Towards near-term quantum simulation of materials.

Area of Science:

• Quantum computing
• Materials science
• Computational chemistry

Background:

• Quantum computers offer promising applications for determining material properties.
• Current quantum hardware limitations include high circuit depths and qubit numbers, hindering complex simulations.
• Simulating materials on near-term quantum devices remains a significant challenge.

Purpose of the Study:

• To develop a novel quantum algorithm for reducing the computational cost of material simulations.
• To improve the efficiency of quantum algorithms for calculating ground and excited state properties of materials.
• To address the limitations of current quantum hardware for materials science applications.

Main Methods:

• Development of a quantum algorithm incorporating localized material Hamiltonians in the Wannier basis.
• Implementation of a hybrid fermion-to-qubit mapping technique.
• Utilizing an efficient quantum circuit compiler to optimize simulation parameters.

Main Results:

• Achieved a circuit depth improvement of up to 6 orders of magnitude for simulating the transition-metal oxide SrVO₃.
• Demonstrated a quantum circuit design with depth independent of system size by leveraging material Hamiltonian locality.
• Showcased significant reduction in estimated costs for quantum material simulations.

Conclusions:

• The developed quantum algorithm offers a pathway to more feasible materials simulations on near-term quantum hardware.
• Realistic simulations of specific material properties may be achievable without fully scalable, fault-tolerant quantum computers.
• Integrating materials understanding into quantum algorithm design is crucial for advancing quantum simulations in materials science.