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Author: Tony Liu
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
"In recent years, adiabatic quantum computing (AQC) has established itself as a useful computing paradigm which utilizes the underlying physical process of quantum annealing (QA) to help solve NP-hard problems. The main enabler of this field has been the introduction of QA hardware by D-Wave Systems, the latest of which has up to 5640 qubits arranged in the topology of a Pegasus graph. Solving NP-hard problems using QA hardware typically involves a compilation (embedding) step which is equivalent to the graph minor embedding problem; itself an NP-hard problem. This has spurred the development of heuristic algorithms which can find valid minor embeddings for a given problem instance in a reasonable amount of time. This paper presents extensions to two papers: Clique Overlap Embedding implements an existing simulated annealing algorithm [1] with an improved guiding pattern and shifting rule; Fault Tolerant Template Embedding extends an integer programming formulation [2] to allow embedding on Chimera graphs with faulty qubits. Benchmark results show a marked improvement in embeddability for both approaches when compared to their original implementation,with each approach also showing distinct areas where they outperform the state of the art.."--Page 3.
Author: Tony Liu
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
"In recent years, adiabatic quantum computing (AQC) has established itself as a useful computing paradigm which utilizes the underlying physical process of quantum annealing (QA) to help solve NP-hard problems. The main enabler of this field has been the introduction of QA hardware by D-Wave Systems, the latest of which has up to 5640 qubits arranged in the topology of a Pegasus graph. Solving NP-hard problems using QA hardware typically involves a compilation (embedding) step which is equivalent to the graph minor embedding problem; itself an NP-hard problem. This has spurred the development of heuristic algorithms which can find valid minor embeddings for a given problem instance in a reasonable amount of time. This paper presents extensions to two papers: Clique Overlap Embedding implements an existing simulated annealing algorithm [1] with an improved guiding pattern and shifting rule; Fault Tolerant Template Embedding extends an integer programming formulation [2] to allow embedding on Chimera graphs with faulty qubits. Benchmark results show a marked improvement in embeddability for both approaches when compared to their original implementation,with each approach also showing distinct areas where they outperform the state of the art.."--Page 3.
Author: Catherine C. McGeoch
Publisher: Morgan & Claypool Publishers
ISBN: 1627053360
Category : Science
Languages : en
Pages : 95
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Book Description
Adiabatic quantum computation (AQC) is an alternative to the better-known gate model of quantum computation. The two models are polynomially equivalent, but otherwise quite dissimilar: one property that distinguishes AQC from the gate model is its analog nature. Quantum annealing (QA) describes a type of heuristic search algorithm that can be implemented to run in the ``native instruction set'' of an AQC platform. D-Wave Systems Inc. manufactures {quantum annealing processor chips} that exploit quantum properties to realize QA computations in hardware. The chips form the centerpiece of a novel computing platform designed to solve NP-hard optimization problems. Starting with a 16-qubit prototype announced in 2007, the company has launched and sold increasingly larger models: the 128-qubit D-Wave One system was announced in 2010 and the 512-qubit D-Wave Two system arrived on the scene in 2013. A 1,000-qubit model is expected to be available in 2014. This monograph presents an introductory overview of this unusual and rapidly developing approach to computation. We start with a survey of basic principles of quantum computation and what is known about the AQC model and the QA algorithm paradigm. Next we review the D-Wave technology stack and discuss some challenges to building and using quantum computing systems at a commercial scale. The last chapter reviews some experimental efforts to understand the properties and capabilities of these unusual platforms. The discussion throughout is aimed at an audience of computer scientists with little background in quantum computation or in physics.
Author: N.B. Singh
Publisher: N.B. Singh
ISBN:
Category : Computers
Languages : en
Pages : 330
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Book Description
"Graph Theory: Adiabatic Quantum Computing Methods" explores the convergence of quantum computing and graph theory, offering a comprehensive examination of how quantum algorithms can tackle fundamental graph problems. From foundational concepts to advanced applications in fields like cryptography, machine learning, and network analysis, this book provides a clear pathway into the evolving landscape of quantum-enhanced graph algorithms. Designed for researchers, students, and professionals alike, it bridges theoretical insights with practical implementations, paving the way for innovative solutions in computational graph theory.
Author: Seyedeh Sahba Etezad
Publisher:
ISBN:
Category :
Languages : en
Pages : 69
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Book Description
We present heuristic algorithms for minor embedding planar graphs in grids. Our work is motivated by the development of quantum computing hardware that performs quantum annealing. This hardware can be used to solve hard combinatorial problems, but requires the graph of each problem instance to be minor embedded in a graph that models the hardware. Hence, there is a need for practical minor embedding algorithms. We restrict our attention to planar graphs, and thus are able to make use of existing graph drawing methods. We present two algorithms for minor embedding planar graphs in grid graphs, and provide an experimental evaluation of one.
Author: Ponnuswamy Sadayappan
Publisher: Springer Nature
ISBN: 3030507432
Category : Computers
Languages : en
Pages : 564
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Book Description
This book constitutes the refereed proceedings of the 35th International Conference on High Performance Computing, ISC High Performance 2020, held in Frankfurt/Main, Germany, in June 2020.* The 27 revised full papers presented were carefully reviewed and selected from 87 submissions. The papers cover a broad range of topics such as architectures, networks & infrastructure; artificial intelligence and machine learning; data, storage & visualization; emerging technologies; HPC algorithms; HPC applications; performance modeling & measurement; programming models & systems software. *The conference was held virtually due to the COVID-19 pandemic. Chapters "Scalable Hierarchical Aggregation and Reduction Protocol (SHARP) Streaming-Aggregation Hardware Design and Evaluation", "Solving Acoustic Boundary Integral Equations Using High Performance Tile Low-Rank LU Factorization", "Scaling Genomics Data Processing with Memory-Driven Computing to Accelerate Computational Biology", "Footprint-Aware Power Capping for Hybrid Memory Based Systems", and "Pattern-Aware Staging for Hybrid Memory Systems" are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Author: Catherine C. McGeoch
Publisher: Springer Nature
ISBN: 3031025180
Category : Mathematics
Languages : en
Pages : 83
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Book Description
Adiabatic quantum computation (AQC) is an alternative to the better-known gate model of quantum computation. The two models are polynomially equivalent, but otherwise quite dissimilar: one property that distinguishes AQC from the gate model is its analog nature. Quantum annealing (QA) describes a type of heuristic search algorithm that can be implemented to run in the ``native instruction set'' of an AQC platform. D-Wave Systems Inc. manufactures {quantum annealing processor chips} that exploit quantum properties to realize QA computations in hardware. The chips form the centerpiece of a novel computing platform designed to solve NP-hard optimization problems. Starting with a 16-qubit prototype announced in 2007, the company has launched and sold increasingly larger models: the 128-qubit D-Wave One system was announced in 2010 and the 512-qubit D-Wave Two system arrived on the scene in 2013. A 1,000-qubit model is expected to be available in 2014. This monograph presents an introductory overview of this unusual and rapidly developing approach to computation. We start with a survey of basic principles of quantum computation and what is known about the AQC model and the QA algorithm paradigm. Next we review the D-Wave technology stack and discuss some challenges to building and using quantum computing systems at a commercial scale. The last chapter reviews some experimental efforts to understand the properties and capabilities of these unusual platforms. The discussion throughout is aimed at an audience of computer scientists with little background in quantum computation or in physics. Table of Contents: Acknowledgments / Introduction / Adiabatic Quantum Computation / Quantum Annealing / The D-Wave Platform / Computational Experience / Bibliography / Author's Biography
Author: William Cruz-Santos
Publisher: Morgan & Claypool Publishers
ISBN: 1627055576
Category : Science
Languages : en
Pages : 115
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Book Description
The adiabatic quantum computation (AQC) is based on the adiabatic theorem to approximate solutions of the Schrödinger equation. The design of an AQC algorithm involves the construction of a Hamiltonian that describes the behavior of the quantum system. This Hamiltonian is expressed as a linear interpolation of an initial Hamiltonian whose ground state is easy to compute, and a final Hamiltonian whose ground state corresponds to the solution of a given combinatorial optimization problem. The adiabatic theorem asserts that if the time evolution of a quantum system described by a Hamiltonian is large enough, then the system remains close to its ground state. An AQC algorithm uses the adiabatic theorem to approximate the ground state of the final Hamiltonian that corresponds to the solution of the given optimization problem. In this book, we investigate the computational simulation of AQC algorithms applied to the MAX-SAT problem. A symbolic analysis of the AQC solution is given in order to understand the involved computational complexity of AQC algorithms. This approach can be extended to other combinatorial optimization problems and can be used for the classical simulation of an AQC algorithm where a Hamiltonian problem is constructed. This construction requires the computation of a sparse matrix of dimension 2n × 2n, by means of tensor products, where n is the dimension of the quantum system. Also, a general scheme to design AQC algorithms is proposed, based on a natural correspondence between optimization Boolean variables and quantum bits. Combinatorial graph problems are in correspondence with pseudo-Boolean maps that are reduced in polynomial time to quadratic maps. Finally, the relation among NP-hard problems is investigated, as well as its logical representability, and is applied to the design of AQC algorithms. It is shown that every monadic second-order logic (MSOL) expression has associated pseudo-Boolean maps that can be obtained by expanding the given expression, and also can be reduced to quadratic forms. Table of Contents: Preface / Acknowledgments / Introduction / Approximability of NP-hard Problems / Adiabatic Quantum Computing / Efficient Hamiltonian Construction / AQC for Pseudo-Boolean Optimization / A General Strategy to Solve NP-Hard Problems / Conclusions / Bibliography / Authors' Biographies
Author: Puya Yao
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
"Minor-embedding is one of the fundamental concepts in adiabatic quantum computing when the hardware structure does not support arbitrary qubit interactions. In particular, when minimizing the energy of an Ising spin configuration, the corresponding graph must be minor-embedded into a Chimera graph [1]."--Page 1.
Author: Catherine McGeoch
Publisher: Frontiers Media SA
ISBN: 2832554369
Category : Science
Languages : en
Pages : 149
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Book Description
The past decade has seen four generations of quantum annealing processors, with qubit counts increasing from 512 on the D-Wave Two (released in 2013), to over 5000 on Advantage processors available in 2023. During this time, expanding access for researchers has sparked enormous growth in publications and in the body of knowledge surrounding capabilities, applications, and best practices in use of these novel computing systems. This Research Topic will invite submissions on all aspects of empirical experience with annealing-based quantum computers. The intention is to present a broad survey of the current state of knowledge about quantum annealing hardware, performance, software infrastructures, and applications.
Author: Michèle Weiland
Publisher: Springer
ISBN: 3030206564
Category : Computers
Languages : en
Pages : 352
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Book Description
This book constitutes the refereed proceedings of the 34th International Conference on High Performance Computing, ISC High Performance 2019, held in Frankfurt/Main, Germany, in June 2019. The 17 revised full papers presented were carefully reviewed and selected from 70 submissions. The papers cover a broad range of topics such as next-generation high performance components; exascale systems; extreme-scale applications; HPC and advanced environmental engineering projects; parallel ray tracing - visualization at its best; blockchain technology and cryptocurrency; parallel processing in life science; quantum computers/computing; what's new with cloud computing for HPC; parallel programming models for extreme-scale computing; workflow management; machine learning and big data analytics; and deep learning and HPC.
