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Even though many neurochips have been developed and investigated, the best suitable way for implementation has not been known clearly. Our approach is to exploit stochastic logic for various operations required for neural functions. The advantage of stochastic logic is that complex operations can be implemented with a few ordinary logic gates. On the other hand, the operation speed is not so fast since stochastic logic requires certain accumulation time for averaging. However, a huge integration can be achieved and its reliability is high because all of operations are done on digital circuits. Furthermore, we propose a nonmonotonic neuron realized by stochastic logic, since the nonmonotonic property is efficient for the performance enhancement in association and learning. In this paper, we show the circuit design and measurement results of a neurochip comprising 50 neurons are shown. The advantages of nonmonotonic and stochastic properties are shown clearly.

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We investigated macroscopic quantum tunneling (MQT) of Bi2Sr2CaCu2Oy intrinsic Josephson junctions (IJJs) for two device structures. One is a small mesa, which is a few nanometers thick with only two or three IJJs, and the other is a stack of a few hundred IJJs in a narrow bridge structure. The experimental results regarding the switching current distribution for the first switch from the zero-voltage state were in good agreement with the conventional theory for a single Josephson junction, indicating that the crossover temperature from thermal activation to the MQT regime for the former device structure was similar to that for the latter device structure. Together with the observation of multiphoton transitions between quantized energy levels in the MQT regime, these results strongly suggest that the observed MQT behavior is intrinsic to a single IJJ in high-Tc cuprates and is independent of the device structure. The switching current distribution for the second switch from the first resistive state, which was carefully distinguished from the first switch, was also compared with respect to the two device structures. In spite of the differences between the heat transfer environments, the second switch exhibited a similar temperature-independent behavior for both devices up to a much higher temperature than the crossover temperature for the first switch. We argue that this cannot be explained in terms of self-heating caused by dissipative currents after the first switch. As possible candidates for this phenomenon, the MQT process for the second switch and the effective increase of the electronic temperature due to the quasiparticle injection are discussed.

SUMMARY There is increasing interest in quantum computing, because of its enormous computing potential. A small number of powerful quantum algorithms have been proposed to date; however, the development of new quantum algorithms for practical use remains essential. Parallel computing with a neural network has successfully realized certain unique functions such as learning and recognition; therefore, the introduction of certain neural computing techniques into quantum computing to enlarge the quantum computing application field is worthwhile. In this paper, a novel quantum associative memory (QuAM) is proposed, which is achieved with a quantum neural network by employing adiabatic Hamiltonian evolution. The memorization and retrieval procedures are inspired by the concept of associative memory realized with an artificial neural network. To study the detailed dynamics of our QuAM, we examine two types of Hamiltonians for pattern memorization. The first is a Hamiltonian having diagonal elements, which is known as an Ising Hamiltonian and which is similar to the cost function of a Hopfield network. The second is a Hamiltonian having non-diagonal elements, which is known as a neuro-inspired Hamiltonian and which is based on interactions between qubits. Numerical simulations indicate that the proposed methods for pattern memorization and retrieval work well with both types of Hamiltonians. Further, both Hamiltonians yield almost identical performance, although their retrieval properties differ. The QuAM exhibits new and unique features, such as a large memory capacity, which differs from a conventional neural associative memory. key words: associative memory, quantum computing, adiabatic Hamiltonian evolution, neural network

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A number of studies realized operation of power systems are unstable in developing countries due to misconfiguration of distribution systems, limited power transfer capability, inconsistency of renewable resources integration, paucity of control and protection measures, timeworn technologies, and disproportionately topology. This study underlines an Afghanistan case study with 40% power losses that is mainly pertinent from old distribution systems. The long length of distribution systems, low-power transfer capability, insufficient control and protection strategy, peak-demand elimination, and unstable operation (low energy quality and excessive voltage deviations) are perceived pre-eminent challenges of Afghanistan distribution systems. Some attainable solutions that fit challenges are remodeling (network reduction), networks reinforcement, optimum compensation strategy, reconfiguration options, improving, and transfer capability. This paper attempts to propose a viable solution using multiobjective optimization method of auto-tap-changer pole transformer (ATCTr). The proposed methodology in terms of optimal numbers and placement of ATCTr can be known as a novel two-dimensional solution. For this purpose, a real case of Kabul City distribution system is evaluated. Simulation results indicate the effectiveness of the proposed method in reducing system losses and improving system overall performance. This approach tends to regulate the voltage deviation in a proper and statutory range with minimum number and optimum placement of ATCTrs. The proposed method is simulated using MATLAB ® environment to compare and evaluate performance of the proposed network under different situations and scenarios. Appl. Sci. 2019, 9, 2813 2 of 13 and management. One of the most effective factors in an electric power energy quality is voltage deviation and stability. Extension of a network length and expansion of topology can be associated with the risk of statutory and standard limit [1]. Kabul is a densely populated and capital city of Afghanistan that distribution networks suffer unstable-rated operation. These networks are extended without length limitation consideration, which demonstrates unstable voltage beyond the statutory range with huge technical and economic losses. In recent years, the government of Afghanistan bounded to retain environmental protection and sustainable development in accordance with the Paris Agreement 2015 (combat climate change), and Sustainable Development Goals (SDGs) 2030. Reform of the energy sector has been part of this endeavor. Afghanistan's distribution networks are the least developed and old-fashioned part of the power system. In addition to the technical and financial losses, shortage of access to electric energy has led to increased utilization of primary energy resources and fossil fuel with high environmental impact. Meanwhile, distribution systems to remote areas are extended without expandability capacity (in local and regional networks) consideration. In priority, it must seriously cons...