213214A Common quantum gates

Rainer Müller, Franziska Greinert

Bum-Kyu Kim, Byeong-Sung Yu, Suk‐In Park +3 more

The parallelization of single-electron pumps is a promising method to increase the quantized current level produced from a semiconductor-based single-electron system. In the parallelization of multiple pumps with common gate electrodes, the key process is to fabricate them with high reproducibility, resulting in an overlap of the most accurate regions in current plateaus at the same gate voltages. However, because of the lack of gating reproducibility, we here adopted a separate gate-tuning scheme to realize the overlap of the current plateaus instead of using a common gate scheme. To minimize the number of gates, we used entrance gates in common but an exit gate in separate with an additional in-common gate located outside the quantum dot but near the exit gates. The combination of the additional gate and separate exit gates led to an optimal current plateau overlap with a pair of pumps among six pumps in parallel. Under the optimal plateau-tuned condition, we achieved a relative type-A uncertainty of 1.4 × 10−6 at a 100 pA level with f = 160 MHz in the parallelized mode with the second current plateaus for both pumps.

Md. Belayet Ali, Takashi Hirayama, Katsuhisa Yamanaka +1 more

The NCV (NOT, CNOT and Controlled-V/V) gate set is most commonly used for the realization of classical reversible functions and implementation of quantum circuits. Logic operations in quantum circuits are performed by individual gates or can be expressed as matrix-vector multiplication. Thispaper presents a two-qubit quantum gate library which consists most commonly used elementary quantum gates NOT, CNOT, Controlled-V and Controlled-V. The new library contains all possible two-qubit quantum gates which do not produce entangled states in the final output state. Two approaches have been appliedto generate the new two-qubit quantum gate library because it hasbeen observed that some entangled gates act like non-entangledif those entangled gates are merged with other valid gates in thelibrary. The experimental result shows the difference betweenthe libraries with and without considering entangled gates in theprocess of generating new gates.

Александр Алексеевич Горбацевич, Н. М. Шубин

Yang Shu-yu

The approximation ability of neural networks plays an important role to the result when one uses neural networks to resolve problems.Unfortunately there is no ideal way to construct proper networks with strong approximation ability.A novel construction approach based on the multi-qubits controller-not gates is proposed for neural networks model in this paper.The proposed model consists of three layers where the hidden nodes are the quantum neurons and the output nodes are the common neurons.The quantum neuron consists of the quantum rotation gates and the multi-qubits controllednot gates.The overall memory of input sequences is captured from information feedback of target qubit from output to input in the multi-qubits controlled-not gate.The output of quantum neuron is obtained from the controlled relationship of the multi-qubits controlled-not gate.The L-M learning algorithms are designed in detail based on the basic principles of quantum computation.The features of input sequences can be effectively obtained in two ways of breadth and depth.The experimental results of solitaire forecast show that,when the number of input nodes is close to the length of sequences,the training set recognition rate of the proposed model increases about 8% than the common neural networks,which reveals the effectiveness of the quantum computation for enhancing the approximation capability of the common neural networks.