A fundamentally quantum model of computation based on quantum entanglement and quantum measurement is called one-way quantum computation model (1WQC). Computations are shown by measurement patterns (or simply patterns) in this model where an initial highly entangled sta More
A fundamentally quantum model of computation based on quantum entanglement and quantum measurement is called one-way quantum computation model (1WQC). Computations are shown by measurement patterns (or simply patterns) in this model where an initial highly entangled state called a graph state is used to perform universal quantum computations. This graph together with the set of its input and output qubits is called the geometry of the pattern. Moreover, some optimization techniques have been introduced to simplify patterns.
Previously, the 1WQC model has been applied to optimize quantum circuits. An approach for parallelizing quantum circuits has been proposed which takes a quantum circuit and then produces the corresponding pattern after performing the proposed optimization techniques for this model. Then it translates the optimized 1WQC patterns back to quantum circuits to parallelize the initial quantum circuit by using a set of rewriting rules.
To improve previous works, in this paper, a new automatic approach is proposed to optimize patterns based on their geometries instead of using rewriting rules by applying optimization techniques simultaneously. Moreover, the optimized pattern is translated back to a quantum circuit and then this circuit is simplified by decreasing the number of auxiliary qubits. Results show that the quantum circuit cost metrics of the proposed approach is improved as compared to the previous ones.
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