Shortcut to chemically accurate quantum computing via density-based basis-set correction.

Area of Science:

• Quantum Computing
• Computational Chemistry
• Materials Science

Background:

• Accurate quantum chemistry calculations are essential for molecular modeling but demand significant computational resources.
• Current quantum processors have limited qubit capabilities, posing a challenge for complex chemical simulations.
• Minimizing quantum resources while maintaining quantitative accuracy is crucial for advancing quantum computing applications.

Purpose of the Study:

• To develop a method for obtaining quantitative quantum chemistry results using limited quantum resources.
• To accelerate the convergence towards the complete-basis-set limit in quantum computations.
• To enable accurate molecular simulations for applications in drug design and materials science.

Main Methods:

• Embedding a quantum computing ansatz into density-functional theory using GPU-accelerated state-vector emulation.
• Applying density-based basis-set corrections to adapt basis sets to specific systems and qubit budgets.
• Utilizing an on-the-fly basis set crafting approach coupled with variational ansätze.

Main Results:

• Achieved quantitative quantum chemistry results with reduced qubit requirements.
• Demonstrated accelerated basis-set convergence, improving electronic densities and ground-state energies.
• Showcased improved first-order properties, such as dipole moments, and potential as a classical energy correction.

Conclusions:

• The proposed method offers a shortcut to chemically accurate quantum computations.
• This approach enhances the efficiency of quantum chemistry simulations on current quantum hardware.
• The technique has potential applications in drug design and materials science by enabling more accurate molecular modeling.