Kavli Affiliate: Jing Wang
| First 5 Authors: Tianrui Zou, Yuan Fang, Jing Wang, Menghan Dou, Jun Fu
| Summary:
In emerging quantum-classical integration applications, the classical time
cost-especially from compilation and protocol-level communication often exceeds
the execution time of quantum circuits themselves, posing a severe bottleneck
to practical deployment. To overcome these limitations, QPanda3 has been
extensively optimized as a high-performance quantum programming framework
tailored for the demands of the NISQ era and quantum-classical hybrid
workflows. It features optimized circuit compilation, a custom binary
instruction stream (OriginBIS), and hardware-aware execution strategies to
significantly reduce latency and communication overhead. OriginBIS achieves up
to 86.9$times$ faster encoding and 35.6$times$ faster decoding than OpenQASM
2.0, addressing critical bottlenecks in hybrid quantum systems. Benchmarks show
10.7$times$ compilation speedup and up to 597$times$ acceleration in
compiling large-scale circuits (e.g., a 118-qubit W-state) compared to Qiskit.
n high-performance simulation, QPanda3 excels in variational quantum
algorithms, achieving up to 26$times$ faster gradient computation than Qiskit,
with minimal time-complexity growth across circuit depths. These capabilities
make QPanda3 well-suited for scalable quantum algorithm development in finance,
materials science, and combinatorial optimization, while supporting industrial
deployment and cloud-based execution in quantum-classical hybrid computing
scenarios.
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