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arXiv · 2609.35163

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

Ju-Young Ryu·Wooyeong Song·Kwangil Bae·Wonhyuk Lee·Ilkwon Sohn
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Abstract

Quantum circuit Born machines (QCBMs) built with instantaneous quantum polynomial (IQP) circuits have loss functions that can be efficiently estimated classically, but require quantum computers during inference. Thus, classical computers can train large IQP QCBMs that exceed the qubit numbers of available quantum hardware. This motivates research into how qubit-limited quantum computers can be used to sample from larger IQP QCBMs. Leveraging insights from classical simulation of noisy IQP circuits, we propose a deployment protocol for IQP QCBMs that injects noise at the logical level to probabilistically decompose the original circuit into smaller clusters that can be sampled on qubit-limited quantum processors. We also apply lightweight resampling of known noisy qubits to mitigate the impact of the introduced error. Numerical simulations of our protocol applied to shallow IQP QCBMs and IBM Heron experiments deploying a 316-qubit IQP circuit onto 156-qubit hardware show that mitigation improves the similarity of the empirical distribution to the target distribution. The proposed deployment protocol also crucially preserves correlation structures more accurately than a classical baseline that has accurate single-qubit marginals.

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Ju-Young Ryu, Wooyeong Song, Kwangil Bae, Wonhyuk Lee, Ilkwon Sohn. 2026-09-28. Deployment of Large IQP Circuit Born Machines on Qubit-Limited Hardware Using Noise Injection. https://arxiv.org/abs/2609.35163

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