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Algorithms Bridging Quantum Computation and Chemistry- [electronic resource]
![Algorithms Bridging Quantum Computation and Chemistry - [electronic resource] / McClean, J...](/Sponge/Images/bookDefaults/DDbookdefaultsmall.png)
Algorithms Bridging Quantum Computation and Chemistry- [electronic resource]
상세정보
- 자료유형
- 학위논문(국외)
- 자관 청구기호
- 기본표목-개인명
- 표제와 책임표시사항
- Algorithms Bridging Quantum Computation and Chemistry - [electronic resource] / McClean, Jarrod Ryan.
- 발행, 배포, 간사 사항
- 형태사항
- 1 online resource(244 p)
- 일반주기
- Source: Dissertation Abstracts International, Volume: 77-04(E), Section: B.
- 일반주기
- Adviser: Alan Aspuru-Guzik.
- 학위논문주기
- Thesis (Ph.D.)--Harvard University, 2015.
- 요약 등 주기
- 요약The design of new materials and chemicals derived entirely from computation has long been a goal of computational chemistry, and the governing equation whose solution would permit this dream is known. Unfortunately, the exact solution to this equation has been far too expensive and clever approximations fail in critical situations. Quantum computers offer a novel solution to this problem. In this work, we develop not only new algorithms to use quantum computers to study hard problems in chemistry, but also explore how such algorithms can help us to better understand and improve our traditional approaches.
- 요약 등 주기
- 요약In particular, we first introduce a new method, the variational quantum eigensolver, which is designed to maximally utilize the quantum resources available in a device to solve chemical problems. We apply this method in a real quantum photonic device in the lab to study the dissociation of the helium hydride (HeH+) molecule.
- 요약 등 주기
- 요약We also enhance this methodology with architecture specific optimizations on ion trap computers and show how linear-scaling techniques from traditional quantum chemistry can be used to improve the outlook of similar algorithms on quantum computers. We then show how studying quantum algorithms such as these can be used to understand and enhance the development of classical algorithms. In particular we use a tool from adiabatic quantum computation, Feynman's Clock, to develop a new discrete time variational principle and further establish a connection between real-time quantum dynamics and ground state eigenvalue problems. We use these tools to develop two novel parallel-in-time quantum algorithms that outperform competitive algorithms as well as offer new insights into the connection between the fermion sign problem of ground states and the dynamical sign problem of quantum dynamics.
- 요약 등 주기
- 요약Finally we use insights gained in the study of quantum circuits to explore a general notion of sparsity in many-body quantum systems. In particular we use developments from the field of compressed sensing to find compact representations of ground states. As an application we study electronic systems and find solutions dramatically more compact than traditional configuration interaction expansions, offering hope to extend this methodology to challenging systems in chemical and material design.
- 주제명부출표목-일반주제명
- 주제명부출표목-일반주제명
- 부출표목-단체명
- 기본자료저록
- Dissertation Abstracts International. 77-04B(E).
- 기본자료저록
- Dissertation Abstract International
- 전자적 위치 및 접속
- 원문정보보기
- 소장사항
-
20170404 2017
MARC
008170601s2015 us esm 001c eng■001MOKWON01255854
■00520170418121729
■007cr
■020 ▼a9781339295350
■035 ▼a(MiAaPQ)AAI3738997
■040 ▼aMiAaPQ▼cMiAaPQ
■090 ▼a전자도서(박사논문)
■1001 ▼aMcClean, Jarrod Ryan.
■24510▼aAlgorithms Bridging Quantum Computation and Chemistry▼h[electronic resource]▼cMcClean, Jarrod Ryan.
■260 ▼a[Sl]▼bHarvard University▼c2015
■300 ▼a1 online resource(244 p)
■500 ▼aSource: Dissertation Abstracts International, Volume: 77-04(E), Section: B.
■500 ▼aAdviser: Alan Aspuru-Guzik.
■5021 ▼aThesis (Ph.D.)--Harvard University, 2015.
■520 ▼aThe design of new materials and chemicals derived entirely from computation has long been a goal of computational chemistry, and the governing equation whose solution would permit this dream is known. Unfortunately, the exact solution to this equation has been far too expensive and clever approximations fail in critical situations. Quantum computers offer a novel solution to this problem. In this work, we develop not only new algorithms to use quantum computers to study hard problems in chemistry, but also explore how such algorithms can help us to better understand and improve our traditional approaches.
■520 ▼aIn particular, we first introduce a new method, the variational quantum eigensolver, which is designed to maximally utilize the quantum resources available in a device to solve chemical problems. We apply this method in a real quantum photonic device in the lab to study the dissociation of the helium hydride (HeH+) molecule.
■520 ▼aWe also enhance this methodology with architecture specific optimizations on ion trap computers and show how linear-scaling techniques from traditional quantum chemistry can be used to improve the outlook of similar algorithms on quantum computers. We then show how studying quantum algorithms such as these can be used to understand and enhance the development of classical algorithms. In particular we use a tool from adiabatic quantum computation, Feynman's Clock, to develop a new discrete time variational principle and further establish a connection between real-time quantum dynamics and ground state eigenvalue problems. We use these tools to develop two novel parallel-in-time quantum algorithms that outperform competitive algorithms as well as offer new insights into the connection between the fermion sign problem of ground states and the dynamical sign problem of quantum dynamics.
■520 ▼aFinally we use insights gained in the study of quantum circuits to explore a general notion of sparsity in many-body quantum systems. In particular we use developments from the field of compressed sensing to find compact representations of ground states. As an application we study electronic systems and find solutions dramatically more compact than traditional configuration interaction expansions, offering hope to extend this methodology to challenging systems in chemical and material design.
■590 ▼aSchool code: 0084.
■650 4▼aPhysical chemistry
■650 4▼aMolecular physics
■690 ▼a0494
■690 ▼a0609
■71020▼aHarvard University▼bChemical Physics.
■7730 ▼tDissertation Abstracts International▼g77-04B(E).
■773 ▼tDissertation Abstract International
■790 ▼a0084
■791 ▼aPh.D.
■792 ▼a2015
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T14491657▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
■980 ▼a20170404▼f2017
