iSOMA swarm intelligence algorithm in synthesis of quantum computing circuits

In the present paper, we demonstrate the possibilities of designing quantum computing circuits using a specific swarm intelligence algorithm — iSOMA in the form of three experiments. All simulations are based on a simple sample of a quantum computing circuit from the Qiskit environment, which was used as a comparison circuit with the results of the three experiments already mentioned. In the first experiment, we try to find an arbitrary functional solution using iSOMA with minimal constraints on this circuit’s design. It can be said that in this experiment, iSOMA showed the highest degree of “creativity”. In the second experiment, we focused on whether iSOMA can be used to find a circuit identical to the one designed by a human or equivalent with the positions of the measurement gates fixed. In the last experiment, we highlight iSOMA’s ability to avoid unnecessary qubit usage by adding redundant qubits to a possible circuit and fixing the measurement gates to the last two qubits in the scheme. In all three experiments, we see that iSOMA can find efficient functional and often astonishing solutions — the proposed method applied to a classical circuit founded a new one preserving required properties while saving one ancilla (redundant, useless, non-used)11https://en.wikipedia.org/wiki/Ancilla_bit. qubit. All computations are implemented in the IBM Qiskit22https://qiskit.org/learn/. environment. Although these are relatively simple experiments, the results show that evolutionary algorithms can successfully design more complex quantum circuits. [Display omitted] •Quantum circuit (QC) design by swarm intelligence.•A practical showcase in Python and IBM Qiskit environment.•3 experiments demonstrating evolutionary algorithms performance in QC design.•Design of unusual QC topology saving one ancilla qubit.