Author

Keisuke Fujii

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Open access Jul 2026

Qubit-efficient variational quantum optimization via Pauli correlation encoding: Application to large-scale power demand portfolio optimization

A qubit-efficient variational framework based on Pauli correlation encoding (PCE) is introduced and applied to electric power demand portfolio optimization, establishing PCE as a physically motivated and qubit-efficient framework for large-scale combinatorial optimization.

Takuya Yoshioka, Keita Sasada, Riku Usuki et al. · Physical Review Applied · 1 citation

#graph neural networks Preprint Sep 2026

Enhancing Pauli Correlation Encoding for quantum optimization via systematic expressivity analysis

A systematic analysis of expressivity and trainability of Pauli Correlation Encoding and a multistage continuation framework that gradually transforms a smooth relaxed objective into a sharper objective that more closely approximates the target discrete problem are proposed.

Riku Usuki, Don Arai, Ken N. Okada et al. · 0 citations

Preprint Jul 2026

Scalable Variational Quantum Optimization via Pauli Correlation Encoding: Application to Large-Scale Power Demand Portfolio Optimization

This work introduces a scalable variational framework based on Pauli correlation encoding (PCE) and applies it to electric power demand portfolio optimization, establishing PCE as a physically motivated and qubit-efficient framework for large-scale combinatorial optimization.

Takuya Yoshioka, Keita Sasada, Riku Usuki et al. · 1 citation