Quantum Resource Estimation for Quantum Chemistry Algorithms

Predicting the quantum resources for potential applications such as quantum chemistry plays a key role in the future development of quantum computers, and a systematic approach based on a reliable metric is needed for efficient resource estimation. In this work, we developed a Python software package QRE (Quantum Resource Estimator) for estimating quantum resources required to compute the properties of molecules. We define the key requirements for the quantum phase estimation (QPE) algorithm for molecules with different basis sets. We estimated the number of ancilla qubits, circuit depth, and time to solution. The input for QRE is the information about a molecule such as atom types, molecular geometries, charges, basis set, and level of theory. Also, we consider an error analysis scheme for QPE algorithm to calculate the number of ancilla qubits. As a part of the estimation, we calculate the number of rotation and CNOT gates for one Trotter step. Based on these results, the QRE program calculates costs for full QPE algorithms for the given gate time, fidelities of CNOT gates, and target success probability. It is expected that our work will contribute to a better understanding of the limitations of current and future quantum computers for quantum chemistry applications.