Polynomial-Time Algorithms for Prime Factorization and Discrete Logarithms on a Quantum Computer
SIAM Journal on Computing
Feynman and computation: exploring the limits of computers
Feynman and computation: exploring the limits of computers
Branching programs and binary decision diagrams: theory and applications
Branching programs and binary decision diagrams: theory and applications
Quantum computation and quantum information
Quantum computation and quantum information
Algebric Decision Diagrams and Their Applications
Formal Methods in System Design
Improving Gate-Level Simulation of Quantum Circuits
Quantum Information Processing
Gate-level simulation of quantum circuits
ASP-DAC '03 Proceedings of the 2003 Asia and South Pacific Design Automation Conference
Improving quantum circuit dependability with reconfigurable quantum gate arrays
Proceedings of the 2nd conference on Computing frontiers
A dependability perspective on emerging technologies
Proceedings of the 3rd conference on Computing frontiers
Design for dependability in emerging technologies
ACM Journal on Emerging Technologies in Computing Systems (JETC)
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Simulating quantum computation on a classical computer is a difficult problem. The matrices representing quantum gates, and vectors modeling qubit states grow exponentially with the number of qubits. It has been shown experimentally that the QuIDD (Quantum Information Decision Diagram) datastructure greatly facilitates simulations using memory and runtime that are polynomial in the number of qubits. In this paper, we present a complexity analysis which formally describes this class of matrices and vectors. We also present an improved implementation of QuIDDs which can simulate Grover's algorithm for quantum search with the asymptotic runtime complexity of an ideal quantum computer up to negligible overhead.