Why are some problems easy to solve, while others seem nearly impossible? What can we compute with a given amount of time or memory, and what cannot be computed at all? How will quantum physics change the landscape of computation? This book gives a playful and accessible introduction to the deep ideas of theoretical computer science.
Why are some problems easy to solve, while others seem nearly impossible? What can we compute with a given amount of time or memory, and what cannot be computed at all? How will quantum physics change the landscape of computation? This book gives a playful and accessible introduction to the deep ideas of theoretical computer science.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Cristopher Moore graduated from Northwestern University with honors in 1986, at the age of 18, with a B.A. in Mathematics, Physics, and Integrated Science. He received his Ph.D. in Physics from Cornell University at the age of 23. After a postdoc at the Santa Fe Institute, he joined the faculty of the University of New Mexico, where he holds joint appointments in Computer Science and Physics and Astronomy. He has written over 90 papers, on topics ranging from undecidability in dynamical systems, to quantum computing, to phase transitions in NP-complete problems, to the analysis of social and biological networks. Stephan Mertens got his Diploma in Physics in 1989, and his Ph.D. in Physics in 1991, both from Georg-August University Göttingen. He holds scholarships from the "Studienstiftung des Deutschen Volkes", Germany's most prestigious organisation sponsoring the academically gifted. After his Ph.D. he worked for three years in the software industry before he joined the faculty of Otto-von-Guericke University Magdeburg as a theoretical physicist. His research focuses on disordered systems in statistical mechanics, average case complexity of algorithms, and parallel computing.
Inhaltsangabe
1: Prologue 2: The Basics 3: Insights and Algorithms 4: Needles in a Haystack: The class NP 5: Who is the Hardest One of All: NP-Completeness 6: The Deep Question: P vs. NP 7: Memory, Paths and games 8: Grand Unified Theory of Computation 9: Simply the Best: Optimization 10: The Power of Randomness 11: Random Walks and Rapid Mixing 12: Counting, Sampling, and Statistical Physics 13: When Formulas Freeze: Phase Transitions in Computation 14: Quantum Computing 15: Epilogue 16: Appendix: Mathematical Tools
1: Prologue 2: The Basics 3: Insights and Algorithms 4: Needles in a Haystack: The class NP 5: Who is the Hardest One of All: NP-Completeness 6: The Deep Question: P vs. NP 7: Memory, Paths and games 8: Grand Unified Theory of Computation 9: Simply the Best: Optimization 10: The Power of Randomness 11: Random Walks and Rapid Mixing 12: Counting, Sampling, and Statistical Physics 13: When Formulas Freeze: Phase Transitions in Computation 14: Quantum Computing 15: Epilogue 16: Appendix: Mathematical Tools
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