Multiscale Embedding for Quantum Computing.

Area of Science:

• Computational Chemistry
• Quantum Computing
• Molecular Simulation

Background:

• Simulating large chemical and biological systems is computationally demanding.
• Existing methods face limitations on quantum devices and classical computers with limited memory.

Purpose of the Study:

• To present a novel multiscale embedding scheme for large-scale molecular simulations.
• To enable efficient calculations on limited quantum and classical computing resources.

Main Methods:

• A multiscale embedding scheme linking QM/MM and bootstrap embedding (BE).
• A mixed-basis BE scheme for extended systems on classical computers.
• Benchmark calculations to validate the approach.

Main Results:

• The combined strategies allow simulations of large chemical systems on limited quantum devices.
• The mixed-basis BE scheme facilitates calculations on classical computers with limited memory.
• Benchmark data confirm the robustness and accuracy of the approach for realistic systems.

Conclusions:

• The developed multiscale BE scheme is a robust and cost-effective method for attaining correlation energies.
• Future quantum computing advancements will further improve accuracy.
• This approach bridges the gap between computational cost and accuracy for complex systems.