Pavičić Mladen, Megill Norman D
Nano Optics, Department of Physics, Humboldt University, 12489 Berlin, Germany.
Center of Excellence for Advanced Materials and Sensors, Research Unit Photonics and Quantum Optics, Institute Ruder Bošković, 10000 Zagreb, Croatia.
Entropy (Basel). 2018 Dec 5;20(12):928. doi: 10.3390/e20120928.
Recently, quantum contextuality has been proved to be the source of quantum computation's power. That, together with multiple recent contextual experiments, prompts improving the methods of generation of contextual sets and finding their features. The most elaborated contextual sets, which offer blueprints for contextual experiments and computational gates, are the Kochen-Specker (KS) sets. In this paper, we show a method of vector generation that supersedes previous methods. It is implemented by means of algorithms and programs that generate hypergraphs embodying the Kochen-Specker property and that are designed to be carried out on supercomputers. We show that vector component generation of KS hypergraphs exhausts all possible vectors that can be constructed from chosen vector components, in contrast to previous studies that used incomplete lists of vectors and therefore missed a majority of hypergraphs. Consequently, this unified method is far more efficient for generations of KS sets and their implementation in quantum computation and quantum communication. Several new KS classes and their features have been found and are elaborated on in the paper. Greechie diagrams are discussed.
最近,量子语境性已被证明是量子计算能力的来源。这一点,连同最近的多个语境实验,促使人们改进语境集的生成方法并找出其特征。最详尽的语境集是科亨 - 施佩克尔(KS)集,它为语境实验和计算门提供了蓝图。在本文中,我们展示了一种取代先前方法的向量生成方法。它通过生成体现科亨 - 施佩克尔性质的超图的算法和程序来实现,并且这些算法和程序设计为在超级计算机上运行。我们表明,与之前使用不完整向量列表从而错过大多数超图的研究不同,KS超图的向量分量生成穷尽了从所选向量分量可以构建的所有可能向量。因此,这种统一方法在生成KS集及其在量子计算和量子通信中的实现方面效率要高得多。本文发现并阐述了几个新的KS类及其特征。还讨论了格里奇图。