerical accuracy.Many physical systems of interest are difficult or impossible to measure experimentally, and so are reliant on predictive and accurate calculations from many-body theory. Neutron stars in particular are difficult to collect observational data for, but simulations of infinite nuclear matter can provide key insights to the internal structure of these astronomical objects. The main focus of this thesis is the development of a large and versatile coupled cluster program which implements a sparse tensor storage scheme and efficient tensor contraction algorithms. A distributed memory data structure for these large, sparse tensors is used so that the code can run in a high-performance computing setting, and can thus handle the computational challenges of infinite nuclear matter calculations using large basis sets. By validating these data structures and algorithms in the context of coupled cluster theory and infinite nuclear matter, they can be applied to a wide range of many-body methods and physical systems.
Justin Gage Lietz
Thesis (Ph. D.)--Michigan State University. Physics, 2019
Includes bibliographical references (pages 187-194)
Quantum chemistry
High performance computing
Many-body problem
Approximation methods
Quantum chemistry
Many-body problem
Approximation methods
High performance computing
Computational physics
Nuclear physics and radiation
Theoretical physics
Electronic Theses & Dissertations
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9781085617277
1085617270
1138555777
22583781
Lietz_grad.msu_0128D_16977
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Michigan State University. Libraries
2020-04-23
2021-03-26
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