Automatic Quantum Computer Programming: A Genetic Programming Approach by Lee Spector

by Lee Spector

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. Quantum Gate and Measurement Emulator. 2. Visualization. 3. 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. 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. 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. QGAME Source Code. Index.

Genres: Computer Science

Paperback

First published June 11, 2004