자료유형  

 학위논문

Control Number  

0017164585

International Standard Book Number  

9798342764391

Dewey Decimal Classification Number  

530.1

Main Entry-Personal Name  

Bonitati, Joey.

Publication, Distribution, etc. (Imprint  

[S.l.] : Michigan State University., 2024

Publication, Distribution, etc. (Imprint  

Ann Arbor : ProQuest Dissertations & Theses, 2024

Physical Description  

129 p.

General Note  

Source: Dissertations Abstracts International, Volume: 86-05, Section: B.

General Note  

Advisor: Lee, Dean.

Dissertation Note  

Thesis (Ph.D.)--Michigan State University, 2024.

Summary, Etc.  

요약This thesis investigates quantum algorithms for eigenstate preparation, with a primary focus on solving eigenvalue problems such as the Schrodinger equation by utilizing near-term quantum computing devices. These problems are ubiquitous in several scientific fields, but more accurate solutions are specifically needed as a prerequisite for many quantum simulation tasks. To address this, we establish three methods in detail: quantum adiabatic evolution with optimal control, the Rodeo Algorithm, and the Variational Rodeo Algorithm.The first method explored is adiabatic evolution, a technique that prepares quantum states by simulating a quantum system that evolves slowly over time. The adiabatic theorem can be used to ensure that the system remains in an eigenstate throughout the process, but its implementation can often be infeasible on current quantum computing hardware. We employ a unique approach using optimal control to create custom gate operations for superconducting qubits and demonstrate the algorithm on a two-qubit IBM cloud quantum computing device. We then explore an alternative to adiabatic evolution, the Rodeo Algorithm, which offers a different approach to eigenstate preparation by using a controlled quantum evolution that selectively filters out undesired components in the wave function stored on a quantum register. We show results suggesting that this method can be effective in preparing eigenstates, but its practicality is predicated on the preparation of an initial state that has significant overlap with the desired eigenstate. To address this, we introduce the novel Variational Rodeo Algorithm, which replaces the initialization step with dynamic optimization of quantum circuit parameters to increase the success probability of the Rodeo Algorithm. The added flexibility compensates for instances in which the original algorithm can be unsuccessful, allowing for better scalability. This research seeks to contribute to a deeper understanding of how quantum algorithms can be employed to attain efficient and accurate solutions to eigenvalue problems. The overarching goal is to present ideas that can be used to improve understanding of nuclear physics by providing potential quantum and classical techniques that can aid in tasks such as the theoretical description of nuclear structures and the simulation of nuclear reactions.

Subject Added Entry-Topical Term  

Quantum physics.

Subject Added Entry-Topical Term  

Computational physics.

Subject Added Entry-Topical Term  

Computer engineering.

Subject Added Entry-Topical Term  

Nuclear physics.

Index Term-Uncontrolled  

Quantum algorithms

Index Term-Uncontrolled  

Quantum computing

Index Term-Uncontrolled  

Quantum simulation

Index Term-Uncontrolled  

Rodeo Algorithm

Index Term-Uncontrolled  

Scalability

Added Entry-Corporate Name  

Michigan State University Physics - Doctor of Philosophy

Host Item Entry  

Dissertations Abstracts International. 86-05B.

Electronic Location and Access  

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Control Number  

joongbu:654927