SOURCE-LINKED INTELLIGENCE

Quantum MeanFlow: single-shot generative sampling on NISQ hardware

arXiv · AI, language, vision and robotics · article · Sep 2, 2026 · UTC

Quantum generative models offer a promising framework for exploring whether quantum computation can enhance generative machine learning. Flow matching is a generative method in which samples are generated by transporting a simple, known distribution to the target data distribution with a learned velocity field. Its quantum counterpart, known as quantum flow matching (QFM), was introduced recently, and, like its classical counterpart, requires integrating an ordinary differential equation over many time steps during inference. As each step requires the output from the previous step, the circuit

Read original source ↗ Open in workspace

recordType

paper

region

Global