Circuit-Depth Reduction of Unitary-Coupled-Cluster Ansatz by Energy Sorting.

Area of Science:

• Quantum Computing
• Quantum Chemistry
• Computational Science

Background:

• Quantum computation offers a novel approach for complex quantum chemistry problems.
• Current noisy intermediate-scale quantum (NISQ) devices have limited resources, posing challenges for large-scale quantum algorithms.
• Variational quantum eigensolver (VQE) algorithms often utilize unitary coupled cluster (UCC) based ansatzes.

Purpose of the Study:

• To significantly reduce the circuit depth of unitary coupled cluster (UCC) and UCC-based ansatzes within the variational quantum eigensolver (VQE) algorithm.
• To address the limitations of current NISQ devices for quantum chemistry applications.
• To develop a more efficient quantum algorithm for calculating molecular and periodic system energies.

Main Methods:

• An energy-sorting strategy was developed to prescreen excitation operators based on their energy contribution.
• Quantum circuit ansatzes were iteratively constructed using selected operators until energy convergence.
• The method was applied to both molecular and periodic systems.

Main Results:

• A substantial reduction in circuit depth was achieved, with 50%-98% fewer operators required.
• The accuracy of the original Unitary Coupled Cluster Singles Doubles (UCCSD) operator pools was maintained.
• The strategy proved effective for molecular and periodic systems.

Conclusions:

• The energy-sorting strategy offers a significant improvement in the efficiency of quantum algorithms for quantum chemistry.
• This method effectively reduces the resource requirements for VQE algorithms on NISQ devices.
• The approach is generalizable to other parametric variational ansatzes in quantum computation.