From the reviews:
"I thoroughly enjoyed this book. It not only introduces quantum computing, but also genetic programming and the author's original genetic programming system "PushGP" which is used to evolve the quantum algorithms discussed in later chapters. The book is comprehensive, with wonderfully clear illustrations and comes with a Lisp-based quantum simulator program. Truly recommended for readers interested in gaining knowledge about exciting frontiers of computer science."
(Wolfgang Banzhaf)
"The book is very well written. Readers with some background in both genetic programming and quantum computing will be able to read it rapidly. … Scientific readers with a general interest in exploring automatic quantum programming, will also like this book. … I have really enjoyed reading this book, it will certainly become a reference book for GP researchers interested to apply genetic programming to search for quantum programs." (Michel Toulouse, Genetic Programming and Evolvable Machines, Vol. 7, 2006)
--This text refers to the Hardcover edition.
Product Description
The potential of large-scale quantum computers, once realized, promises to radically transform computer science. Despite large-scale international efforts, however, essential questions about the potential of quantum algorithms are still unanswered. The application of automatic programming technologies, particularly genetic programming techniques, has produced several new quantum algorithms. These methods will help to guide theoretical work on both the power and limits of quantum computing, and lead to the discovery of new solutions to practical problems using quantum computers.
Automatic Quantum Computer Programming is an introduction both to quantum computing for non-physicists and to genetic programming for non-computer-scientists. The book explores several ways in which genetic programming can support automatic quantum computer programming and presents detailed descriptions of specific techniques, along with several examples of their human-competitive performance on specific problems.
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