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Exploring Parameter Redundancy in the Unitary Coupled-Cluster Ansätze for Hybrid Variational Quantum Computing.
Shashank G Mehendale1, Bo Peng2, Niranjan Govind2
1Indian Institute of Science Education and Research (IISER), Kolkata, West Bengal 741246, India.
The Journal of Physical Chemistry. A
|May 16, 2023
Summary
This study reduces the number of parameters in unitary coupled-cluster (UCC) ansätze for quantum computing. Our approach enhances efficiency for near-term quantum devices by optimizing parameter redundancy in unitary coupled-cluster singles and doubles (UCCSD).
Area of Science:
- Quantum Computing
- Computational Chemistry
- Quantum Chemistry
Background:
- Unitary coupled-cluster (UCC) ansätze are common in variational quantum computing.
- Standard UCC ansätze face scaling challenges with system size, limiting their use on current quantum hardware.
Purpose of the Study:
- To explore parameter redundancy in preparing unitary coupled-cluster singles and doubles (UCCSD) ansätze.
- To develop more efficient UCC variants for variational quantum computing.
Main Methods:
- Employing spin-adapted formulation for UCCSD ansätze.
- Utilizing small amplitude filtration and entropy-based orbital selection.
- Investigating parameter redundancy in UCCSD preparation.
Main Results:
- Significant reduction in the number of parameters for UCCSD ansätze.
- Improved convergence time compared to conventional UCCSD-VQE simulations.
- Demonstrated cost reduction on small molecular systems.
Conclusions:
- The explored methods offer a more efficient approach to UCCSD ansätze.
- Potential for machine learning to further optimize parameter redundancy in quantum computing.
- Provides a pathway for practical application of UCC methods on near-term quantum devices.
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