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The Physics of Computing With Memory
The Physics of Computing With Memory
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20250211152726
- ISBN
- 9798384468110
- DDC
- 530
- 저자명
- Zhang, Yuanhang.
- 서명/저자
- The Physics of Computing With Memory
- 발행사항
- [Sl] : University of California, San Diego, 2024
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2024
- 형태사항
- 198 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 86-04, Section: B.
- 주기사항
- Advisor: Di Ventra, Massimiliano.
- 학위논문주기
- Thesis (Ph.D.)--University of California, San Diego, 2024.
- 초록/해제
- 요약The evolution of computing technologies has perpetually intersected with the fundamental principles of physics. In this dissertation, we explore the frontier of computational paradigms through the lens of memory-augmented physical systems. Conventional computing, constrained by the architecture of Turing machines, can be substantially evolved by incorporating elements of memory into the physical computing substrates.We demonstrate that time non-local interactions, conceptualized as "memory," can induce spatial long-range order by correlating distant computational units despite their spatially local interactions. Such long-range order is critical for solving complex optimization problems as it enables strategies that transcend local moves to escape local minima. MemComputing, embodying this methodology, solves target problems by following the trajectory of a dynamical system embedded with memory. This system is meticulously designed so that its equilibrium points align with the solutions of the problem, and it explores distant configurations through instantonic tunneling.We provide a comprehensive demonstration of the MemComputing framework through applications in complex problem-solving scenarios, including the efficient simulation of quantum systems and tackling NP-complete problems like the SAT problem. Our findings indicate significant enhancements over traditional computing methods, spotlighting the profound potential of integrating memory with physical systems for next-generation computing.This research not only deepens our understanding of the intersection between memory and physical laws in computational processes but also establishes a foundational basis for the development of next-generation computing technologies. These technologies are poised to be more efficient and scalable, representing a significant leap over conventional computational frameworks.
- 일반주제명
- Condensed matter physics
- 일반주제명
- Computational physics
- 일반주제명
- Computer science
- 일반주제명
- Physics
- 키워드
- MemComputing
- 키워드
- Quantum systems
- 키워드
- Dynamical system
- 기타저자
- University of California, San Diego Physics
- 기본자료저록
- Dissertations Abstracts International. 86-04B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■006m o d
■007cr#unu||||||||
■020 ▼a9798384468110
■035 ▼a(MiAaPQ)AAI31490210
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a530
■1001 ▼aZhang, Yuanhang.
■24510▼aThe Physics of Computing With Memory
■260 ▼a[Sl]▼bUniversity of California, San Diego▼c2024
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2024
■300 ▼a198 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 86-04, Section: B.
■500 ▼aAdvisor: Di Ventra, Massimiliano.
■5021 ▼aThesis (Ph.D.)--University of California, San Diego, 2024.
■520 ▼aThe evolution of computing technologies has perpetually intersected with the fundamental principles of physics. In this dissertation, we explore the frontier of computational paradigms through the lens of memory-augmented physical systems. Conventional computing, constrained by the architecture of Turing machines, can be substantially evolved by incorporating elements of memory into the physical computing substrates.We demonstrate that time non-local interactions, conceptualized as "memory," can induce spatial long-range order by correlating distant computational units despite their spatially local interactions. Such long-range order is critical for solving complex optimization problems as it enables strategies that transcend local moves to escape local minima. MemComputing, embodying this methodology, solves target problems by following the trajectory of a dynamical system embedded with memory. This system is meticulously designed so that its equilibrium points align with the solutions of the problem, and it explores distant configurations through instantonic tunneling.We provide a comprehensive demonstration of the MemComputing framework through applications in complex problem-solving scenarios, including the efficient simulation of quantum systems and tackling NP-complete problems like the SAT problem. Our findings indicate significant enhancements over traditional computing methods, spotlighting the profound potential of integrating memory with physical systems for next-generation computing.This research not only deepens our understanding of the intersection between memory and physical laws in computational processes but also establishes a foundational basis for the development of next-generation computing technologies. These technologies are poised to be more efficient and scalable, representing a significant leap over conventional computational frameworks.
■590 ▼aSchool code: 0033.
■650 4▼aCondensed matter physics
■650 4▼aComputational physics
■650 4▼aComputer science
■650 4▼aPhysics
■653 ▼aComputing technologies
■653 ▼aMemComputing
■653 ▼aEquilibrium points
■653 ▼aQuantum systems
■653 ▼aDynamical system
■690 ▼a0611
■690 ▼a0216
■690 ▼a0984
■690 ▼a0605
■71020▼aUniversity of California, San Diego▼bPhysics.
■7730 ▼tDissertations Abstracts International▼g86-04B.
■790 ▼a0033
■791 ▼aPh.D.
■792 ▼a2024
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17163574▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
