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arXiv · 2605.25986

Training-Free Quantum Generative Paradigm via Local Parent Hamiltonians

Shu Tian·Jiaqi Hu·Rebing Wu·Yu Shi
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Abstract

We propose a training-free quantum generative paradigm, which is fundamentally different from current generative models, which demand substantial computational power, face practical scalability limits, and often function as opaque black boxes, despite their remarkable success. We enable image and text generation without parameter training, by constructing a local parent Hamiltonian whose ground state encodes the target distribution and then solving the global Hamiltonian. Rooted directly in quantum mechanical principles, this approach establishes a new pathway for generative modeling that leverages superposition and entanglement to maintain global consistency.

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Shu Tian, Jiaqi Hu, Rebing Wu, Yu Shi. 2026-05-25. Training-Free Quantum Generative Paradigm via Local Parent Hamiltonians. https://arxiv.org/abs/2605.25986

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