Deployment of Large IQP Circuit Born Machines on Qubit-Limited Hardware Using Noise Injection

arXiv:2609.35163 · quant-ph · Submitted 2026-09-28 · Read on arXiv

quant-ph

Submitted: 2026-09-28

Updated: 2026-09-28

Terminology

• Quantum Circuits — 6× in this paper · explained in 2 episodes
• Consistency — 5× in this paper · explained in 3 episodes
• Generative Model — 5× in this paper · explained in 2 episodes
• Loss Function — 5× in this paper · explained in 2 episodes
• Fine-Tuning — 4× in this paper · explained in 5 episodes
• Generative Models — 4× in this paper · explained in 2 episodes
• Self-consistency — 4× in this paper · explained in 2 episodes
• Generative Modeling — 3× in this paper · explained in 3 episodes
• Calibration — 2× in this paper · explained in 7 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Bayesian Optimization — 1× in this paper · explained in 3 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Entanglement — 1× in this paper · explained in 3 episodes
• Transferability — 1× in this paper · explained in 4 episodes

Sources

• Train on classical, deploy on quantum: scaling generative quantum machine learning to a thousand qubits
• IQPopt: Fast optimization of instantaneous quantum polynomial circuits in JAX
• Universality and kernel-adaptive training for classically trained, quantum-deployed generative models
• Weak distillation of quantum resources
• Simulating quantum computers with probabilistic methods
• IQP Born Machines under Data-dependent and Agnostic Initialization Strategies
• A Quantum Approximate Optimization Algorithm
• The Quantum Approximate Optimization Algorithm at High Depth for MaxCut on Large-Girth Regular Graphs and the Sherrington-Kirkpatrick Model
• Universality of Classically Trainable, Quantum-Deployed Boson-Sampling Generative Models
• PennyLane: Automatic differentiation of hybrid quantum-classical computations

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