Namkung Min, Kwon Younghun
Departments of Applied Mathematics, Tikhonov Moscow Institute of Electronics and Mathematics, National Research University Higher School of Economics, 101000 Moscow, Russia.
Departments of Applied Physics, Hanyang University, Ansan, Kyunggi-Do 425-791, Korea.
Entropy (Basel). 2020 Nov 11;22(11):1277. doi: 10.3390/e22111277.
In quantum computation, what contributes supremacy of quantum computation? One of the candidates is known to be a quantum coherence because it is a resource used in the various quantum algorithms. We reveal that quantum coherence contributes to the training of variational quantum perceptron proposed by Y. Du et al., arXiv:1809.06056 (2018). In detail, we show that in the first part of the training of the variational quantum perceptron, the quantum coherence of the total system is concentrated in the index register and in the second part, the Grover algorithm consumes the quantum coherence in the index register. This implies that the quantum coherence distribution and the quantum coherence depletion are required in the training of variational quantum perceptron. In addition, we investigate the behavior of entanglement during the training of variational quantum perceptron. We show that the bipartite concurrence between feature and index register decreases since Grover operation is only performed on the index register. Also, we reveal that the concurrence between the two qubits of index register increases as the variational quantum perceptron is trained.
在量子计算中，是什么促成了量子计算的优越性？已知的候选因素之一是量子相干性，因为它是各种量子算法中使用的一种资源。我们揭示了量子相干性有助于Y. Du等人在arXiv:1809.06056 (2018)中提出的变分量子感知器的训练。具体而言，我们表明，在变分量子感知器训练的第一部分，整个系统的量子相干性集中在索引寄存器中，而在第二部分，格罗弗算法消耗索引寄存器中的量子相干性。这意味着在变分量子感知器的训练中需要量子相干性分布和量子相干性消耗。此外，我们研究了变分量子感知器训练过程中的纠缠行为。我们表明，由于格罗弗操作仅在索引寄存器上执行，特征寄存器和索引寄存器之间的二分并发度会降低。而且，我们还揭示了随着变分量子感知器的训练，索引寄存器的两个量子比特之间的并发度会增加。
