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FQsun: A Configurable Wave Function-Based Quantum Emulator for Power-Efficient Quantum Simulations
arXiv
Authors: Tuan Hai Vu, Vu Trung Duong Le, Hoai Luan Pham, Quoc Chuong Nguyen, Yasuhiko Nakashima
Year
2024
Paper ID
37079
Status
Preprint
Abstract Read
~2 min
Abstract Words
199
Citations
N/A
Abstract
Quantum computers are promising powerful computers for solving complex problems, but access to real quantum hardware remains limited due to high costs. Although the software simulators on CPUs/GPUs such as Qiskit, ProjectQ, and Qsun offer flexibility and support for many qubits, they struggle with high power consumption and limited processing speed, especially as qubit counts scale. Accordingly, quantum emulators implemented on dedicated hardware, such as FPGAs and analog circuits, offer a promising path for addressing energy efficiency concerns. However, existing studies on hardware-based emulators still face challenges in terms of limited flexibility and lack of fidelity evaluation. To overcome these gaps, we propose FQsun, a quantum emulator that enhances performance by integrating four key innovations: efficient memory organization, a configurable Quantum Gate Unit (QGU), optimized scheduling, and multiple number precisions. Five FQsun versions with different number precisions are implemented on the Xilinx ZCU102, consuming a maximum power of 2.41W. Experimental results demonstrate high fidelity, low mean square error, and high normalized gate speed, particularly with 32-bit versions, establishing FQsun's capability as a precise quantum emulator. Benchmarking on famous quantum algorithms reveals that FQsun achieves a superior power-delay product, outperforming software simulators on CPUs in the processing speed range.
Why This Paper Matters
- This paper contributes to the Quantum Simulation research area in the Quantum Articles archive.
- It adds a 2024 reference point for readers tracking recent quantum research.
- Quantum computers are promising powerful computers for solving complex problems, but access to real quantum hardware remains limited due to high costs.
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