  Adaptive construction of ansatz circuits offers a promising route towards
applicable variational quantum eigensolvers on near-term quantum hardware.
Those algorithms aim to build up optimal circuits for a certain problem and
ansatz circuits are adaptively constructed by selecting and adding entanglers
from a predefined pool. In this work, we propose a way to construct entangler
pools with reduced size by leveraging classical algorithms. Our method uses
mutual information between the qubits in classically approximated ground state
to rank and screen the entanglers. The density matrix renormalization group
method is employed for classical precomputation in this work. We corroborate
our method numerically on small molecules. Our numerical experiments show that
a reduced entangler pool with a small portion of the original entangler pool
can achieve same numerical accuracy. We believe that our method paves a new way
for adaptive construction of ansatz circuits for variational quantum
algorithms.
