Abstract
Quantum-dot Cellular Automata (QCA) has emerged as a new design paradigm for nanotechnologies. Since the operational logic in QCA is the majority logic, much research about the synthesis and optimization of majority logic has been proposed recently. In this thesis, we propose an optimization method by merging nodes in the Majority-Inverter-Graph, which is the representation of majority logic circuits. Instead of using satisfiability solvers, our approach can identify the node mergers by using logic implications for circuit size reduction. The experimental results show that for a set of EPFL benchmarks, our approach can minimize the node count by 21% when integrated with the state-of-the-art on average.