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Preprint Oct 2026

Efficient Sampling for Many-Body Fermionic Non-Gaussianity

Fermionic non-Gaussianity is a key resource for universal quantum computation, and its behavior in quantum many-body systems has attracted growing interest. Recently, a convolution-based measure, which we call the magic R\'enyi entropy (MRE), has been proposed as a resource measure of non-Gaussianity, but its evaluatio...

Ryota Matsuda, Masahiro Hoshino, Y. Ashida · 0 citations
Preprint Oct 2026

Universal Bound and Phase Transition in Many-Body Fermionic Non-Gaussianity

Fermionic non-Gaussianity is a resource for universal quantum computation that can be generated by interactions in quantum many-body systems. Using the magic R\'enyi entropy (MRE) as a measure of non-Gaussianity, we derive its universal upper bound and Haar mean, proving that typical Haar-random states attain the maxim...

Masahiro Hoshino, Ryota Matsuda, Y. Ashida · 2 citations
Preprint Aug 2026

Renormalization Group Flow Matching for Scalable Local Generative Modeling

Despite their remarkable success in modeling complex data, generative models face a fundamental tradeoff. Global approaches can capture full structural coherence but suffer from high computational costs, while local models are efficient but often fail to reproduce long-range correlations and global coherence. The renor...

Kanta Masuki, Y. Ashida · 1 citation

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