Quantum computation and quantum information
Quantum computation and quantum information
Evolutionary Approach to Quantum andReversible Circuits Synthesis
Artificial Intelligence Review
Irreversibility and heat generation in the computing process
IBM Journal of Research and Development
Multi-objective evolutionary algorithm based on adaptive discrete differential evolution
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Synthesis of reversible logic circuits
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Toffoli network synthesis with templates
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
An Algorithm for Synthesis of Reversible Logic Circuits
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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The reversible logic synthesis is a multi-objective optimization problem with rigorous constraints such as prohibiting the feedback and fan-out, and the same number of inputs and outputs, so it is difficult to be solved by general synthesis methods. Moreover, the synthesis methods of reversible logic circuits are very different from that of existing irreversible logic circuits. To make improvements in the capability and effectiveness of reversible logic synthesis, this paper proposes an algorithm of reversible logic gate-level evolutionary synthesis using multi-objective adaptive discrete differential evolution based on Pareto optimal. The synthesis experiments are conducted for a set of benchmark reversible logic circuits which are widely used in the reversible logic synthesis tests. The experiment results show that the proposed synthesis algorithm can give attention to multiple synthesis objectives at the same time, and has the capability to automatically synthesize the better reversible logic circuits, which verifies the feasibility and effectiveness of the proposed synthesis algorithm.