  Quantum chemistry applications on quantum computers currently rely heavily on
the variational quantum eigensolver (VQE) algorithm. This hybrid
quantum-classical algorithm aims at finding ground state solutions of molecular
systems based on the variational principle. VQE calculations can be
systematically implemented for perturbations to each molecular degree of
freedom, generating a Born-Oppenheimer potential energy surface (PES) for the
molecule. The PES can then be used to derive thermodynamic properties, which
are often desirable for applications in chemical engineering and materials
design. It is clear from this process that quantum chemistry applications
contain a substantial classical computing component in addition to steps that
can be performed using a quantum computer. In order to design efficient
work-flows that take full advantage of each hardware-type, it is critical to
consider the entire process so that the high-accuracy electronic energies
possible from quantum computing are not squandered in the process of
calculating thermodynamic properties. We present a summary of the hybrid
quantum-classical work-flow to compute thermodynamic properties. This work-flow
contains many options that can significantly affect the efficiency and the
accuracy of the results, including classical optimizer attributes, number of
ansatz repetitions, and how the vibrational Schroedinger equation is solved to
determine vibrational modes. We also analyze the effects of these options by
employing robust statistics along with simulations and experiments on actual
quantum hardware. We show that through careful selection of work-flow options,
nearly order-of-magnitude increases in accuracy are possible at equivalent
computing time.
