Automatic Quantum Computer Programming provides an introduction to quantum computing for non-physicists, as well as an introduction 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. Source code for the authorbs QGAME quantum computer simulator is included as an appendix, and pointers to additional online resources furnish the reader with an array of tools for automatic quantum computer programming.

Automatic Quantum Computer Programming provides an introduction to quantum computing for non-physicists, as well as an introduction 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. Source code for the author's QGAME quantum computer simulator is included as an appendix, and pointers to additional online resources furnish the reader with an array of tools for automatic quantum computer programming.
TOC:Preface.- 1: The Power of Quantum Computing.- 2: Quantum Computer Simulation.- 3: Quantum Computer Programming.- 4: Genetic and Evolutionary Computation.- 5: Genetic Programming.- 6: Evolution of Complex Programs.- 7: Evolution of Quantum Programs.- 8: Evolved Quantum Programs.- 9: Conclusions and Prospects.- Appendices: QGAME Source Code.- Index.

Preface. 1: The Power of Quantum Computing. 1. What is Quantum Computing? 2. Possibilities Count. 3. The Role of Automatic Programming. 2: Quantum Computer Simulation. 1. Bits, Qubits and Gates. 2. Gate-Level Simulation. 3: Quantum Computer Programming. 1. QGAME: Quantum Gate and Measurement Emulator. 2. Visualization. 3. Example: Grover's Database Search Algorithm. 4: Genetic and Evolutionary Computation. 1. What Is Genetic and Evolutionary Computation? 2. Genetic Algorithms. 3. Scalability via Parallelism. 4. Applicability of Genetic and Evolutionary Computation. 5: Genetic Programming. 1. Programming by Genetic Algorithm. 2. Traditional Program Representations. 3. Traditional Genetic Operators. 4. Example: Symbolic Regression. 5. Obtaining Genetic Programming Results. 6: Evolution of Complex Programs. 1. Types, Modules and Development. 2. The Push Programming Language. 3. Push Examples. 4. PshGP: Genetic Programming with Push. 5. Autoconstructive Evolution. 7: Evolution of Quantum Programs. 1. Program Representations. 2. Fitness. 3. Operators and Refinements. 8: Evolved Quantum Programs. 1. The 1-Bit Deutsch-Jozsa Problem. 2. Grover's Database Search Problem. 3. Scaling Majority-ON. 4. The OR and AND/OR Problems. 5. Gate Communication Problems. 6. Significance of These Results. 9: Conclusions and Prospects. Appendices: QGAME Source Code. Index.

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)