Quantum Annealer Eigensolver (QAE) is an algorithm that finds the smallest eigenvalues and eigenvectors of a real symmetric matrix on a quantum annealer device. The method is based on the variational principle where the expansion coefficients of the wave function (magnitudes) are discretized using a finite number of qubits. The only parameter which is optimized classically is the normalization penalty. Specifically for D-Wave quantum annealers, one more parameter, a chain penalty, is also determined classically to ensure all-to-all connectivity between qubits. Once the ground state is computed, spectral transformations are applied to compute the exited states. Multidimensional problems are treated with direct-product basis sets, which currently makes the algorithm scale exponentially with the number of degrees of freedom. The approach was successfully applied to the calculation of vibrational spectra of two molecules O2 and O3 (see Fig. 1). We found that unsatisfactory performance of annealer is caused by the hardware noise, whereas a simulation on a classical computer was two to three orders of magnitude more accurate. Optimal basis sets (particularly for O3) and matrix elements are generated on a supercomputer and serve as an input for quantum computation. Currently, we are applying QAE to electronic structure calculations. This work demonstrates how two completely different types of computation, adiabatic quantum computing and high-performance computing, perfectly synergize their efforts in solving fundamental chemistry problems.

Quantum Annealer Eigensolver (QAE): Combining quantum computing with high-performance computing to solve fundamental chemistry problems

Macromolecular Chemistry: The Second Century

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ACS Spring 2020 National Meeting & Expo

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