01948nas a2200205   4500000000100000000000100001008004100002260001200043100002400055700002100079700002000100700001800120700002200138700002400160245011400184856006500298490000700363520135800370022001401728       2021                            d  c08/20211 aIsmail Ghodsollahee1 aZohreh Davarzani1 aMariam Zomorodi1 aPawel Plawiak1 aMonireh Houshmand1 aMahboobeh Houshmand00aConnectivity matrix model of quantum circuits and its application to distributed quantum circuit optimization  uhttps://link.springer.com/article/10.1007/s11128-021-03170-50 v203 a<p>As quantum computation grows, the number of qubits involved in a given quantum computer increases. But due to the physical limitations in the number of qubits of a single quantum device, the computation should be performed in a distributed system. In this paper, a new model of quantum computation based on the matrix representation of quantum circuits is proposed. Then, using this model, we propose a novel approach for reducing the number of teleportations in a distributed quantum circuit. The proposed method consists of two phases: the pre-processing phase and the optimization phase. In the pre-processing phase, it considers the bi-partitioning of quantum circuits by Non-Dominated Sorting Genetic Algorithm (NSGA-III) to minimize the number of global gates and to distribute the quantum circuit into two balanced parts with equal number of qubits and minimum number of global gates. In the optimization phase, two heuristics named Heuristic I and Heuristic II are proposed to optimize the number of teleportations according to the partitioning obtained from the pre-processing phase. Finally, the proposed approach is evaluated on many benchmark quantum circuits. The results of these evaluations show an average of 22.16% improvement in the teleportation cost of the proposed approach compared to the existing works in the literature.</p>
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