Improving the Accuracy of Variational Quantum Eigensolvers with Fewer Qubits Using Orbital Optimization.

Area of Science:

• Quantum computing
• Computational chemistry
• Electronic structure theory

Background:

• Near-term quantum computers have limitations in qubit count and circuit depth.
• Current quantum algorithms like the Variational Quantum Eigensolver (VQE) are restricted to small molecules and minimal basis sets due to these constraints.

Purpose of the Study:

• To propose and demonstrate an orbital optimization scheme integrated with quantum eigensolvers.
• The goal is to reduce the qubit requirements for electronic structure calculations on near-term quantum devices.

Main Methods:

• Incorporation of a parametrized partial unitary transformation applied to basis functions.
• Optimization of this transformation by minimizing the ground state energy with respect to the partial unitary matrix.
• Numerical simulations performed on small molecules up to 16 spin orbitals.

Main Results:

• The proposed orbital optimization scheme significantly extends the capabilities of near-term quantum computers for electronic structure problems.
• VQE combined with orbital optimization consistently yields lower ground state energies compared to traditional VQE using the same number of qubits.
• The method frequently achieves lower ground state energies than VQE approaches that utilize more qubits.

Conclusions:

• Orbital optimization is an effective strategy for mitigating qubit limitations in quantum eigensolvers.
• This approach enhances the accuracy and feasibility of quantum electronic structure calculations on current quantum hardware.
• The method shows promise for tackling more complex molecular systems in the future.