Computational Complexity of Counting and Sampling

Computational Complexity of Counting and Sampling

Author: Istvan Miklos

Publisher: CRC Press

Published: 2019-02-21

Total Pages: 292

ISBN-13: 1351971603

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Computational Complexity of Counting and Sampling provides readers with comprehensive and detailed coverage of the subject of computational complexity. It is primarily geared toward researchers in enumerative combinatorics, discrete mathematics, and theoretical computer science. The book covers the following topics: Counting and sampling problems that are solvable in polynomial running time, including holographic algorithms; #P-complete counting problems; and approximation algorithms for counting and sampling. First, it opens with the basics, such as the theoretical computer science background and dynamic programming algorithms. Later, the book expands its scope to focus on advanced topics, like stochastic approximations of counting discrete mathematical objects and holographic algorithms. After finishing the book, readers will agree that the subject is well covered, as the book starts with the basics and gradually explores the more complex aspects of the topic. Features: Each chapter includes exercises and solutions Ideally written for researchers and scientists Covers all aspects of the topic, beginning with a solid introduction, before shifting to computational complexity’s more advanced features, with a focus on counting and sampling


Book Synopsis Computational Complexity of Counting and Sampling by : Istvan Miklos

Download or read book Computational Complexity of Counting and Sampling written by Istvan Miklos and published by CRC Press. This book was released on 2019-02-21 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Complexity of Counting and Sampling provides readers with comprehensive and detailed coverage of the subject of computational complexity. It is primarily geared toward researchers in enumerative combinatorics, discrete mathematics, and theoretical computer science. The book covers the following topics: Counting and sampling problems that are solvable in polynomial running time, including holographic algorithms; #P-complete counting problems; and approximation algorithms for counting and sampling. First, it opens with the basics, such as the theoretical computer science background and dynamic programming algorithms. Later, the book expands its scope to focus on advanced topics, like stochastic approximations of counting discrete mathematical objects and holographic algorithms. After finishing the book, readers will agree that the subject is well covered, as the book starts with the basics and gradually explores the more complex aspects of the topic. Features: Each chapter includes exercises and solutions Ideally written for researchers and scientists Covers all aspects of the topic, beginning with a solid introduction, before shifting to computational complexity’s more advanced features, with a focus on counting and sampling

Counting, Sampling and Integrating: Algorithms and Complexity

Counting, Sampling and Integrating: Algorithms and Complexity

Author: Mark Jerrum

Publisher: Birkhäuser

Published: 2012-12-06

Total Pages: 120

ISBN-13: 3034880057

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The subject of these notes is counting and related topics, viewed from a computational perspective. A major theme of the book is the idea of accumulating information about a set of combinatorial structures by performing a random walk on those structures. These notes will be of value not only to teachers of postgraduate courses on these topics, but also to established researchers. For the first time this body of knowledge has been brought together in a single volume.


Book Synopsis Counting, Sampling and Integrating: Algorithms and Complexity by : Mark Jerrum

Download or read book Counting, Sampling and Integrating: Algorithms and Complexity written by Mark Jerrum and published by Birkhäuser. This book was released on 2012-12-06 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: The subject of these notes is counting and related topics, viewed from a computational perspective. A major theme of the book is the idea of accumulating information about a set of combinatorial structures by performing a random walk on those structures. These notes will be of value not only to teachers of postgraduate courses on these topics, but also to established researchers. For the first time this body of knowledge has been brought together in a single volume.

Computational Complexity of Counting and Sampling

Computational Complexity of Counting and Sampling

Author: Istvan Miklos

Publisher: CRC Press

Published: 2019-02-21

Total Pages: 390

ISBN-13: 1351971611

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Computational Complexity of Counting and Sampling provides readers with comprehensive and detailed coverage of the subject of computational complexity. It is primarily geared toward researchers in enumerative combinatorics, discrete mathematics, and theoretical computer science. The book covers the following topics: Counting and sampling problems that are solvable in polynomial running time, including holographic algorithms; #P-complete counting problems; and approximation algorithms for counting and sampling. First, it opens with the basics, such as the theoretical computer science background and dynamic programming algorithms. Later, the book expands its scope to focus on advanced topics, like stochastic approximations of counting discrete mathematical objects and holographic algorithms. After finishing the book, readers will agree that the subject is well covered, as the book starts with the basics and gradually explores the more complex aspects of the topic. Features: Each chapter includes exercises and solutions Ideally written for researchers and scientists Covers all aspects of the topic, beginning with a solid introduction, before shifting to computational complexity’s more advanced features, with a focus on counting and sampling


Book Synopsis Computational Complexity of Counting and Sampling by : Istvan Miklos

Download or read book Computational Complexity of Counting and Sampling written by Istvan Miklos and published by CRC Press. This book was released on 2019-02-21 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Complexity of Counting and Sampling provides readers with comprehensive and detailed coverage of the subject of computational complexity. It is primarily geared toward researchers in enumerative combinatorics, discrete mathematics, and theoretical computer science. The book covers the following topics: Counting and sampling problems that are solvable in polynomial running time, including holographic algorithms; #P-complete counting problems; and approximation algorithms for counting and sampling. First, it opens with the basics, such as the theoretical computer science background and dynamic programming algorithms. Later, the book expands its scope to focus on advanced topics, like stochastic approximations of counting discrete mathematical objects and holographic algorithms. After finishing the book, readers will agree that the subject is well covered, as the book starts with the basics and gradually explores the more complex aspects of the topic. Features: Each chapter includes exercises and solutions Ideally written for researchers and scientists Covers all aspects of the topic, beginning with a solid introduction, before shifting to computational complexity’s more advanced features, with a focus on counting and sampling

Computational Complexity

Computational Complexity

Author: Sanjeev Arora

Publisher: Cambridge University Press

Published: 2009-04-20

Total Pages: 609

ISBN-13: 0521424267

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New and classical results in computational complexity, including interactive proofs, PCP, derandomization, and quantum computation. Ideal for graduate students.


Book Synopsis Computational Complexity by : Sanjeev Arora

Download or read book Computational Complexity written by Sanjeev Arora and published by Cambridge University Press. This book was released on 2009-04-20 with total page 609 pages. Available in PDF, EPUB and Kindle. Book excerpt: New and classical results in computational complexity, including interactive proofs, PCP, derandomization, and quantum computation. Ideal for graduate students.

Handbook of Satisfiability

Handbook of Satisfiability

Author: A. Biere

Publisher: IOS Press

Published: 2021-05-05

Total Pages: 1486

ISBN-13: 1643681613

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Propositional logic has been recognized throughout the centuries as one of the cornerstones of reasoning in philosophy and mathematics. Over time, its formalization into Boolean algebra was accompanied by the recognition that a wide range of combinatorial problems can be expressed as propositional satisfiability (SAT) problems. Because of this dual role, SAT developed into a mature, multi-faceted scientific discipline, and from the earliest days of computing a search was underway to discover how to solve SAT problems in an automated fashion. This book, the Handbook of Satisfiability, is the second, updated and revised edition of the book first published in 2009 under the same name. The handbook aims to capture the full breadth and depth of SAT and to bring together significant progress and advances in automated solving. Topics covered span practical and theoretical research on SAT and its applications and include search algorithms, heuristics, analysis of algorithms, hard instances, randomized formulae, problem encodings, industrial applications, solvers, simplifiers, tools, case studies and empirical results. SAT is interpreted in a broad sense, so as well as propositional satisfiability, there are chapters covering the domain of quantified Boolean formulae (QBF), constraints programming techniques (CSP) for word-level problems and their propositional encoding, and satisfiability modulo theories (SMT). An extensive bibliography completes each chapter. This second edition of the handbook will be of interest to researchers, graduate students, final-year undergraduates, and practitioners using or contributing to SAT, and will provide both an inspiration and a rich resource for their work. Edmund Clarke, 2007 ACM Turing Award Recipient: "SAT solving is a key technology for 21st century computer science." Donald Knuth, 1974 ACM Turing Award Recipient: "SAT is evidently a killer app, because it is key to the solution of so many other problems." Stephen Cook, 1982 ACM Turing Award Recipient: "The SAT problem is at the core of arguably the most fundamental question in computer science: What makes a problem hard?"


Book Synopsis Handbook of Satisfiability by : A. Biere

Download or read book Handbook of Satisfiability written by A. Biere and published by IOS Press. This book was released on 2021-05-05 with total page 1486 pages. Available in PDF, EPUB and Kindle. Book excerpt: Propositional logic has been recognized throughout the centuries as one of the cornerstones of reasoning in philosophy and mathematics. Over time, its formalization into Boolean algebra was accompanied by the recognition that a wide range of combinatorial problems can be expressed as propositional satisfiability (SAT) problems. Because of this dual role, SAT developed into a mature, multi-faceted scientific discipline, and from the earliest days of computing a search was underway to discover how to solve SAT problems in an automated fashion. This book, the Handbook of Satisfiability, is the second, updated and revised edition of the book first published in 2009 under the same name. The handbook aims to capture the full breadth and depth of SAT and to bring together significant progress and advances in automated solving. Topics covered span practical and theoretical research on SAT and its applications and include search algorithms, heuristics, analysis of algorithms, hard instances, randomized formulae, problem encodings, industrial applications, solvers, simplifiers, tools, case studies and empirical results. SAT is interpreted in a broad sense, so as well as propositional satisfiability, there are chapters covering the domain of quantified Boolean formulae (QBF), constraints programming techniques (CSP) for word-level problems and their propositional encoding, and satisfiability modulo theories (SMT). An extensive bibliography completes each chapter. This second edition of the handbook will be of interest to researchers, graduate students, final-year undergraduates, and practitioners using or contributing to SAT, and will provide both an inspiration and a rich resource for their work. Edmund Clarke, 2007 ACM Turing Award Recipient: "SAT solving is a key technology for 21st century computer science." Donald Knuth, 1974 ACM Turing Award Recipient: "SAT is evidently a killer app, because it is key to the solution of so many other problems." Stephen Cook, 1982 ACM Turing Award Recipient: "The SAT problem is at the core of arguably the most fundamental question in computer science: What makes a problem hard?"

Approximate Complexity in Statistical Mechanics

Approximate Complexity in Statistical Mechanics

Author: Tianyu Liu

Publisher:

Published: 2020

Total Pages: 159

ISBN-13:

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The six- and eight-vertex models originate in statistical mechanics for crystal lattices with hydrogen bonds. The first such model was introduced by Linus Pauling in 1935 to account for the residual entropy of water ice. The family of models not only are among the most extensively studied topics in physics, but also have fascinated chemists, mathematicians, theoretical computer scientists, and others, with thousands of papers studying their properties and connections to other fields. In this dissertation, we study the computational complexity of approximately counting and sampling in the six- and eight-vertex models on various classes of underlying graphs. First, we study the approximability of the partition function on general 4-regular graphs, classified according to the parameters of the models. Our complexity results conform to the phase transition phenomenon from physics due to the change in temperature. We introduce a quantum decomposition of the six- and eight-vertex models and prove a set of closure properties in various regions of the parameter space. These regions of the parameter space are concordant with the phase transition threshold. Using these closure properties, we derive polynomial time approximation algorithms via Markov chain Monte Carlo in some parameter space in the high temperature regime. In some other parameter space in the high temperature regime, we prove that the problem is (at least) as hard as approximately counting perfect matchings, a central open problem in this field. We also show that the six- and eight-vertex models are NP-hard to approximate in the whole low temperature regime on general 4-regular graphs. We then study the six- and eight-vertex models on more restricted classes of 4-regular graphs, including planar graphs and bipartite graphs. We give the first polynomial time approximation algorithm for the partition function in the low temperature regime on planar and on bipartite graphs. Our results show that the six- and eight-vertex models are the first problems with the provable property that while NP-hard to approximate on general graphs (even #P-hard for planar graphs in exact complexity), they possess efficient approximation schemes on both bipartite graphs and planar graphs in substantial regions of the parameter space. Finally, we study the square lattice six- and eight-vertex models. We prove that natural Markov chains for these models are mixing torpidly in the low temperature regime. Moreover, we give the first efficient approximate counting and sampling algorithms for the six- and the eight-vertex models on the square lattice at sufficiently low temperatures.


Book Synopsis Approximate Complexity in Statistical Mechanics by : Tianyu Liu

Download or read book Approximate Complexity in Statistical Mechanics written by Tianyu Liu and published by . This book was released on 2020 with total page 159 pages. Available in PDF, EPUB and Kindle. Book excerpt: The six- and eight-vertex models originate in statistical mechanics for crystal lattices with hydrogen bonds. The first such model was introduced by Linus Pauling in 1935 to account for the residual entropy of water ice. The family of models not only are among the most extensively studied topics in physics, but also have fascinated chemists, mathematicians, theoretical computer scientists, and others, with thousands of papers studying their properties and connections to other fields. In this dissertation, we study the computational complexity of approximately counting and sampling in the six- and eight-vertex models on various classes of underlying graphs. First, we study the approximability of the partition function on general 4-regular graphs, classified according to the parameters of the models. Our complexity results conform to the phase transition phenomenon from physics due to the change in temperature. We introduce a quantum decomposition of the six- and eight-vertex models and prove a set of closure properties in various regions of the parameter space. These regions of the parameter space are concordant with the phase transition threshold. Using these closure properties, we derive polynomial time approximation algorithms via Markov chain Monte Carlo in some parameter space in the high temperature regime. In some other parameter space in the high temperature regime, we prove that the problem is (at least) as hard as approximately counting perfect matchings, a central open problem in this field. We also show that the six- and eight-vertex models are NP-hard to approximate in the whole low temperature regime on general 4-regular graphs. We then study the six- and eight-vertex models on more restricted classes of 4-regular graphs, including planar graphs and bipartite graphs. We give the first polynomial time approximation algorithm for the partition function in the low temperature regime on planar and on bipartite graphs. Our results show that the six- and eight-vertex models are the first problems with the provable property that while NP-hard to approximate on general graphs (even #P-hard for planar graphs in exact complexity), they possess efficient approximation schemes on both bipartite graphs and planar graphs in substantial regions of the parameter space. Finally, we study the square lattice six- and eight-vertex models. We prove that natural Markov chains for these models are mixing torpidly in the low temperature regime. Moreover, we give the first efficient approximate counting and sampling algorithms for the six- and the eight-vertex models on the square lattice at sufficiently low temperatures.

Computational Complexity

Computational Complexity

Author: Oded Goldreich

Publisher: Cambridge University Press

Published: 2008-04-28

Total Pages: 632

ISBN-13: 9780521884730

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This book offers a comprehensive perspective to modern topics in complexity theory, which is a central field of the theoretical foundations of computer science. It addresses the looming question of what can be achieved within a limited amount of time with or without other limited natural computational resources. Can be used as an introduction for advanced undergraduate and graduate students as either a textbook or for self-study, or to experts, since it provides expositions of the various sub-areas of complexity theory such as hardness amplification, pseudorandomness and probabilistic proof systems.


Book Synopsis Computational Complexity by : Oded Goldreich

Download or read book Computational Complexity written by Oded Goldreich and published by Cambridge University Press. This book was released on 2008-04-28 with total page 632 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a comprehensive perspective to modern topics in complexity theory, which is a central field of the theoretical foundations of computer science. It addresses the looming question of what can be achieved within a limited amount of time with or without other limited natural computational resources. Can be used as an introduction for advanced undergraduate and graduate students as either a textbook or for self-study, or to experts, since it provides expositions of the various sub-areas of complexity theory such as hardness amplification, pseudorandomness and probabilistic proof systems.

Complexity Dichotomies for Counting Problems

Complexity Dichotomies for Counting Problems

Author: Jin-Yi Cai

Publisher: Cambridge University Press

Published: 2017-11-16

Total Pages: 473

ISBN-13: 1107062373

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Volume 1. Boolean domain


Book Synopsis Complexity Dichotomies for Counting Problems by : Jin-Yi Cai

Download or read book Complexity Dichotomies for Counting Problems written by Jin-Yi Cai and published by Cambridge University Press. This book was released on 2017-11-16 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: Volume 1. Boolean domain

Mathematics and Computation

Mathematics and Computation

Author: Avi Wigderson

Publisher: Princeton University Press

Published: 2019-10-29

Total Pages: 434

ISBN-13: 0691189137

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An introduction to computational complexity theory, its connections and interactions with mathematics, and its central role in the natural and social sciences, technology, and philosophy Mathematics and Computation provides a broad, conceptual overview of computational complexity theory—the mathematical study of efficient computation. With important practical applications to computer science and industry, computational complexity theory has evolved into a highly interdisciplinary field, with strong links to most mathematical areas and to a growing number of scientific endeavors. Avi Wigderson takes a sweeping survey of complexity theory, emphasizing the field’s insights and challenges. He explains the ideas and motivations leading to key models, notions, and results. In particular, he looks at algorithms and complexity, computations and proofs, randomness and interaction, quantum and arithmetic computation, and cryptography and learning, all as parts of a cohesive whole with numerous cross-influences. Wigderson illustrates the immense breadth of the field, its beauty and richness, and its diverse and growing interactions with other areas of mathematics. He ends with a comprehensive look at the theory of computation, its methodology and aspirations, and the unique and fundamental ways in which it has shaped and will further shape science, technology, and society. For further reading, an extensive bibliography is provided for all topics covered. Mathematics and Computation is useful for undergraduate and graduate students in mathematics, computer science, and related fields, as well as researchers and teachers in these fields. Many parts require little background, and serve as an invitation to newcomers seeking an introduction to the theory of computation. Comprehensive coverage of computational complexity theory, and beyond High-level, intuitive exposition, which brings conceptual clarity to this central and dynamic scientific discipline Historical accounts of the evolution and motivations of central concepts and models A broad view of the theory of computation's influence on science, technology, and society Extensive bibliography


Book Synopsis Mathematics and Computation by : Avi Wigderson

Download or read book Mathematics and Computation written by Avi Wigderson and published by Princeton University Press. This book was released on 2019-10-29 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to computational complexity theory, its connections and interactions with mathematics, and its central role in the natural and social sciences, technology, and philosophy Mathematics and Computation provides a broad, conceptual overview of computational complexity theory—the mathematical study of efficient computation. With important practical applications to computer science and industry, computational complexity theory has evolved into a highly interdisciplinary field, with strong links to most mathematical areas and to a growing number of scientific endeavors. Avi Wigderson takes a sweeping survey of complexity theory, emphasizing the field’s insights and challenges. He explains the ideas and motivations leading to key models, notions, and results. In particular, he looks at algorithms and complexity, computations and proofs, randomness and interaction, quantum and arithmetic computation, and cryptography and learning, all as parts of a cohesive whole with numerous cross-influences. Wigderson illustrates the immense breadth of the field, its beauty and richness, and its diverse and growing interactions with other areas of mathematics. He ends with a comprehensive look at the theory of computation, its methodology and aspirations, and the unique and fundamental ways in which it has shaped and will further shape science, technology, and society. For further reading, an extensive bibliography is provided for all topics covered. Mathematics and Computation is useful for undergraduate and graduate students in mathematics, computer science, and related fields, as well as researchers and teachers in these fields. Many parts require little background, and serve as an invitation to newcomers seeking an introduction to the theory of computation. Comprehensive coverage of computational complexity theory, and beyond High-level, intuitive exposition, which brings conceptual clarity to this central and dynamic scientific discipline Historical accounts of the evolution and motivations of central concepts and models A broad view of the theory of computation's influence on science, technology, and society Extensive bibliography

Computational Complexity

Computational Complexity

Author: Sanjeev Arora

Publisher: Cambridge University Press

Published: 2009-04-20

Total Pages: 519

ISBN-13: 1139477366

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This beginning graduate textbook describes both recent achievements and classical results of computational complexity theory. Requiring essentially no background apart from mathematical maturity, the book can be used as a reference for self-study for anyone interested in complexity, including physicists, mathematicians, and other scientists, as well as a textbook for a variety of courses and seminars. More than 300 exercises are included with a selected hint set. The book starts with a broad introduction to the field and progresses to advanced results. Contents include: definition of Turing machines and basic time and space complexity classes, probabilistic algorithms, interactive proofs, cryptography, quantum computation, lower bounds for concrete computational models (decision trees, communication complexity, constant depth, algebraic and monotone circuits, proof complexity), average-case complexity and hardness amplification, derandomization and pseudorandom constructions, and the PCP theorem.


Book Synopsis Computational Complexity by : Sanjeev Arora

Download or read book Computational Complexity written by Sanjeev Arora and published by Cambridge University Press. This book was released on 2009-04-20 with total page 519 pages. Available in PDF, EPUB and Kindle. Book excerpt: This beginning graduate textbook describes both recent achievements and classical results of computational complexity theory. Requiring essentially no background apart from mathematical maturity, the book can be used as a reference for self-study for anyone interested in complexity, including physicists, mathematicians, and other scientists, as well as a textbook for a variety of courses and seminars. More than 300 exercises are included with a selected hint set. The book starts with a broad introduction to the field and progresses to advanced results. Contents include: definition of Turing machines and basic time and space complexity classes, probabilistic algorithms, interactive proofs, cryptography, quantum computation, lower bounds for concrete computational models (decision trees, communication complexity, constant depth, algebraic and monotone circuits, proof complexity), average-case complexity and hardness amplification, derandomization and pseudorandom constructions, and the PCP theorem.