Standalone FPGA-Based QAOA Emulator for Weighted-MaxCut on Embedded Devices
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866909554286002176 |
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| author | Choi, Seonghyun Lee, Kyeongwon Lee, Jae-Jin Lee, Woojoo |
| author_facet | Choi, Seonghyun Lee, Kyeongwon Lee, Jae-Jin Lee, Woojoo |
| contents | Quantum computing QC emulation is crucial for advancing QC applications, especially given the scalability constraints of current devices. FPGA-based designs offer an efficient and scalable alternative to traditional large-scale platforms, but most are tightly integrated with high-performance systems, limiting their use in mobile and edge environments. This study introduces a compact, standalone FPGA-based QC emulator designed for embedded systems, leveraging the Quantum Approximate Optimization Algorithm (QAOA) to solve the Weighted-MaxCut problem. By restructuring QAOA operations for hardware compatibility, the proposed design reduces time complexity from O(N^2) to O(N), where N equals 2^n for n qubits. This reduction, coupled with a pipeline architecture, significantly minimizes resource consumption, enabling support for up to nine qubits on mid-tier FPGAs, roughly three times more than comparable designs. Additionally, the emulator achieved energy savings ranging from 1.53 times for two-qubit configurations to up to 852 times for nine-qubit configurations, compared to software-based QAOA on embedded processors. These results highlight the practical scalability and resource efficiency of the proposed design, providing a robust foundation for QC emulation in resource-constrained edge devices. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_11316 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Standalone FPGA-Based QAOA Emulator for Weighted-MaxCut on Embedded Devices Choi, Seonghyun Lee, Kyeongwon Lee, Jae-Jin Lee, Woojoo Emerging Technologies Quantum Physics Quantum computing QC emulation is crucial for advancing QC applications, especially given the scalability constraints of current devices. FPGA-based designs offer an efficient and scalable alternative to traditional large-scale platforms, but most are tightly integrated with high-performance systems, limiting their use in mobile and edge environments. This study introduces a compact, standalone FPGA-based QC emulator designed for embedded systems, leveraging the Quantum Approximate Optimization Algorithm (QAOA) to solve the Weighted-MaxCut problem. By restructuring QAOA operations for hardware compatibility, the proposed design reduces time complexity from O(N^2) to O(N), where N equals 2^n for n qubits. This reduction, coupled with a pipeline architecture, significantly minimizes resource consumption, enabling support for up to nine qubits on mid-tier FPGAs, roughly three times more than comparable designs. Additionally, the emulator achieved energy savings ranging from 1.53 times for two-qubit configurations to up to 852 times for nine-qubit configurations, compared to software-based QAOA on embedded processors. These results highlight the practical scalability and resource efficiency of the proposed design, providing a robust foundation for QC emulation in resource-constrained edge devices. |
| title | Standalone FPGA-Based QAOA Emulator for Weighted-MaxCut on Embedded Devices |
| topic | Emerging Technologies Quantum Physics |
| url | https://arxiv.org/abs/2502.11316 |