Multi-target quantum compilation algorithm
Abstract Quantum compilation is the process of converting a target unitary operation into a trainable unitary represented by a quantum circuit. It has a wide range of applications, including gate optimization, quantum-assisted compiling, quantum state preparation, and quantum dynamic simulation. Traditional quantum compilation usually optimizes circuits for a single target. However, many quantum systems require simultaneous optimization of multiple targets, such as thermal state preparation, time-dependent dynamic simulation, and others. To address this, we develop a multi-target quantum compilation algorithm to improve the performance and flexibility of simulating multiple quantum systems. Our benchmarks and case studies demonstrate the effectiveness of the algorithm, highlighting the importance of multi-target optimization in advancing quantum computing. This work lays the groundwork for further development and evaluation of multi-target quantum compilation algorithms.
Authors
- Thu-Uyen Nguyen (ORCID: https://orcid.org/0009-0009-2260-4271)
- Van-Nhan Nguyen (ORCID: https://orcid.org/0000-0002-0321-9425)
- Lan Nguyen Tran (ORCID: https://orcid.org/0000-0003-2649-2122)
- Vu Tuan Hai (ORCID: https://orcid.org/0000-0002-2293-0968)
- Le Bin Ho (ORCID: https://orcid.org/0000-0002-8816-4450)
- Jesus Urbaneja
Institutions
- FPT University (VN)
- Vietnam National University Ho Chi Minh City (VN)
- Tohoku University (JP)
- Nara Institute of Science and Technology (JP)
Publication Details
- Journal
- Machine Learning Science and Technology
- Published
- 2024-11-25
- DOI
- https://doi.org/10.1088/2632-2153/ad9705
- Primary Topic
- Quantum Computing Algorithms and Architecture
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Japan Society for the Promotion of Science