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Bulletin of the American Physical Society

Compiler tools for hybrid quantum-classical algorithms

Peter J. Karalekas, Nikolas Tezak, Lauren Capelluto, Eric Peterson, Robert J. Smith, Mark Suska, Adam Mocarski, S.A. Brown, Celena Tanguay, Rodney Sinclair, Nima Taie-Nobarie, Chloe Song, Stefan Turkowski, Michael J. Rust, Glenn A Jones, Schuyler Fried, Diego Scarabelli, Deanna Abrams, Shane Caldwell, Colm A. Ryan, Prasahnt Sivarajah, William J. Zeng, Blake Johnson, Chad T. Rigetti

Published Mar 5, 2019• 0 citations
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Near term quantum devices have the potential to outperform classical computing through the use of hybrid classical-quantum algorithms such as Variational Quantum Eigensolvers. These iterative algorithms use a classical optimiser to update a parameterised quantum circuit. Each iteration, the circuit is executed on a physical quantum processor or quantum computing simulator, and the average measurement result is passed back to the classical optimiser. When many iterations are required, the whole quantum program is also recompiled many times. We have implemented explicit parameters that prevent recompilation of the whole program in the quantum programming framework OpenQL, called OpenQLPC. These parameters improve the compilation and therefore total runtime for hybrid quantum-classical algorithms. We compare the time required for compilation and simulation of the MAXCUT algorithm in OpenQLpcto the same algorithm in both PyQuil and Qiskit. We show that efficient handling of parameterised circuits results in up to 70 % reduction in total compilation time for the MAXCUT benchmark, and leads to a reduced total execution time. When using OpenQLPC, compilation of hybrid algorithms is up to two times faster than when using PyQuil or Qiskit.