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High-Dimensional Molecular Quantum Dynamics With Tensor-Trains and Quantum Computation
High-Dimensional Molecular Quantum Dynamics With Tensor-Trains and Quantum Computation
Detailed Information
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20250211151006
- ISBN
- 9798383565759
- DDC
- 540
- 저자명
- Lyu, Ningyi.
- 서명/저자
- High-Dimensional Molecular Quantum Dynamics With Tensor-Trains and Quantum Computation
- 발행사항
- [Sl] : Yale University, 2024
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2024
- 형태사항
- 168 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 86-02, Section: B.
- 주기사항
- Advisor: Batista, Victor S.
- 학위논문주기
- Thesis (Ph.D.)--Yale University, 2024.
- 초록/해제
- 요약This thesis introduces numerically exact methods for simulating the quantum dynamics of complex molecular systems beyond the limitations of current models like Transition State Theory and the Born-Oppenheimer approximation. By leveraging tensor-train-based solvers and advancements in quantum hardware, particularly bosonic circuit Quantum Electrodynamics (cQED) processors, the computational challenges posed by the "curse of dimensionality" of high-dimensional molecular wavefunctions are addressed. Applied methods demonstrate significant progress in modeling intricate chemical processes such as electron and energy transfer and photochemical reactions across various systems from biological complexes to in-solvent intramolecular charge transfer processes. Specific attention has focused on the development and application of the Tensor-Train Split-Operator KSL (TT-SOKSL) method for high-dimensional wavefunction dynamics and Tensor-Train Thermo-Field Dynamics (TT-TFD) method for high-dimensional density matrix propagation. The feasibility of employing bosonic cQED devices for molecular simulations has also been explored, including novel strategies like the Single-Bosonic-Mode (SBM) mapping for cQED-based simulation of arbitrary molecular Hamiltonians and a holographic quantum-computing scheme for Gaussian Boson Sampling (GBS) tasks. The findings emerging from this work not only offer new insights into quantum molecular dynamics but also pave the way for practical quantum computing applications in chemistry and drug discovery.
- 일반주제명
- Chemistry
- 일반주제명
- Physical chemistry
- 일반주제명
- Quantum physics
- 일반주제명
- Molecular chemistry
- 기타저자
- Yale University Chemistry
- 기본자료저록
- Dissertations Abstracts International. 86-02B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■00520250211151006
■006m o d
■007cr#unu||||||||
■020 ▼a9798383565759
■035 ▼a(MiAaPQ)AAI30994700
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a540
■1001 ▼aLyu, Ningyi.
■24510▼aHigh-Dimensional Molecular Quantum Dynamics With Tensor-Trains and Quantum Computation
■260 ▼a[Sl]▼bYale University▼c2024
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2024
■300 ▼a168 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 86-02, Section: B.
■500 ▼aAdvisor: Batista, Victor S.
■5021 ▼aThesis (Ph.D.)--Yale University, 2024.
■520 ▼aThis thesis introduces numerically exact methods for simulating the quantum dynamics of complex molecular systems beyond the limitations of current models like Transition State Theory and the Born-Oppenheimer approximation. By leveraging tensor-train-based solvers and advancements in quantum hardware, particularly bosonic circuit Quantum Electrodynamics (cQED) processors, the computational challenges posed by the "curse of dimensionality" of high-dimensional molecular wavefunctions are addressed. Applied methods demonstrate significant progress in modeling intricate chemical processes such as electron and energy transfer and photochemical reactions across various systems from biological complexes to in-solvent intramolecular charge transfer processes. Specific attention has focused on the development and application of the Tensor-Train Split-Operator KSL (TT-SOKSL) method for high-dimensional wavefunction dynamics and Tensor-Train Thermo-Field Dynamics (TT-TFD) method for high-dimensional density matrix propagation. The feasibility of employing bosonic cQED devices for molecular simulations has also been explored, including novel strategies like the Single-Bosonic-Mode (SBM) mapping for cQED-based simulation of arbitrary molecular Hamiltonians and a holographic quantum-computing scheme for Gaussian Boson Sampling (GBS) tasks. The findings emerging from this work not only offer new insights into quantum molecular dynamics but also pave the way for practical quantum computing applications in chemistry and drug discovery.
■590 ▼aSchool code: 0265.
■650 4▼aChemistry
■650 4▼aPhysical chemistry
■650 4▼aQuantum physics
■650 4▼aMolecular chemistry
■653 ▼aTensor-Train Thermo-Field Dynamics
■653 ▼aCircuit Quantum Electrodynamics
■653 ▼aSingle-Bosonic-Mode
■653 ▼aQuantum computation
■653 ▼aGaussian Boson Sampling
■690 ▼a0485
■690 ▼a0599
■690 ▼a0431
■690 ▼a0494
■71020▼aYale University▼bChemistry.
■7730 ▼tDissertations Abstracts International▼g86-02B.
■790 ▼a0265
■791 ▼aPh.D.
■792 ▼a2024
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17160368▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
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