Benchmarking Quantum Simulators: Comparative Analysis of Quantum Network Protocols Across Six Frameworks

Abstract

Quantum networking protocol advancement heavily relies on classical simulation for algorithm design, validation, and optimization before deployment on quantum hardware. However, selecting the quantum computing framework significantly influences simulation performance memory utilization, and productivity. This research paper renders a systematic performance analysis of quantum computing simulators for network protocol implementation across six important quantum frameworks: Qiskit, CirQ, Amazon Braket SDK, PyQuil, Q#, and PennyLane. We have evaluated it by implementing nine fundamental networking protocols, conducting 1,620 simulation executions with N = 30 trials per measurement under both ideal and noisy conditions. We have observed significant performance disparities: PyQuil accomplishes 405× faster total execution than Qiskit with 1,237× lower peak memory consumption, whereas Q# demonstrates comparable speed using JIT compilation. while using real depolarizing noise (p=0.001) all frameworks exhibit 0.1–1.0% teleportation fidelity degradation.