Quantum Computation and Quantum Error Prevention
Just to remind everyone -- THIS IS UNDER CONSTRUCTION!
Table of Contents
Main
- Chapter 1 - Introduction
- Chapter 2 - Qubits and Collections of Qubits
- Chapter 3 - Physics of Quantum Information
- Chapter 4 - Entanglement
- Chapter 5 - Quantum Information: Basic Principles and Simple Examples
- Chapter 6 - Quantum Computation
- Quantum Computation Basics
- Deutsch-Josza Algorithm
- Simon’s Algorithm
- Shor’s Algorithm
- Grover’s Algorithm
- Chapter 7 - Experiments
- Chapter 8 - Noise in Quantum Systems
- Operator-Sum Decomposition
- Sudarshan Representation
- Superoperators: (more or less) Standard representation
- Notes
- Chapter 9 - Conclusions
- What have we learned?
Appendices
- Appendix A - Basic Probability Concepts
- Appendix B - Complex Numbers
- Appendix C - Vectors and Linear Algebra
- Appendix D - Group Theory
- Introduction
- Definitions and Examples
- Comparing Groups: Homomorphisms and Isomorphisms
- Infinite Order Groups: Lie Groups
- Appendix E - Density Operator: Extensions
- The Coherence Vector/Polarization Vector
- The Polarization Vector: Other Conventions
- The Density Matrix for Two Qubits
- Appendix F - NOTES and CREDITS
Index
Bibliography
Preface
These are notes to accompany the course on quantum computing taught at Southern Illinois University. Until otherwise noted these notes are a work in progress. Therefore, if there are any suggestions, questions, comments, errors, etc. please let me know so that appropriate modifications can be made.
There are several good books on quantum computing. This is not an attempt to displace them or replace them. The concentration on error prevention and noise is likely different than what has been done before and the desire is to have them rather self-contained so that few, if any, other resources are absolutely required. However, it is strongly recommended that other resources are consulted along with these notes since they are unlikely to be a complete resource any time soon. Furthermore, the are not likely to be a better resource for many topics which are better and more thoroughly treated elsewhere.
The objective to provide course material which will be introductory enough to enable an undergraduate science major with some background in linear algebra to follow the course. This includes physics, mathematics, computer science, and engineering majors. A good place to start is N. David Mermin’s book [11].
N. David Mermin’s book [11], David J. Giffiths’s book [8], and (of course) Michael Nielsen and Isaac Chuang’s book [13] have all greatly influenced these notes. They have influenced many parts even if they are not explicitly cited. In the case of Griffiths’s book, I taught an undergraduate quantum mechanics course the semester before I taught this course. Therefore many of the examples, pedagogy, and exposition were influenced by his book, which I very much appreciate.
Much of this material is based upon work supported by the National Science Foundation under Grant No. 0545798. However, any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.