@techreport{oai:ipsj.ixsq.nii.ac.jp:00210570,
 author = {Hiroshi, Horii and Jun, Doi and Hiroshi, Horii and Jun, Doi},
 issue = {23},
 month = {Mar},
 note = {Memory to simulate quantum computing is exponentially increased based on qubits of a circuit and the entire memory is updated for simulation of each gate in a circuit to be simulated. For example, 32 GB memory is necessary to represent all the probability amplitudes with double-precision and all of them is updated for each gate. Aggregating multiple gates into a single unitary-matrix gate reduces load and store of memory. However, if an aggregated gate updates many qubits, memory access and calculation of intermediate state of matrix multiplication can become the bottleneck. We propose a method to efficiently aggregate gates with pattern-matchings, greedy algorithms, and a graph algorithm. Our gate fusion reduced gates of various quantum circuits of Qiskit and improved performance of their simulation., Memory to simulate quantum computing is exponentially increased based on qubits of a circuit and the entire memory is updated for simulation of each gate in a circuit to be simulated. For example, 32 GB memory is necessary to represent all the probability amplitudes with double-precision and all of them is updated for each gate. Aggregating multiple gates into a single unitary-matrix gate reduces load and store of memory. However, if an aggregated gate updates many qubits, memory access and calculation of intermediate state of matrix multiplication can become the bottleneck. We propose a method to efficiently aggregate gates with pattern-matchings, greedy algorithms, and a graph algorithm. Our gate fusion reduced gates of various quantum circuits of Qiskit and improved performance of their simulation.},
 title = {Optimization of Quantum Computing Simulation with Gate Fusion},
 year = {2021}
}