Qubit Count Reduction by Orthogonally Constrained Orbital Optimization for Variational Quantum Excited-State Solvers

Area of Science:

• Quantum Computing
• Computational Chemistry
• Electronic Structure Theory

Background:

• Accurate calculation of electronic excited states is crucial for understanding molecular properties and reactions.
• Near-term quantum computers present opportunities for advancing computational chemistry, but require efficient algorithms.

Purpose of the Study:

• To propose a novel state-averaged orbital optimization scheme for enhancing the accuracy of excited states on quantum computers.
• To develop a method that overcomes limitations of conventional orbital optimization techniques.

Main Methods:

• Parameterization of orbital rotation as a general partial unitary matrix.
• Optimization of state-averaged energy using an orthogonally constrained gradient projection method without expansion approximations.

Main Results:

• The proposed method achieves higher accuracy than fixed basis Full CI (FCI) for molecular systems.
• Demonstrated significant qubit reduction, e.g., matching FCI accuracy for H2 with 14 qubits instead of 56.

Conclusions:

• The state-averaged orbital optimization scheme offers a more accurate and resource-efficient approach for excited state calculations on quantum hardware.
• This method shows promise for advancing quantum chemistry simulations.