3 papers
quant-ph2025
Fair sampling of ground-state configurations using hybrid quantum-classical MCMC algorithms
Yuichiro Nakano, Keisuke Fujii
We study the fair sampling properties of hybrid quantum-classical Markov chain Monte Carlo (MCMC) algorithms for combinatorial optimization problems with degenerate ground states.…
quant-ph2025
Electric Power Demand Portfolio Optimization by Fermionic QAOA with Self-Consistent Local Field Modulation
Takuya Yoshioka, Keita Sasada, Yuichiro Nakano +1
Quantum Approximation Optimization Algorithms (QAOA) have been actively developed, among which Fermionic QAOA (FQAOA) has been successfully applied to financial portfolio optimizat…
quant-ph2025
Optimal elemental configuration search in crystal using quantum approximate optimization algorithm
Kazuhide Ichikawa, Genta Hayashi, Satoru Ohuchi +3
Optimal elemental configuration search in crystal is a crucial task to discovering industrially important materials such as lithium-ion battery cathodes. In this paper we present a…