Efficient quantum state preparation through seniority driven operator selection.

Area of Science:

• Quantum Computing
• Computational Chemistry
• Strongly Correlated Systems

Background:

• Accurate electronic state representation is crucial for quantum algorithms, especially for strongly correlated systems.
• Existing methods face challenges in balancing chemical accuracy with gate efficiency and often require extensive pre-circuit measurements, leading to inefficiencies.
• The approximation of electronic wavefunctions for these systems remains a significant theoretical hurdle.

Purpose of the Study:

• To develop an algorithmic framework that efficiently captures molecular strong correlation.
• To minimize pre-circuit measurement overhead in quantum computations.
• To enhance the accuracy, robustness, and resource efficiency of quantum algorithms for strongly correlated systems on near-term quantum hardware.

Main Methods:

• Proposing a parameterized Ansatz using rank-one and seniority-zero paired excitations for shallow gate depth.
• Implementing selective pruning of excitations via a hybrid approach combining chemical insights and energy-sorting optimization.
• Incorporating qubit-based excitations through particle-preserving exchange circuits to reduce quantum complexities.

Main Results:

• The dynamic Ansatz significantly enhances computational efficiency for strongly correlated systems.
• The approach delivers exceptional accuracy and robustness, even in noisy quantum environments.
• Demonstrated reduction in quantum complexities and improved resource efficiency.

Conclusions:

• The proposed framework offers a synergistic solution to the challenges of chemical accuracy and gate efficiency in quantum computation.
• This method provides a viable pathway for accurate and efficient quantum simulations of strongly correlated systems.
• The dynamic Ansatz shows promise for practical applications on noisy, near-term quantum devices.