Harnessing Quantum Systems for Sensing, Simulation, and Optimization
Harnessing Quantum Systems for Sensing, Simulation, and Optimization
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20250211151938
- ISBN
- 9798384423713
- DDC
- 530.1
- 서명/저자
- Harnessing Quantum Systems for Sensing, Simulation, and Optimization
- 발행사항
- [Sl] : University of Maryland, College Park, 2024
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2024
- 형태사항
- 442 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 86-03, Section: B.
- 주기사항
- Advisor: Gorshkov, Alexey V.;Davoudi, Zohreh.
- 학위논문주기
- Thesis (Ph.D.)--University of Maryland, College Park, 2024.
- 초록/해제
- 요약Quantum information science offers a remarkable promise: by thinking practically about how quantum systems can be put to work to solve computational and information processing tasks, we gain novel insights into the foundations of quantum theory and computer science. Or, conversely, by (re)considering the fundamental physical building blocks of computers and sensors, we enable new technologies, with major impacts for computational and experimental physics.In this dissertation, we explore these ideas through the lens of three different types of quantum hardware, each with a particular application primarily in mind: (1) networks of quantum sensors for measuring global properties of local field(s); (2) analog quantum computers for solving combinatorial optimization problems; and (3) digital quantum computers for simulating lattice (gauge) theories.For the setting of quantum sensor networks, we derive the fundamental performance limits for the sensing task of measuring global properties of local field(s) in a variety of physical settings (qubit sensors, Mach-Zehnder interferometers, quadrature displacements) and present explicit protocols that achieve these limits. In the process, we reveal the geometric structure of the fundamental bounds and the associated algebraic structure of the corresponding protocols. We also find limits on the resources (e.g. entanglement or number of control operations) required by such protocols.For analog quantum computers, we focus on the possible origins of quantum advantage for solving combinatorial optimization problems with an emphasis on investigating the power of adiabatic quantum computation with so-called stoquastic Hamiltonians. Such Hamiltonians do not exhibit a sign problem when classically simulated via quantum Monte Carlo algorithms, suggesting deep connections between the sign problem, the locality of interactions, and the origins of quantum advantage. We explore these connections in detail.Finally, for digital quantum computers, we consider the optimization of two tasks relevant for simulating lattice (gauge) theories. First, we investigate how to map fermionic systems to qubit systems in a hardware-aware manner that consequently enables an improved parallelization of Trotter-based time evolution algorithms on the qubitized Hamiltonian. Second, we investigate how to take advantage of known symmetries in lattice gauge theories to construct more efficient randomized measurement protocols for extracting purities and entanglement entropies from simulated states. We demonstrate how these protocols can be used to detect a phase transition between a trivial and a topologically ordered phase in Z2 lattice gauge theory. Detecting this transition via these randomized methods would not otherwise be possible without relearning all symmetries.
- 일반주제명
- Quantum physics
- 일반주제명
- Computer science
- 일반주제명
- Theoretical physics
- 일반주제명
- Computational physics
- 키워드
- Optimization
- 키워드
- Quantum theory
- 기타저자
- University of Maryland, College Park Physics
- 기본자료저록
- Dissertations Abstracts International. 86-03B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■1001 ▼aBringewatt, Jacob Allen.▼0(orcid)0000-0003-3235-3444
■24510▼aHarnessing Quantum Systems for Sensing, Simulation, and Optimization
■260 ▼a[Sl]▼bUniversity of Maryland, College Park▼c2024
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2024
■300 ▼a442 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 86-03, Section: B.
■500 ▼aAdvisor: Gorshkov, Alexey V.;Davoudi, Zohreh.
■5021 ▼aThesis (Ph.D.)--University of Maryland, College Park, 2024.
■520 ▼aQuantum information science offers a remarkable promise: by thinking practically about how quantum systems can be put to work to solve computational and information processing tasks, we gain novel insights into the foundations of quantum theory and computer science. Or, conversely, by (re)considering the fundamental physical building blocks of computers and sensors, we enable new technologies, with major impacts for computational and experimental physics.In this dissertation, we explore these ideas through the lens of three different types of quantum hardware, each with a particular application primarily in mind: (1) networks of quantum sensors for measuring global properties of local field(s); (2) analog quantum computers for solving combinatorial optimization problems; and (3) digital quantum computers for simulating lattice (gauge) theories.For the setting of quantum sensor networks, we derive the fundamental performance limits for the sensing task of measuring global properties of local field(s) in a variety of physical settings (qubit sensors, Mach-Zehnder interferometers, quadrature displacements) and present explicit protocols that achieve these limits. In the process, we reveal the geometric structure of the fundamental bounds and the associated algebraic structure of the corresponding protocols. We also find limits on the resources (e.g. entanglement or number of control operations) required by such protocols.For analog quantum computers, we focus on the possible origins of quantum advantage for solving combinatorial optimization problems with an emphasis on investigating the power of adiabatic quantum computation with so-called stoquastic Hamiltonians. Such Hamiltonians do not exhibit a sign problem when classically simulated via quantum Monte Carlo algorithms, suggesting deep connections between the sign problem, the locality of interactions, and the origins of quantum advantage. We explore these connections in detail.Finally, for digital quantum computers, we consider the optimization of two tasks relevant for simulating lattice (gauge) theories. First, we investigate how to map fermionic systems to qubit systems in a hardware-aware manner that consequently enables an improved parallelization of Trotter-based time evolution algorithms on the qubitized Hamiltonian. Second, we investigate how to take advantage of known symmetries in lattice gauge theories to construct more efficient randomized measurement protocols for extracting purities and entanglement entropies from simulated states. We demonstrate how these protocols can be used to detect a phase transition between a trivial and a topologically ordered phase in Z2 lattice gauge theory. Detecting this transition via these randomized methods would not otherwise be possible without relearning all symmetries.
■590 ▼aSchool code: 0117.
■650 4▼aQuantum physics
■650 4▼aComputer science
■650 4▼aTheoretical physics
■650 4▼aComputational physics
■653 ▼aQuantum algorithms
■653 ▼aQuantum computation
■653 ▼aQuantum information science
■653 ▼aOptimization
■653 ▼aQuantum theory
■690 ▼a0599
■690 ▼a0984
■690 ▼a0753
■690 ▼a0216
■71020▼aUniversity of Maryland, College Park▼bPhysics.
■7730 ▼tDissertations Abstracts International▼g86-03B.
■790 ▼a0117
■791 ▼aPh.D.
■792 ▼a2024
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17162148▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
