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Emergent Features of Many-Body Systems: Classical and Quantum
Emergent Features of Many-Body Systems: Classical and Quantum
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20260202105618
- ISBN
- 9798265427656
- DDC
- 658
- 저자명
- Nebabu, Tamra.
- 서명/저자
- Emergent Features of Many-Body Systems: Classical and Quantum
- 발행사항
- [Sl] : Stanford University, 2025
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2025
- 형태사항
- 153 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 87-05, Section: B.
- 주기사항
- Advisor: Ganguli, Surya.
- 학위논문주기
- Thesis (Ph.D.)--Stanford University, 2025.
- 초록/해제
- 요약Emergence refers to the fact that complex, composite systems can exhibit fundamentally different behavior from their building blocks, and is an important tenet in many scientific disciplines. This thesis discusses emergence in the context of quantum many-body physics and machine learning. The first part will discuss how interacting quantum many-body dynamics can give rise to emergent effective dynamics at low energies, which may be given a geometric interpretation reminiscent of the emergent bulk in holographic duality. In the second part, I discuss the emergence of phase diagrams for large artificial neural networks in the context of neural network-encoded quantum states and signal propagation in deep transformers.
- 일반주제명
- Behavior
- 일반주제명
- Neurons
- 일반주제명
- Statistical mechanics
- 일반주제명
- Gravity
- 일반주제명
- Quantum theory
- 일반주제명
- Theoretical physics
- 일반주제명
- Black holes
- 일반주제명
- Neural networks
- 일반주제명
- Symmetry
- 일반주제명
- Phase transitions
- 일반주제명
- Geometry
- 일반주제명
- Entropy
- 일반주제명
- Astronomy
- 일반주제명
- Astrophysics
- 일반주제명
- Atomic physics
- 기타저자
- Stanford University.
- 기본자료저록
- Dissertations Abstracts International. 87-05B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■020 ▼a9798265427656
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■035 ▼a(MiAaPQ)Stanfordwg471tp4974
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a658
■1001 ▼aNebabu, Tamra.
■24510▼aEmergent Features of Many-Body Systems: Classical and Quantum
■260 ▼a[Sl]▼bStanford University▼c2025
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2025
■300 ▼a153 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 87-05, Section: B.
■500 ▼aAdvisor: Ganguli, Surya.
■5021 ▼aThesis (Ph.D.)--Stanford University, 2025.
■520 ▼aEmergence refers to the fact that complex, composite systems can exhibit fundamentally different behavior from their building blocks, and is an important tenet in many scientific disciplines. This thesis discusses emergence in the context of quantum many-body physics and machine learning. The first part will discuss how interacting quantum many-body dynamics can give rise to emergent effective dynamics at low energies, which may be given a geometric interpretation reminiscent of the emergent bulk in holographic duality. In the second part, I discuss the emergence of phase diagrams for large artificial neural networks in the context of neural network-encoded quantum states and signal propagation in deep transformers.
■590 ▼aSchool code: 0212.
■650 4▼aBehavior
■650 4▼aNeurons
■650 4▼aStatistical mechanics
■650 4▼aGravity
■650 4▼aQuantum theory
■650 4▼aTheoretical physics
■650 4▼aBlack holes
■650 4▼aNeural networks
■650 4▼aSymmetry
■650 4▼aPhase transitions
■650 4▼aGeometry
■650 4▼aEntropy
■650 4▼aAtoms & subatomic particles
■650 4▼aAstronomy
■650 4▼aAstrophysics
■650 4▼aAtomic physics
■690 ▼a0753
■690 ▼a0800
■690 ▼a0606
■690 ▼a0596
■690 ▼a0748
■71020▼aStanford University.
■7730 ▼tDissertations Abstracts International▼g87-05B.
■790 ▼a0212
■791 ▼aPh.D.
■792 ▼a2025
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17360780▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
