Quantum Circuit Simulation

1 Introduction. 1.1 Quantum Circuits. 1.2 Quantum Simulation. 1.3 Book. 2 Gate Modeling and Circuit Simulation. 2.1 Classical Digital Circuits. 2.2 Simulation with Binary Decision Diagrams. 2.3 Sequential Circuits and Synchronization. 2.4 Summary. 3 Linear Algebra and Quantum Mechanics. 3.1 Linear Algebra. 3.2 Quantum Mechanics. 3.3 Summary. 4 Quantum Information Processing. 4.1 Quantum Gates. 4.2 Quantum Circuits. 4.3 Synchronization of Quantum Circuits. 4.4 Sample Algorithms. 4.5 Summary. 5 Special Case: Simulating Stabilizer Circuits. 5.1 Basics of a Quantum Circuit Simulator. 5.2 Stabilizer States, Gates and Circuits. 5.3 Data structures. 5.4 Algorithms. 5.5 Summary. 6 Generic Circuit Simulation Techniques. 6.1 Qubit-wise Multiplication. 6.2 P-blocked Simulation. 6.3 Tensor Networks. 6.4 Slightly-entangled Simulation. 6.5 Summary. 7 State-Vector Simulation with Decision Diagrams. 7.1 Quantum Information Decision Diagrams. 7.2 Scalability of QuIDD-based Simulation. 7.3 Empirical Validation. 7.4 Related Decision Diagrams. 7.5 Summary. 8 Density-Matrix Simulation with QuIDDs. 8.1 QuIDD Properties and Density Matrices. 8.2 QuIDD-based Outer Product. 8.3 QuIDD-based Partial Trace. 8.4 Empirical Validation. 8.5 Summary. 9 Checking Equivalence of States and Circuits. 9.1 Quantum Equivalence Checking. 9.2 Global-Phase Equivalence. 9.3 Relative-Phase Equivalence. 9.4 Empirical Validation. 9.5 Summary. 10 Improving QuIDD-based Simulation. 10.1 Gate Algorithms. 10.2 Dynamic Tensor Products and Partial Tracing. 10.3 Empirical Validation. 10.4 Summary. 11 Closing Remarks. A QuIDDPro Simulator. A.1 Running the Simulator. A.2 Functions and Code in Multiple Files. A.3 Language Reference. B QuIDDPro Examples. B.1 Well-known Quantum States. B.2 Grover's Search Algorithm. B.3 Shor's Integer Factoring Algorithm. References. Index.

George Viamontes has a Ph.D. in Computer Science and Enginering from the University of Michigan where his research was focused on quantum circuit simulation.  Through a Department of Energy fellowship for high-performance computer science, he completed a portion of his graduate research at Los Alamos National Laboratory.  Upon graduation, Dr. Viamontes spent a year at Lockheed Martin Advanced Technology Laboratories where he continued to work on quantum circuit simulation.  Currently he develops and implements algorithms for high-frequency automated trading and continues to consult for Lockheed Martin on quantum computing projects.

Igor L. Markov is an associate professor of Electrical Engineering and Computer Science at the University of Michigan. He received his Ph.D. in Computer Science from UCLA. Currently he is a member of the Executive Board of ACM SIGDA, Editorial Board member of Communications of ACM, ACM TODAES, IEEE Transactions on Computers, IEEE Transactions on CAD, as well as IEEE Design & Test. Prof. Markov researches computers that make computers. He has co-authored two books and more than 160 refereed publications, some of which were honored by the best-paper awards at the Design Automation and Test in Europe Conference (DATE), the Int'l Symposium on Physical Design (ISPD) and IEEE Trans. on Computer-Aided Design. Prof. Markov is the recipient of a DAC Fellowship, an ACM SIGDA Outstanding New Faculty award, an NSF CAREER award, an IBM Partnership Award, and a Microsoft A. Richard Newton Breakthrough Research Award.

John P. Hayes received the B.E. degree from the National University of Ireland, Dublin, and the M.S. and Ph.D. degrees from the University of Illinois, Urbana-Champaign, all in electrical engineering. While at the University of Illinois, he participated in the design of the ILLIAC III computer. In 1970 he joined the Operations Research Group at the Shell Benelux Computing Center