Quantum computation and quantum information
Quantum computation and quantum information
Reducing Quantum Computations to Elementary Unitary Operations
Computing in Science and Engineering
A transformation based algorithm for reversible logic synthesis
Proceedings of the 40th annual Design Automation Conference
Synthesis of reversible logic circuits
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Quadratic Form Expansions for Unitaries
Theory of Quantum Computation, Communication, and Cryptography
Efficient Reversible Logic Design of BCD Subtractors
Transactions on Computational Science III
BDD-based synthesis of reversible logic for large functions
Proceedings of the 46th Annual Design Automation Conference
Universal test sets for reversible circuits
COCOON'10 Proceedings of the 16th annual international conference on Computing and combinatorics
Synthesis and optimization of reversible circuits—a survey
ACM Computing Surveys (CSUR)
BDD-Based Synthesis of Reversible Logic
International Journal of Applied Metaheuristic Computing
Line ordering of reversible circuits for linear nearest neighbor realization
Quantum Information Processing
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In this paper we consider circuit synthesis for n-wire linear reversible circuits using the C-NOT gate library. These circuits are an important class of reversible circuits with applications to quantum computation. Previous algorithms, based on Gaussian elimination and LU-decomposition, yield circuits with O(n2) gates in the worst-case. However, an information theoretic bound suggests that it may be possible to reduce this to as few as O(n2/log n) gates. We give an algorithm that is optimal up to a multiplicative constant, and Θ(log n) times faster than previous methods. While our results are primarily asymptotic, simulation results show that even for relatively small n our algorithm is faster and yields smaller circuits than the standard method. The proposed algorithm has direct applications to the synthesis of stabilizer circuits, an important class of quantum circuits. Generically our algorithm can be interpreted as a matrix decomposition algorithm, yielding an asymptotically efficient decomposition of a binary matrix into a product of elementary matrices.