Quantum Generative Adversarial Network (QGAN) Benchmark
Quantum Generative Adversarial Network (QGAN) · Machine-learning · 8 qubits · Qiskit Machine Learning, PennyLane
Benchmark for quantum generative adversarial networks that learn probability distributions and load them into quantum states. Through the interplay of quantum channels and classical neural networks, QGANs achieve polynomial gate complexity for distribution loading. Implementations on IBM Quantum hardware demonstrate competitive image generation on MNIST and Fashion-MNIST, with the MosaiQ framework achieving significant improvements in Frechet Inception Distance scores.
Benchmark for quantum generative adversarial networks that learn probability distributions and load them into quantum states. Through the interplay of quantum channels and classical neural networks, QGANs achieve polynomial gate complexity for distribution loading. Implementations on IBM Quantum hardware demonstrate competitive image generation on MNIST and Fashion-MNIST, with the MosaiQ framework achieving significant improvements in Frechet Inception Distance scores.
Demonstrates that quantum generative models can achieve polynomial gate complexity for distribution loading, a potential exponential advantage over classical methods.
IBM Quantum, simulators
Qiskit Machine Learning, PennyLane