University of the Ryukyus · Faculty of Engineering · 准教授

Research keywords脳模倣型量子計算・量子ニューラルネットワーク・断熱的量子計算・ホップフィールドネットワーク・ジョセフソン接合・マクロスコピック量子トンネル効果

Research fieldsNano/Microsystems・ナノ材料科学・半導体、光物性、原子物理・Information network・薄膜、表面界面物性・Computer system

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• Learning Rule for a Quantum Neural Network Inspired by Hebbian Learning2021 · <p>Utilizing the enormous potential of quantum computers requires new and practical quantum algorithms. Motivated by the success of machine learning, we investigate the fusion of neural and quantum computing, and propose a learning method for a quantum neural network inspired by the Hebb rule. Based on an analogy between neuron-neuron interactions and qubit-qubit interactions, the proposed quantum learning rule successfully changes the coupling strengths between qubits according to training data. To evaluate the effectiveness and practical use of the method, we apply it to the memorization process of a neuro-inspired quantum associative memory model. Our numerical simulation results indicate that the proposed quantum versions of the Hebb and anti-Hebb rules improve the learning performance. Furthermore, we confirm that the probability of retrieving a target pattern from multiple learned patterns is sufficiently high.</p>
• Islanding operation scheme for DC microgrid utilizing pseudo Droop control of photovoltaic system2020 · Matayoshi H.
• A real distribution network voltage regulation incorporating auto-tap-changer pole transformer multiobjective optimization2019 · Danish S.M.S.
• Optimal scheduling method of controllable loads in smart home considering Re-forecast and Re-plan for uncertainties2019 · Yoza A.

• デコヒーレンス効果を利用した脳模倣型量子計算アルゴリズムに関する研究2006 · 若手研究(B)
• 脳模倣型量子計算アルゴリズムエミュレータに関する研究若手研究(B)

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