Approximate degree in classical and quantum computing
著者
書誌事項
Approximate degree in classical and quantum computing
(Foundations and trends in theoretical computer science, 15:3-4)
now Publishers, c2023
- : pbk
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注記
Includes bibliographical references (p. 189-201)
内容説明・目次
内容説明
The ability (or inability) to represent or approximate Boolean functions by polynomials is a central concept in complexity theory, underlying interactive and probabilistically checkable proof systems, circuit lower bounds, quantum complexity theory, and more. In this book, the authors survey what is known about a particularly natural notion of approximation by polynomials, capturing pointwise approximation over.
This book covers recent progress on proving approximate degree lower and upper bounds and describes some applications of the new bounds to oracle separations, quantum query and communication complexity, and circuit complexity. The authors explain how several of these advances have been unlocked by a particularly simple and elegant technique, called dual block composition, for constructing solutions to this dual linear program. They also provide concise coverage of even more recent lower bound techniques based on a new complexity measure called spectral sensitivity. Finally, they show how explicit constructions of approximating polynomials have been inspired by quantum query algorithms.
This book provides a comprehensive review of the foundational and recent developments of an important topic in both classical and quantum computing. The reader has a considerable body of knowledge condensed in an accessible form to quickly understand the principles and further their own research.
目次
1. Introduction
2. Preliminaries
3. General Upper Bound Techniques
4. Polynomials from Query Algorithms
5. Lower Bounds by Symmetrization
6. The Method of Dual Polynomials
7. Dual Lower Bounds for Block-Composed Functions
8. Beyond Block-Composed Functions
9. Spectral Sensitivity
10. Approximate Rank Lower Bounds from Approximate Degree
11. Assorted Applications
Acknowledgements
References
「Nielsen BookData」 より