Quantum chemistry as a benchmark for near-term quantum computers

Abstract

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.

Practical quantum computation of chemical and nuclear energy levels using quantum imaginary time evolution and Lanczos algorithms

“…Thus far, the variational quantum eigensolver has proved to be one of the most useful applications for these devices. Variational methods have been used to solve problems in chemistry, nuclear physics, quantum field theory, high-energy physics, and others [2][3][4][5][6][7][8] . While these smallscale applications show promise for using NISQ devices to sample from distributions and calculate expectation values, short coherence times make calculations involving time evolution exceedingly difficult on NISQ devices.…”

Orbital optimized unitary coupled cluster theory for quantum computer

“…The parameters of the circuit are iteratively tuned by a nonlinear optimizer running on a classical computer to minimize the energy. VQE calculations using actual quantum computers have already been performed for small molecules [16,[18][19][20][21][22][23]. Recently, researchers have proposed electron-correlation methods based on UCC for quantum computers [24][25][26][27][28][29][30][31][32][33].…”

Unfolding quantum computer readout noise

“…Furthermore, current QIS methods have pathologies that can be avoided with techniques from HEP. In particular, the most popular quantum simulators pyQuil 33 (by Rigetti), Cirq 34,35 (by Google), and XACC [36][37][38] implement a version of matrix inversion, and the other popular simulator Qiskit by IBM 39,40 uses a least squares method (see also refs. 41,42 ) that is the same as the matrix inversion solution when the the latter is nonnegative.…”