Computational Approaches to the Nuclear Many-Body Problem
type: CreativeWork
description: The nuclear many-body problem is conceptualized in an infinite-dimensional Hilbert space, but computationally solved in a finite one. Thus, the predictive power of microscopic calculations relies on the truncated representation of the infinite-dimensional space as well as leveraging advanced computational methods. My dissertation research focuses on three problems related to computational nuclear physics: exploring aspects of nuclear structure, efficiently solving the large sparse matrix-eigenvalue problem and improving the construction of the many-body basis in the no-core configuration-interaction (NCCI) framework. I) Elliott’s rotational SU(3) model, and its later extension, the symplectic Sp(3, R) model, both played a foundational role in improving the description of nuclear rotational spectral bands. My study of several beryllium isotopes, and 20Ne uses the decomposition of no-core shell-model wavefunctions into symmetry defined subspaces to show the Sp(3, R) picture provides a more consistent description of rotational band structure. II) Solving the non-relativistic many-body Schrödinger equation is often cast as a large sparse Hamiltonian eigenvalue problem. State-of-the-art NCCI calculation dimensions can exceed several billion and typically require supercomputers and thousands of core hours to compute small numbers of low-lying eigenstates. Thus, there is strong motivation for ways to reduce computational costs. In this research, I augment the block Lanczos algorithm using a bootstrapped pivot to significantly reduce the number of Hamiltonian-matrix multiplications typically dominating the algorithm’s total time-to-solution. My results demonstrate significant speedup in time-to-solution, often by a factor of two or more, and up to ten, can be achieved through the use of bootstrapping. III) In NCCI, the many-body basis is historically constructed from antisymmeterized products of harmonic oscillator (HO) single-particle wavefunctions. However, one often need…
abstract: The nuclear many-body problem is conceptualized in an infinite-dimensional Hilbert space, but computationally solved in a finite one. Thus, the predictive power of microscopic calculations relies on the truncated representation of the infinite-dimensional space as well as leveraging advanced computational methods. My dissertation research focuses on three problems related to computational nuclear physics: exploring aspects of nuclear structure, efficiently solving the large sparse matrix-eigenvalue problem and improving the construction of the many-body basis in the no-core configuration-interaction (NCCI) framework. I) Elliott’s rotational SU(3) model, and its later extension, the symplectic Sp(3, R) model, both played a foundational role in improving the description of nuclear rotational spectral bands. My study of several beryllium isotopes, and 20Ne uses the decomposition of no-core shell-model wavefunctions into symmetry defined subspaces to show the Sp(3, R) picture provides a more consistent description of rotational band structure. II) Solving the non-relativistic many-body Schrödinger equation is often cast as a large sparse Hamiltonian eigenvalue problem. State-of-the-art NCCI calculation dimensions can exceed several billion and typically require supercomputers and thousands of core hours to compute small numbers of low-lying eigenstates. Thus, there is strong motivation for ways to reduce computational costs. In this research, I augment the block Lanczos algorithm using a bootstrapped pivot to significantly reduce the number of Hamiltonian-matrix multiplications typically dominating the algorithm’s total time-to-solution. My results demonstrate significant speedup in time-to-solution, often by a factor of two or more, and up to ten, can be achieved through the use of bootstrapping. III) In NCCI, the many-body basis is historically constructed from antisymmeterized products of harmonic oscillator (HO) single-particle wavefunctions. However, one often need…
author: Zbikowski, Ryan M
keywords: Computational Physics, Computational Science, Lanczos Algorithm, Nuclear Structure
date published: 2024-01-01T08:00:00Z
date modified: 2026-07-24T01:40:36Z
provider: Claremont Graduate University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Claremont Graduate University