  Quantum computers are expected to be highly beneficial for chemistry
simulations, promising significant improvements in accuracy and speed. The most
prominent algorithm for chemistry simulations on NISQ devices is the
Variational Quantum Eigensolver (VQE). It is a hybrid quantum-classical
algorithm which calculates the ground state energy of a Hamiltonian based on
parametrized quantum circuits, while a classical optimizer is used to find
optimal parameter values. However, quantum hardware is affected by noise, and
it needs to be understood to which extent it can degrade the performance of the
VQE algorithm. In this paper, we study the impact of noise on the example of
the hydrogen molecule. First, we compare the VQE performance for a set of
various optimizers, from which we find NFT to be the most suitable one. Next,
we quantify the effect of different noise sources by systematically increasing
their strength. The noise intensity is varied around values common to
superconducting devices of IBM Q, and curve fitting is used to model the
relationship between the obtained energy values and the noise magnitude. Since
the amount of noise in a circuit highly depends on its architecture, we perform
our studies for different ansatzes, including both hardware-efficient and
chemistry-inspired ones.
