4 citations · 10 across the 5 of their papers we have counts for
5 papers
Feedback-based quantum optimization and its classical counterpart: quantum advantage and the power of classical algorithms
Tomohiro Hattori, Takuya Hatomura
Feedback-based quantum optimization is a quantum approach to combinatorial optimization. In this paper, we introduce the classical counterpart of feedback-based quantum optimizatio…
Frustration-enhanced quantum annealing correction models with additional inter-replica interactions
Tomohiro Hattori, Shu Tanaka
Quantum annealing correction (QAC) models provide a promising approach for mitigating errors in quantum annealers. Previous studies have established that QAC models are crucial for…
Improving the efficiency of quantum annealing with controlled diagonal catalysts
Tomohiro Hattori, Shu Tanaka
Quantum annealing is a promising algorithm for solving combinatorial optimization problems. It searches for the ground state of the Ising model, which corresponds to the optimal so…
Impact of Fixing Spins in a Quantum Annealer with Energy Rescaling
Tomohiro Hattori, Hirotaka Irie, Tadashi Kadowaki +1
Quantum annealing is a promising algorithm for solving combinatorial optimization problems. However, various hardware restrictions significantly impede its efficient performance. S…
Advantages of fixing spins in quantum annealing
Tomohiro Hattori, Hirotaka Irie, Tadashi Kadowaki +1
Quantum annealing can efficiently obtain solutions to combinatorial optimization problems. Size-reduction methods are used to treat large-scale combinatorial optimization problems…