Benchmarking hybrid digitized-counterdiabatic quantum optimization
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866909162881941504 |
|---|---|
| author | Xu, Ruoqian Tang, Jialiang Chandarana, Pranav Paul, Koushik Xu, Xusheng Yung, Manhong Chen, Xi |
| author_facet | Xu, Ruoqian Tang, Jialiang Chandarana, Pranav Paul, Koushik Xu, Xusheng Yung, Manhong Chen, Xi |
| contents | Hybrid digitized-counterdiabatic quantum computing (DCQC) is a promising approach for leveraging the capabilities of near-term quantum computers, utilizing parameterized quantum circuits designed with counterdiabatic protocols. However, the classical aspect of this approach has received limited attention. In this study, we systematically analyze the convergence behavior and solution quality of various classical optimizers when used in conjunction with the digitized-counterdiabatic approach. We demonstrate the effectiveness of this hybrid algorithm by comparing its performance to the traditional QAOA on systems containing up to 28 qubits. Furthermore, we employ principal component analysis to investigate the cost landscape and explore the crucial influence of parameterization on the performance of the counterdiabatic ansatz. Our findings indicate that fewer iterations are required when local cost landscape minima are present, and the SPSA-based BFGS optimizer emerges as a standout choice for the hybrid DCQC paradigm. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_09849 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Benchmarking hybrid digitized-counterdiabatic quantum optimization Xu, Ruoqian Tang, Jialiang Chandarana, Pranav Paul, Koushik Xu, Xusheng Yung, Manhong Chen, Xi Quantum Physics Hybrid digitized-counterdiabatic quantum computing (DCQC) is a promising approach for leveraging the capabilities of near-term quantum computers, utilizing parameterized quantum circuits designed with counterdiabatic protocols. However, the classical aspect of this approach has received limited attention. In this study, we systematically analyze the convergence behavior and solution quality of various classical optimizers when used in conjunction with the digitized-counterdiabatic approach. We demonstrate the effectiveness of this hybrid algorithm by comparing its performance to the traditional QAOA on systems containing up to 28 qubits. Furthermore, we employ principal component analysis to investigate the cost landscape and explore the crucial influence of parameterization on the performance of the counterdiabatic ansatz. Our findings indicate that fewer iterations are required when local cost landscape minima are present, and the SPSA-based BFGS optimizer emerges as a standout choice for the hybrid DCQC paradigm. |
| title | Benchmarking hybrid digitized-counterdiabatic quantum optimization |
| topic | Quantum Physics |
| url | https://arxiv.org/abs/2401.09849 |