Efficient quantum gate decomposition via adaptive circuit compression

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In this work, we report on a novel quantum gate approximation algorithm based on the application of parametric two-qubit gates in the synthesis process.

• The utilization of these parametric two-qubit gates in the circuit design allows us to transform the discrete combinatorial problem of circuit synthesis into an optimization problem over continuous variables.
• The circuit is then compressed by a sequential removal of two-qubit gates from the design, while the remaining building blocks are continuously adapted to the reduced gate structure by iterated learning cycles.
• We implemented the developed algorithm in the SQUANDER software package and benchmarked it against several state-of-the-art quantum gate synthesis tools.