Quantum Chemistry as a Benchmark for Near-Term Quantum Computers
We present a quantum chemistry benchmark for noisy intermediate-scale quantum
computers that leverages the variational quantum eigensolver, active space
reduction, a reduced unitary coupled cluster ansatz, and reduced density
purification as error mitigation. We demonstrate this benchmark on the 20 qubit
IBM Tokyo and 16 qubit Rigetti Aspen processors via the simulation of alkali
metal hydrides (NaH, KH, RbH),with accuracy of the computed ground state energy
serving as the primary benchmark metric. We further parameterize this benchmark
suite on the trial circuit type, the level of symmetry reduction, and error
mitigation strategies. Our results demonstrate the characteristically high
noise level present in near-term superconducting hardware, but provide a
relevant baseline for future improvement of the underlying hardware, and a
means for comparison across near-term hardware types. We also demonstrate how
to reduce the noise in post processing with specific error mitigation
techniques. Particularly, the adaptation of McWeeny purification of noisy
density matrices dramatically improves accuracy of quantum computations, which,
along with adjustable active space, significantly extends the range of
accessible molecular systems. We demonstrate that for specific benchmark
settings, the accuracy metric can reach chemical accuracy when computing over
the cloud on certain quantum computers.
Alexander J. McCaskey Zachary P. Parks Jacek Jakowski Shirley V. Moore T. Morris Travis S. Humble Raphael C. Pooser